Health Care Marketing 9781845446703, 9780861767588

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ISSN 0736-3761

J OURNAL OF C ONSUMER M ARKETING Health care marketing Guest Editor: Benn Greenspan

Volume 19 Number 7 2002 This issue is part of a comprehensive multiple access information service Paper format The Journal of Consumer Marketing includes seven issues in traditional paper format. The contents of this issue are detailed below.

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Editorial advisory board . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 543 ........................................................

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Abstracts and keywords Editorial comment Richard C. Leventhal

Guest editorial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547 Loyalty strategy development using applied member-cohort segmentation Steven Cooley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 550 Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years David P. Paul, Amy Handlin and Angela D’Auria Stanton . . . . . . . . . . . . . . . . . . 564 Patient/enrollee satisfaction with healthcare and health plan Karin Braunsberger and Roger H. Gates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 575 Buyer beliefs, attitudes and behaviour: foods with therapeutic claims Suku Bhaskaran and Felicity Hardley . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591 Using data mining/data repository methods to identify marketing opportunities in health care Edward Rafalski . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607 The American Hospital Association’s Annual Survey of Hospitals: a critical appraisal Ross Mullner and Kyusuk Chung . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614 Executive summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 619 Internet currency Edited by Dennis A. Pitta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 628 A note from the publisher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631 Index to volume 19, 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633 Call for papers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 636

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Editorial Advisory Board Raj Arora University of Missouri, USA Andy Aylesworth Bentley College, USA Emin Babakus University of Memphis, USA Siva K. Balasubramanian Southern Illinois University, USA Barry L. Bayus University of North Carolina, USA Blaise J. Bergiel Nicholls State University, USA William Bolen Georgia Southern College, USA D.A. Booth University of Birmingham, UK David F. Birks University of Bath, UK Douglas Brownlie University of Stirling, UK Lee Cambell Bentley College, USA Frank Cespedes The Center for Executive Development, USA Leslie de Chernatony Birmingham University Business School, UK Tom Collinger Chicago, IL, USA Roger Dickinson University of Texas, USA Betty Diener University of Massachusetts, USA Elsie L. Doser Truckee Meadows Community College, USA Robert C. Duke University of Leeds, UK Christopher J. Easingwood Manchester Business School, UK Eugene H. Fram Rochester Institute of Technology, USA Benn Greenspan Evanston, IL, USA Stephen J. Grove Clemson University, USA Lynn Harris Shippensburg University, USA Michael Howley University of Surrey, UK Junying Huang National Sun Yat Sen University, Taiwan Robert W. Hughes Maroon Resources Corporation, USA

William James Hofstra University, USA Joby John Bentley College, USA Scott Johnson University of Louisville, USA Ted Jula Stonehill College, USA Constantine S. Katsikeas Cardiff Business School, UK Carol Kaufman-Scarborough Rutgers School of Business, USA Bob Kearney Denver, USA Inder Khera Wright State University, USA Simon Knox Cranfield School of Management, UK Thomas Kuczmarski Kuczmarski & Associates, USA Geoffrey Lantos Stonehill College, USA Steven Lysonski Marquette University, USA Michael McBride Southwest Texas University, USA Karen Porter Lakewood, Colorado, USA John Richardson Pepperdire University, USA Mary Lou Roberts University of Massachusetts, USA Herbert Jack Rotfeld Auburn University, USA Paul Ruocco Alcan Consumer Products, UK Michael Saren University of Strathclyde, UK Byron M. Sharp University of South Australia, Australia Rosemary Anne Sharp University of South Australia, Australia Elaine Sherman Hofstra University, USA Bob Stone Tuscaloosa, Alabama, USA Bill Thomas USWEST DEX-DPG, Colorado, USA Ugur Yavas East Tennessee State University, USA

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Abstracts and keywords

Loyalty strategy development using applied member-cohort segmentation Steven Cooley Keywords Customer loyalty, Market segmentation, Consumer behaviour, Corporate strategy, Services marketing, Health Marketers in service industries face challenges similar to those in packaged and durable goods. However, the approach to these challenges is often quite different. This case study examines how a health insurance company used common market segmentation techniques to better understand member needs to improve customer loyalty and increase member retention. The author describes a new paradigm for considering customer loyalty in service industries. A two-stage segmentation approach identified four key member cohorts for loyalty intervention. Primary research then uncovered three themes among these members and cohort-specific barriers to achieving loyal relationships. Broad representation on the Customer Loyalty Steering Committee facilitated disseminating results and developing shared learning among organizational units. Planning and implementation efforts using this knowledge were widespread. A comprehensive strategic framework was developed to assess new enhanced services and existing programs against member needs. Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years David P. Paul, Amy Handlin and Angela D’Auria Stanton Keywords Direct selling, Consumers, Advertising, Drugs companies, Doctors, Attitudes Based upon a national random sample of primary care physicians, this study updates earlier investigations of direct-to-consumer (DTC) advertising of prescription pharmaceutical drugs, in light of the explosive growth of such advertising since the late 1990s. The attitudes of the majority of primary care physicians surveyed remain strongly negative, with particular concern about the overstatement of efficacy/exaggerated benefit claims and inadequate risk information. There is, however, a minority of primary care physicians who might be favorably disposed toward DTC prescription drug advertising, provided the pharmaceutical industry addresses the expressed concerns of the medical profession. Patient/enrollee satisfaction with healthcare and health plan Karin Braunsberger and Roger H. Gates Keywords Health care, Marketing, Consumer satisfaction The findings of the present study show that healthier patients, older patients, males, those with a lower level of education, those who perceive system performance to be high and those with lower levels of system usage are more satisfied with both their healthcare and health plan than their opposite counterparts. Regarding the incremental effects of these variables, the most striking finding is the strong, pivotal role of physicians in influencing patient satisfaction with healthcare. In regard to satisfaction with health plan, the extent of the problems that members have had with their health plan has by far the largest statistical influence on their satisfaction with that plan. The effects of other independent variables including the three demographic variables, self-stated health status, number of visits to doctor’s office or clinic, and issues related to access, though significant, show relatively small statistical influences on overall satisfaction with healthcare and health plan. Buyer beliefs, attitudes and behaviour: foods with therapeutic claims Suku Bhaskaran and Felicity Hardley Keywords Food, Health care, Consumers, Attitudes, Consumer behaviour Builds on past studies in the USA and assesses the market potential for functional goods through investigating consumer needs and attitudes. Aims to add to past research through: assessing consumer knowledge and beliefs on nutrition and diet-health relationships; analysing the influence of such knowledge and beliefs of information and sources of 544

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information; and evaluating the effectiveness and implications of government preventative health campaigns on purchase behaviour. Concludes that issues regarding personal and national health are extremely important because of the financial costs and human suffering that could be involved; and that functional goods, as a relatively new phenomenon, still need to be examined further with regard to their influence on trust and legitimacy in buyer behaviour. Using data mining/data repository methods to identify marketing opportunities in health care Edward Rafalski Keywords Data mining, Data storage, Obstetrics Using data mining techniques, opportunities for improving continuity of care, improving patient satisfaction, and enhancing system revenue were discovered at Sinai Health System, Chicago by analyzing the compliance of patients in prenatal care and subsequent delivery at the hospital with which their primary care clinic was affiliated. This led to the development of a telephone survey used to determine why patients who were receiving prenatal care at the health system’s affiliated primary care sites chose to deliver their baby at other non-affiliated hospitals. The results of the survey are being used by management and marketing in order to improve processes in ways that would minimize the lost business. The American Hospital Association’s Annual Survey of Hospitals: a critical appraisal Ross Mullner and Kyusuk Chung Keywords Hospitals, Statistics, Surveys, Error cause identification Data from the American Hospital Association’s Annual Survey of Hospitals, which are used to produce the AHA Guide, Hospital Statistics, and other data products, are widely used by hospital administrators, academic researchers, and healthcare marketers. Although they are widely used, many who use data from the survey are unaware of their limitations and problems. Such problems include: inaccuracies and inconsistencies in reporting; low response rates to certain data items; biases in reporting; and a lack of publicly available technical documentation concerning the statistical methodology of the survey, particularly its estimation and imputation procedures for missing data. Failure to be sophisticated consumers of data products can misdirect the outcome of important planning and marketing efforts.

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Editorial comment

When a ‘‘Call For Papers’’ for The Journal of Consumer Marketing’s Special Issue on Health Care Marketing was announced in September of 2001, I was certain that there was an untapped source of interest in this particular aspect of the marketplace. It has been a gratifying experience to see how both the academic and practitioner communities have responded. As you will see in the articles included in this issue, there is quite a diversity of attention being paid to the application of marketing as it concerns the consuming public. I would like to personally thank Dr Benn Greenspan, Chief Executive Officer of the Sinai Health System in Chicago, Illinois, for taking the time to assume the role of Guest Editor for this Special Issue. His interest and expertise in the area of marketing as it applies to health care is to be recognized, for without his support and dedication this issue would not have come to fruition. Richard C. Leventhal

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Guest editorial

About the guest editor. Benn Greenspan has been the President and CEO of the Sinai Health System since January 1991. He held numerous positions within the growing Sinai Health System for 15 years before he became the CEO. During his tenure as CEO, Mount Sinai Hospital won the Foster McGaw prize – the industry’s national award for creative and effective community health service. The Sinai Health System is widely recognised for its tenacity in serving all patients regardless of ability to pay, in an environment of significant economic challenges. It has become nationally known for the development of a comprehensive fully integrated delivery system in that environment. Benn has a PhD in Public Health Sciences from the University of Illinois at Chicago. He is Adjunct Assistant Professor at the Graduate School of Public Health – University of Illinois – Chicago and holds an adjunct Faculty appointment at the Philadelphia College of Osteopathic Medicine. He was the 2000 recipient of the ACHE Regents Senior Executive Award. Marketing is a term that generally causes confusion among health care professionals. It sometimes even draws derision in the world of health care providers. When it is applied in health care services it is often met with distrust. And, it is almost always misunderstood by management throughout the health care service delivery industry. The health care market is typically characterized as imperfect; confusing; out of control; overly competitive; not competitive enough; monopolized by professionals through licensing and regulation; monopsonistic (driven by a handful of government and private payers); and perverted by the imbalance between consumer and provider. The ‘‘disadvantaged consumer’’ is a term frequently summoned to explain why health care cannot and should not be constructed in a free market model. What role has marketing played in changing the US Health Care System? Do consumers benefit from the application of marketing sciences and tools to the industry? Is there something so immutably different about health care that we should want to preserve it as a ‘‘marketing-free’’ zone? Can we even agree about what the health care industry includes? In the presence of such confusing perceptions and basic (but unanswered) questions, it should be no surprise that marketing theory and practice have been slow to assert a positive presence in health care. Assessing the level of marketing impact on the delivery of health care in the USA must be undertaken in the context of the widely different segments that exist in the industry. Personal services by clinical professionals, the provision of institutional technical and professional services, home based clinical services, long term custodial care, diagnostic testing (both in institutions and at home), therapies services, medical equipment, orthotics, prosthetics, pharmaceuticals, vitamin and other supplements, and health JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002, pp. 547-549, # MCB UP LIMITED, 0736-3761

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foods, are just some of the traditional and emerging segments of the industry. Each has its own set of traditions and rules pertaining to how it is delivered and sold to the public. Some of these endeavors have emerged from traditions of other supply and commodity industries. Some still are struggling to understand how best to move toward a dynamic model that improves the quality and value that consumers (clearly, and almost religiously, identified here as ‘‘patients’’) receive. In this special issue, we are privileged to read about the efforts of several individuals from a variety of these segments. Their work to understand and support the application of professional marketing principles in the varied endeavors of the health care industry provides interesting and current information about the state of marketing in some of the important segments of health care. More important, they provide insight that may be helpful in answering the questions about consumer benefit and the ability of marketing sciences to bring health care closer to that elusive dynamic model that improves quality and value for patients. Introduction of the highest principles of Marketing to Health Care Delivery has the potential to profoundly rebalance the roles of consumer and provider in ways that will improve quality and value. Cooley (‘‘Loyalty strategy development using applied member-cohort segmentation’’) raises the possibility that measuring and attempting to improve customer satisfaction may not be the most effective route to improving customer retention. He presents us with an unusual opportunity to look in on the internal efforts of one of North America’s premier health insurers, as it develops and applies information about its members in an organization-wide initiative to come closer into coincidence with their needs. He offers up a fine example of the scientific method in proposing a new model for thinking about member retention, evaluating the hypothesis, testing it and using the informational tools available to most efficiently implement plan services and health care services informed by the new paradigm. Paul, Handlin and Stanton (‘‘Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years’’) have refined previous studies of the dissatisfaction of primary care physicians with the impact of pharmaceutical industry advertising aimed at consumers. It is no surprise that the physicians sampled continue to express concerns ranging from worries about overstated claims of efficacy to the failure to offer information about non-medical, or lifestyle, alternatives to drug therapy. Primary care physicians also expressed their frustration with the need generated to ‘‘re-educate’’ patients. This disconnect with the physician population may signal further problems in the context of the findings of the next article in this issue. Braunsberger and Gates (‘‘Patient/enrollee satisfaction with healthcare and health plan’’) has looked at the satisfaction of health plan members with their health plan and with their health care. They give us the results of a survey of 76 health plans covering all regions of the USA, and in all of the top 25 major metropolitan areas of the USA. This rare national examination validates some of the earlier research about peoples’ relationships with healthcare and insurance. It also shows that whether it is satisfaction with the care, or with the insurance plan, it is still the underlying relationship with the physician that drives outcomes. 548

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Bhaskaran and Hardley (‘‘Buyer beliefs, attitudes and behavior: foods with therapeutic claims’’) present the findings of focus group studies indicating that consumers are not likely to adopt ‘‘functional foods’’ as a major disease prevention vehicle. While there has been much investment in the rapid growth of the ‘‘nutraceuticals’’ market, and in the concomitant development of regulatory information panels, consumer skepticism is still a powerful force in decision making. Rafalski (‘‘Using data mining/data repository methods to identify marketing opportunities in health care’’) has taken the common retail technique of data mining and shown us how it can be applied to the delivery of health care services to enhance the quality of care, as well as to elevate the organization’s revenue. He suggests that as in other consumer markets, health care can effectively learn to improve its product not only through technological innovation, but also through patient researched and driven service improvement. Mullner and Chung (‘‘The American Hospital Association’s Annual Survey of Hospitals: a critical appraisal’’) point out in their commentary that the search for market intelligence in health care is not without its risks. They remind us that the most commonly available sources of data, often voluntary submissions, may have intrinsic problems of consistency, accuracy and methodology that must be accounted for. Benn Greenspan

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An executive summary for managers and executive readers can be found at the end of this issue

Loyalty strategy development using applied member-cohort segmentation Steven Cooley Manager, Market Research and Loyalty, Marketing Strategy Group, Blue Cross and Blue Shield of Illinois, Illinois, USA

Keywords Customer loyalty, Market segmentation, Consumer behaviour, Corporate strategy, Services marketing, Health Abstract Marketers in service industries face challenges similar to those in packaged and durable goods. However, the approach to these challenges is often quite different. This case study examines how a health insurance company used common market segmentation techniques to better understand member needs to improve customer loyalty and increase member retention. The author describes a new paradigm for considering customer loyalty in service industries. A two-stage segmentation approach identified four key member cohorts for loyalty intervention. Primary research then uncovered three themes among these members and cohort-specific barriers to achieving loyal relationships. Broad representation on the Customer Loyalty Steering Committee facilitated disseminating results and developing shared learning among organizational units. Planning and implementation efforts using this knowledge were widespread. A comprehensive strategic framework was developed to assess new enhanced services and existing programs against member needs.

Member retention

Critical mass

The objective of the program detailed in this case study was to assess consumer needs toward a goal of increasing member retention. Our process relied on gaining a deep understanding of member cohorts derived via segmentation. Primary outcomes included common themes for establishing a strong relationship between members and our health plans, as well as cohortspecific activities to enhance that relationship. The company responded by changing the way we do business. The learning provided by our membercohort segmentation drove changes in infrastructure, our decision-making processes and our call center management strategy. The processes, findings and responses are detailed below. Member loyalty during growth and change In early 1998, Blue Cross and Blue Shield of Illinois (BCBSIL) had been experiencing a period of high growth. There was rapid growth in our local managed care products and we had a number of large marquis accounts that considered us a valuable partner. However, in the midst of this growth, BCBSIL was also facing great challenges. There was considerable consolidation in the marketplace. A number of key competitors, both locally and nationally, were beginning to concentrate their operations via mergers and acquisitions. Once a competitor grew to critical mass, it would be in a better position to disrupt our relationships with network providers and clients. Not surprisingly, industry research revealed that most people have a negative attitude toward insurance in general. The reactions are emotional, not The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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intellectual, and this reaction carries over to all forms of insurance. Three reasons that were cited for the response were: (1) You only use insurance when there is a problem so you associate insurance with a negative situation that prompted its use. (2) Most people believe that they pay a lot for coverage; yet making a claim to their insurance only leads to problems. (3) There is a lack of trust in the system because consumers are not sure of how insurance or the health care system work. High-risk outcomes

The nature of the insurance industry creates volatile customer relationships. Especially health insurance, which is a low involvement category – most people are not very involved with their health care financing. However, it involves potentially high-risk outcomes that can create the opportunity for someone who has not been paying attention to get into a large financial predicament, which generates a negative response. Since our own prior research had shown that customers are generally satisfied with their current carrier, we believed that there should be a new focus on non-product, emotional reasons for switching. All of the prior findings focused on satisfaction, not the likelihood to retain customers so we wanted to explore that issue a little differently.

Retaining members

Finally, another continuing threat was the pressure to do more. Competitors began launching HMO products that featured open access to specialists. New member welcome calls and member-retention programs appeared in the marketplace. Affinity and discount programs were becoming the norm, while a backlash against managed care surged within the media. So the loyalty challenge was learning how to retain members in the midst of this growth and change. BCBSIL approach As market share grows, retention becomes increasingly important for maintaining share. Since we had been sustaining growth in 1998, we chose to focus our attention on increasing retention. We determined, based on some of the enlightened marketing thought at the time, that BCBSIL could also improve growth by concentrating on retaining members as opposed to simply bringing new members into the front door. The process we undertook involved establishing a Customer Loyalty Steering Committee comprised of senior executives representing marketing, sales, health care management and subscriber services (i.e. claims processing and customer service). Including a wide array of organizations within the company was a critical success factor. By doing so, we created a shared sense of commitment and ensured communality of learning and communication across these key divisions.

Understanding members’ needs

The Steering Committee was charged with understanding member needs and providing opportunities to increase member retention. This increased focus on the member was new for the BCBSIL Group Markets Division. Prior to that point, the key focus of marketing efforts had been on the employer account decision-maker. The member was considered the secondary sale. After the employer had chosen BCBSIL products, they were then sold again to the member at open enrollment. The definition of victory for the Steering Committee was to generate longterm competitive advantage through improved member loyalty. The path

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chosen to reach that goal required exploring the antecedents of customer loyalty and determining opportunities for enhancing our relationship with consumers. These efforts contributed to our understanding of consumer desires by first identifying high-impact cohorts of members. Next, we conducted in-depth qualitative research on those cohorts. And finally, we detailed new perspectives on how we should interact with our members. Develop understanding

The objectives were to develop that core understanding of what drives loyalty for key member segments in the Illinois marketplace and how BCBSIL compared to competitors along loyalty dimensions. We wanted to create an initial strategy to improve member loyalty in targeted segments as well as strengthen the company’s focus on members. Finally, we wanted to provide input into the budgeting process for loyalty initiatives going forward. The Steering Committee focused the efforts of staff. We included external support via a third party management consulting firm to help staff the program. The final component was the development of an in-house market research program to support the information needs of the Steering Committee and the staff who were involved in developing these strategies. Customer loyalty Before detailing the research program, let us briefly examine a seminal shift in the loyalty paradigm as adapted by BCBSIL. There had been some backlash in the popular business press and market research literature against customer satisfaction measurement. A number of companies across various industries had adopted customer satisfaction as a key management tool in the late 1980s. Then there was disillusionment with these programs in the 1990s. Although many companies that had adopted customer satisfaction programs saw increases in their satisfaction scores, they were still seeing customers leaving their business.

No guarantee of loyalty

We determined that satisfaction alone was no guarantee of loyalty within our own HMO membership. As shown in Figure 1, an empirical study revealed that approximately 18 percent of voluntary disenrollees provided an ‘‘excellent’’ rating for member satisfaction. During the same time frame, 19 percent of active members rated their health plan product ‘‘excellent.’’ There was no differentiation between current members and recently disenrolled members who left the plan voluntarily. These members did not leave through a job change or having that product taken away from them by their employer, but left for a competing product offered by their employer.

Figure 1. Survey rating responses by member states 552

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However, there was a difference within that empirical study in the percentage of those who said they would recommend the HMO to others. A similar difference was apparent for those who said that they would likely stay enrolled (or re-enroll in the case of the disenrollees). Here only 22 percent of the voluntary disenrollees would recommend BCBSIL to family or friends while 42 percent of existing members would. Among the voluntary disenrollees, 28 percent would have liked to re-enroll with BCBSIL’s HMO, while 47 percent fully intended to stay enrolled. So the differences between these two categories of consumers were not captured in satisfaction ratings; rather, they were seen in the behavioral intention measures.

Change in perspective on loyalty

Two-dimensional loyalty model Another thing that we saw occurring in the customer satisfaction arena was a change in perspective on loyalty. From a single continuous measure – low loyalty through high loyalty – the idea evolved that there are multiple drivers in the marketplace. A consumer could be very satisfied and feel very committed to their current carrier. If, however, the price point (the employee contribution) between their current carrier and a competing offer shifts substantially, then we have an external market force that could impact loyalty. Such external issues are not captured by the satisfaction measurement paradigm that focuses internally. Our approach to this was to change how we looked at satisfaction and loyalty. We chose to look at loyalty in two dimensions. First we considered the member’s commitment to the current carrier. The two items on which we earlier saw differentiation, ‘‘likelihood to recommend’’ and ‘‘likelihood to stay or switch’’ were added together. That combined measure was then applied in a two-dimensional loyalty model that would also involve some measure of shopping behavior. Doing this accounts for both internal commitment and external market forces. The key issue is whether a member would seriously consider other carriers when they had the opportunity. A quick review of the marketing literature did not produce a clean measurement scale for shopping behavior. Examples were either product category-specific or too strongly couched in terms of consumer packaged goods to be useful in a service industry.

Chicago metropolitan market

The best measure among those available in our datasets seemed to be a perceptual measure of health plan value. Therefore, our theoretical position was that if someone had a low perceived value for their current carrier they were more likely to consider alternatives when the opportunity arose. However, those who perceived a high value would be less inclined to ‘‘shop.’’ We were able to evaluate this loyalty model using our standing database, which included the Sachs data, a marketplace measure of consumers in the Chicago metropolitan market. Attitudinal loyalty segmentation Our exploration of member loyalty then turned to database analysis using a double segmentation process. The first step was to segment respondents based on their attitudinal loyalty using the new commitment measure, again ‘‘likelihood to recommend’’ and ‘‘likelihood to stay or switch’’, combined into a single score against the value item which was the inverse of one’s likelihood to shop. When respondents were segmented based on these dimensions, we found a clean break into the three general areas displayed in Figure 2. The first and most loyal group, which we termed ‘‘faithful,’’ represented about 25 percent

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Figure 2. Two-dimensional loyalty model with attitudinal-based segements

of the Chicago commercially insured market. They saw high value in their current health plans and had an extremely high level of commitment to them. At the other end of the spectrum were the ‘‘fickle,’’ about 13 percent of the market. Regardless of the value that they saw in their current coverage, they had a very low level of commitment to their health plans. These consumers reported that they definitely wanted to leave and they definitely would not recommend their plan. The remaining 62 percent of the Chicago-area market fell into three distinct sub categories we combined into a group that we called ‘‘prudent.’’ Moderate commitment

Drilling down one level reveals the differences among these three distinct subgroups within the prudent segment. One sub-segment had moderate commitment but perceived very high value in their current coverage. They were not fully loyal to the health plan but they were not ready to leave as they did recognize high value. An opposite group demonstrated very high commitment but low perceived value. While highly committed to their health plan they did realize they were paying a price premium. Finally, the third subgroup combined aspects of the prior two – with moderate commitment and moderate to low value. One-half of the 62 percent of the market that comprised these three sub-segments were on the borders surrounding the faithful region. In order to validate the segments we examined the participants’ self-reported reaction to the most recent open enrollment opportunity. There was an item within the study through which we were able to determine whether they stayed enrolled because they wanted to, because they had no better choice or because they had no choice at all. Looking across the three segments we found that 98 percent of the faithful segment exhibited a strong repeat purchase behavior; they reported staying because they wanted to stay.

Lower desire to look elsewhere

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Only 11 percent of the fickle population had actively chosen to stay. Most of this segment reported they had no other choice and the remaining had no viable choice. Either the other products they had to choose from were too expensive or did not fit their needs – they were stuck with the carrier coverage they had. The difference was that the faithful reported much stronger repeat purchase behavior, stronger advocacy for their current carrier JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

and a lower desire to look elsewhere. They also had a high regard for plan value. Conscious, proactive decision to renew

Who are the faithful? They comprised approximately 25 percent of the commercial marketplace. Database analysis of the segments reveals that the faithful were more likely to be in managed care products than the marketplace overall and were more likely to have BCBSIL coverage than the market norm. They made a conscious, proactive decision to renew. Demonstrating a strong likelihood to stay with their current carrier, they reported a higher incidence of carrier choice than other segments did and they were likely to stay with their health plan for at least five years. They provided high satisfaction scores across the entire array of plan services, although they did express belief that there was room for improvement. The cost-value benefit and the quality of administrative services were also important issues among these respondents.

Transforming prudent members into faithful members

Based on our focus groups we found that the faithful were very content with their current carrier. They did see that problems exist, but the general perception was that ‘‘nobody’s perfect.’’ Some had service problems and issues with referrals or emergency care, but their positive experiences were shaped by how their plan handled their health care crises. The attitude was influenced by the overall experience. They were more assertive, would not accept ‘‘no’’ for an answer and they were more proactive than typical. The goal of the BCBSIL Customer Loyalty Steering Committee was to gain a better understanding of how to transform prudent members into faithful members. Criterion-based segmentation Why target the prudent segment? That group provided the most potential for loyalty improvement initiatives. It represented almost two-thirds of the commercial marketplace and the majority was already leaning toward being faithful, not fickle. This decision recognized that faithful members, whether our own members or competitors’, were too strongly ingrained with their current carrier to make effective targets for acquisition. They also did not require additional retention efforts. On the other end of the scale, the fickle members were already looking to leave. We determined it was not an effective use of marketing resources to try and bring them back into the fold. The conclusion was that it was much more cost effective to focus on the large segment of current prudent members and increase their loyalty.

Primary research

The next stage of the research program involved primary research on prudent members. To accomplish this objective we needed to determine an approach for identifying high concentrations of prudent members within the BCBSIL membership. This entailed conducting a second wave of database research. We needed to clarify what actionable member information was readily available to locate these individuals and how we could effectively target the right individuals for loyalty intervention. Our approach used CHAID, an algorithm that provides criterion-based segmentation on identifiable variables. The pool of potential segmentation variables included demographics (e.g. age, gender, etc.), socio-economic status (e.g. education and income levels) and self-reported health status. The data also included some information on health care consumption such as usage of primary care, hospital or emergency room services within the past year as well as employer size. Employer size had been considered a key variable as our sales and marketing approaches were segmented into local small groups, medium groups and national accounts. Another set of obvious

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variables encompassed health plan information such as product type (HMO, POS, PPO or traditional indemnity), health plan tenure and whether the member had a choice of health plans. Health plan choice for members was not available for very small groups (less than 50) until very recently, although BCBSIL and a couple other carriers now offer health plan choice to the small group market. External consultants

An important observation, especially given the expectations of our external consultants, was that socio-economic status, health status and some of the external marketing factors were not important drivers of member loyalty. An initial hypothesis proposed that members utilized a loyalty test flow process. Take certain issues such as claims processing turnaround, the availability of information, cost of the plan and provider relationships. These issues could be impacted by a critical event such as changes in employer contribution levels, employers adding another carrier, competitor modification to their product offering, or a job or family status change. Then, during the open enrollment period, decisions would be influenced by the critical event. Alternatively, members could fall into a ‘‘low involvement’’ category where they followed an inertia effect, not bothering to make the choice – they just continued with what they had.

Primary driver was tenure

Our modeling with CHAID did not support the loyalty test flow hypothesis. We found that those issues did not drive the likelihood of someone being a prudent member (that is, not wholly loyal, but someone who is close to becoming loyal). The key segmentation variables, selected via the algorithm, from that exhaustive list were limited to five simple items. The first and primary driver was tenure (new vs established members). Others included product type, one utilization issue (whether they visited a primary care physician or not within the past year) and a couple of demographics (gender and age categories). Targeted member cohorts The segmentation revealed four key cohorts as displayed in Figure 3. Recall that 62 percent of the marketplace was comprised of prudent members. The four target cohorts that were identified using CHAID consisted of between 82 percent and 95 percent prudent members. The hit rate for finding prudent

Figure 3. Criterion-based segmentation: target member cohorts 556

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members within these identifiable cohorts was much greater than would have been possible just using a blanket market-wide strategy. And the defining variables were quite different than what our content experts would have had us focus on had we not run the second segmentation. The first two cohorts were new members; the second two cohorts were more established but not yet long-term members. New members were defined as having less than six months tenure with their current carriers while established members ranged from six months to five years of tenure. (1) The first cohort included only the HMO members among those who had been with the health plan less than six months. Among this cohort 95 percent were prudent, 5 percent were fickle and therefore already lost; there were no loyal members within this group. (2) The second highest cohort, at 94 percent prudent members, also involved members with tenure less than six months, but it included only females, 18-34 years old, with non-HMO coverage. (3) The third group included only females, aged 35-64 that did not visit a PCP in the past year. It was considered atypical behavior for mature women to not see a physician within the past year. (4) The final target cohort included only males, aged 18-34 that visited a PCP in the past year. Again this was atypical behavior in that young adult men are less likely to see physicians on an annual basis. Positive relationship

Briefly considering the member life cycle, there was a trend toward more loyalty as members became further entrenched within their health plans. So during the early stages, for cohorts 1 and 2, the goal is to initiate a positive relationship with the member. For the established members, especially those in cohorts 3 and 4, we want to further develop that relationship. Our longterm crowd (those with five or more years of tenure) primarily falls into that faithful group where the objective is to maintain the relationship. Member-cohort focus groups The next phase of the research program turned on getting an in-depth understanding of what these member cohorts were looking for from their health plan via primary qualitative research. The process involved conducting focus groups among members segmented by their cohorts to leverage a commonality of participant perspectives within each session. However, we not only broke out the four target cohorts, but also included a couple of focus groups with faithful members to find out what the goal relationship was like. Specifically, we aimed to find out what the end result of our efforts should be. That is, how the members in our four target cohorts should look within a few years.

Quick resolution

The primary research finding identified three underlying themes for all members. These included a focus on the well being and wellness of oneself and one’s family, navigation of the health plan and problem resolution. With respect to navigation, people want to do things correctly the first time without having to go through a lot of process in order to understand what they should be doing. Also, when some problem or error occurs, members want it resolved quickly and with a personal touch, and want to be informed when it is resolved. One does not typically expect this to occur in health care insurance. Participants reported perceived barriers to these goals in the focus groups. For well being and wellness, most people wanted to stay healthy but they

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were not always sure what needed to be done in order to stay healthy. There were no incentives in their current health plans to stay healthy. Many members experienced difficulty selecting the correct doctor. As for health plan navigation, members reported that there was not enough education and communication from their health plan. They did not understand the emergency care policies and they saw referrals as an obstacle to care. Finally, for problem resolution, one perceived barrier was difficulty in finding someone within the health plan to help him or her solve their problems. Another was the feeling that health plans did a poor job of followup regarding the resolution status of their questions and issues. Further detail on the focus group findings (the results of our qualitative research on the member cohorts) is provided below.

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New member findings Looking at the results for cohorts 1 and 2, we found early relationship themes. The first was a lack of control and empowerment. Participants expressed the opinion that shopping for health plans was different from other services such as banking and auto insurance. The employer, not the member, made the primary choice. From the employer one got few choices, if any, among health plans to choose from. Members could not switch at any time as they could with a bank or auto insurance and the process was not customerfocused. Also, product choice cannot substitute for carrier choice, so having multiple products from the same carrier was not seen as being as valid a choice as multiple products from different health insurance carriers. They felt that there was little flexibility given to allow people to make judgment calls.

Format of information critical

Another early relationship issue was termed ‘‘dazed and confused.’’ Consumers did not feel well informed. They thought that the existing member materials were either insufficient or too complicated for them to use. When they did try to find out how to do something with their health insurance they found that the answers could vary by the source (depending on who they spoke to, they got different answers). And they worried about breaking the rules and suffering the consequences. Participants also expressed that they must learn from experience. The school of hard knocks often provided access to information only after it was needed and too late for making the right decision. Learning health plan rules and procedures was not a priority before they needed to use the plan. When members received the information initially there was no real incentive for them to read all the regulations and know what to do ahead of time. They also needed assistance processing the information. Much of the information was not provided in a format they could use.

Personal attention

The final theme regarding the early relationship was personal attention. Consumer participants from cohorts 1 and 2 expressed a desire for personal service similar to an insurance or travel agent. They wanted proactive follow-up and sought a customer champion who would help coordinate care. The champion would know their personal health care experiences and needs and be able to assist them with navigating the system. An especially poignant quote from one session was, ‘‘If you have a travel agent, every time you call them, you don’t have to say ‘Well I don’t want to sit in the smoking section and I want a window seat,’ because they already know that.’’ The key for health insurance carriers is that members expect us to know them as well as their travel agents do. JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

Differences based on demographic make-up

There were some cohort-specific differences as well. The first cohort, HMO members for less than six months, looked for features such as a 24-hour customer service line and phone triage for referrals. They asked for a list of frequently asked questions and tip sheets – possibly wallet size that they could take with them. The second cohort, which also had less than six months tenure and included females, aged 18-34, was looking for better coordination of care, possibly via job-site visits, and help with frequently asked questions. So the needs of these two groups, though highly consistent by virtue of their new member composition, also reflected differences based on their demographic make-up. Some of the differences between the HMO product and non-HMO products and what members were looking for in a health care plan were also reflected. Established member findings Relationship themes from the established members (cohorts 3 and 4) included a focus on wellness and the desire for additional support. The mature women of cohort 3 focused on learning how to take better care of themselves and their families. Other personal and family matters often distracted them from personal health maintenance. They were so busy leading their families through other issues that their own health concerns fell by the wayside. One quote from a participant in cohort 3 was, ‘‘Anything I want is not covered; things I want, like wellness care.’’ Another participant, referring to preventive care services, said, ‘‘If they offered it, they wouldn’t have as many surgeries as they do because they’d be catching it a lot sooner.’’

Health care not a concern until major health event

There were two distinct qualifiers for the younger men in cohort 4. One was an active lifestyle, with an emphasis on wellness. These members wanted to maintain their health so they could maintain their active lifestyle. Health care was not an important concern until a major health or lifestyle event occurred. Examples included an acute health condition or an impending marriage or the addition of children to the family. The other factor that caused young men to qualify for this cohort was a recent occurrence of some catastrophic ailment such as cancer or substance abuse. These conditions increased utilization and prompted follow-up care with primary care providers. A second relationship theme for the established members was the need for affirmation and reassurance that they were doing things right. These participants voiced a strong desire to play by the rules but were often not sure how and when the rules applied. For instance, emergency situations and special cases caused them greater anxiety. They felt that the rules were not applied consistently and thought that maybe victory goes to those who fight hard enough. If you pushed back against the rules, there was an opportunity to bend some in your favor. They also looked for someone or something to tell them what was covered, expressing the belief that they only received negative reinforcement. This might have occurred when being told that something that they already did was not covered rather than being told in advance that it would not be covered.

Personal attention

Finally, the third key theme from the established members was personal attention. It appeared that they were looking for value and focused on high quality service. Members reported paying a great deal of money, between themselves and their employer, and expected excellent service for the price. Established members also sought support mechanisms for handling problems. However, they wanted more of an advisor instead of the champion desired by new members.

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Concerns centered on their families

As one might expect, the cohort-specific differences among established members were primarily due to demographic issues. The mature females in cohort 3 had a broader view of how they wanted to include alternative care, weight management or stress management to improve and maintain well being. They placed a greater emphasis on choice and flexibility. Many of their health concerns centered not on themselves but on how to take care of their families. The fourth cohort (younger adult males) was more focused on cost and coverage, with their health concerns focused on how to protect themselves and their families. They also had strong opinions on their own physician selection. To summarize, there were three general problem areas: difficulty resolving problems with the health plan; difficulty navigating the health plan; and, health plans not being focused on wellness and well being. Cohort-specific needs and desires from each targeted member group that provided additional nuance were also captured and documented.

Redesign of customer service experience

Company response Activity toward these drivers has occurred throughout the organization. The Marketing Division updated communication programs and launched a number of enhancements to the Welcome Call Program. Health Care Management staff has continued to develop new quality and service initiatives. Subscriber Services developed the Health Operations Service Plan to address the full roster of these issues within the call center context by redesigning the customer service experience. Separately, we have developed strong assessment tools, including the Continuous Tracking Program and revised transaction-based surveys to provide ongoing measurement and aid our management of customer health plan interaction. Below is a brief review of some programs addressing each of the needs expressed by our target member cohorts. Targeted interventions The Welcome Call Program was established as an orientation program for new HMO members to help with navigation issues. The objective was to improve satisfaction and loyalty among these members. The results have shown an increase in retention of at least 7 percent for those new members who received a completed welcome call contact. This contact also generated a positive perception of the health plan and we find that effective behaviors can be encouraged when the program script is focused properly.

Positive impact on customer loyalty

The objective of our ‘‘Just In Time Communications’’ redesign was to improve member understanding of health plan features. The program focused on information relevant to a member at a particular point in time, (i.e. at enrollment, in case of emergency, etc.) and redesigning the collateral materials to target issues important to members. One of the steps in this program involved identifying topics critical at the time of enrollment. Developing information and activities to encourage quick and effective integration of new members was another. The final step was redesigning the format of the communications materials. A separate component of this program was to measure the performance of new materials to ensure that the new themes identified in the focus groups were having a positive impact on member loyalty. This testing was also used to uncover differential impact on the various customer segments. Redesigning the Explanation of Benefits (EOB) addressed problem resolution. The objectives were to satisfy customer needs and corporate

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business requirements while improving our corporate image. The program intended to demonstrate accountability and responsiveness to our customer base. Expected outcomes of redesigning the EOB were simplified language, clearly identifying who owes what to whom and leveraging this vehicle as an opportunity to educate members. Targeting members with chronic medical conditions

BCBSIL has sponsored a variety of programs in the realm of wellness and well being, many targeting members with chronic medical conditions by offering specific interventions. The objectives have been to encourage healthy behavior among our membership and demonstrate BCBSIL’s commitment to member well being. Key issues for the company included determining how existing BCBSIL programs impact loyalty and identifying critical success factors that can be incorporated into new programs. Our plan was to evaluate the existing programs, develop recommendations for structuring these programs within a strategic framework and identify potential pilot programs to address any gaps in that framework. Broad organizational implementation Another aspect of the company’s response has been the rapid acceptance of both the concepts and findings. We saw the learning derived from this program being used throughout the company. Health care management, marketing, sales and subscriber services all incorporated the information from the customer loyalty research program into their planning and budgeting for the next year. This can be directly attributed to having representatives from multiple constituencies within the corporate structure at the table.

Restructure of customer service experience

Probably the most aggressive approach was taken by subscriber services in developing the Health Operations Service Plan. This three-year vision document completely restructured the customer service experience for members contacting the call center. The effort included 16 work groups that focused on components of the service experience from the job description of the service representatives all the way through to the structure of the service organization. Also included were redesigning the technical infrastructure of data and voice communications and the systems used to support service representatives interacting with members. Revised evaluation tools were established to monitor improvements.

Individual member needs

A special point should be made that this division did not focus solely on problem resolution as one might expect from a call center organization. Instead, they embraced both navigation and well being as being within their purview in that the service representative is the human face of the company to the member. Therefore, all three of these issues fell within the context of that job. How broadly operations staff use and implement the insights gained from market research is a true test of a research program’s success. At BCBSIL, Health Care Management, Marketing and Subscriber Services have been applying the same process framework (i.e. segment, select subset to target and focus efforts on the target) to meeting individual member needs. The evaluation components of management’s response were also critically important. It would have been insufficient to simply find out what members needed, using cohorts or any other segmentation process, without building in the mechanisms to find out if the new initiatives had any impact on the three drivers. Our primary measurement components included an overall member satisfaction and loyalty-tracking program that was put in place at about the same time. Also, we redesigned member transaction surveys conducted by the service organization on claims and customer service experiences. Both of

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these vehicles included the concepts of well being, navigation and problem resolution as issues to be examined when looking at the relationship between the member and the health plan.

Assessment of increase in loyalty

Recent efforts Another positive response by management was to initiate an inventory of the member-facing programs to better understand the program objectives, which of the three loyalty drivers each address, and if gaps remain between what members want and what was currently being done for them. A review process has been put in place to look at these programs and explore how well they impact member retention to assess if there is any increase in loyalty to the company for having initiated these programs. Wellbeing issues dominate the 36 current initiatives that were reviewed at BCBSIL. Many of these are primarily niche clinical programs that attempt to restore health such as asthma care or diabetes intervention. There are also well being initiatives, for instance the neo-natal and the immunization programs that focus on supporting health.

Three key drivers

Follow-up primary research in 2001 confirmed that the three key drivers of loyalty (navigation, problem resolution and wellbeing) still matter to members. Wellbeing seemed paramount among these three in the general population. Consumers are seeking a holistic approach, not just physical health but mental and spiritual health. There is a broader scope among members of what wellbeing means than for the other two drivers. Possible directions for additional research and planning include new segmenting approaches. Options include focusing on what kind of interactions people are having with their health plan and the health system and how that impacts their loyalty. Also, focusing on households with and without children may provide information on what is going on within a household that might be blurring some of the health care issues for the primary care initiator, most often the female head of household. Finally, one might examine member’s perspectives on using health as an empowering force. Summary The Customer Loyalty initiative at BCBSIL succeeded in refocusing management and staff on consumer members and building member retention. The process identified high-impact customer segments and discovered hot-button issues for the targeted membership cohorts (promoting wellness and well being, making health plan navigation easier and improving problem resolution).

Strategic framework

Further exploring cohort-specific needs helped establish a strategic framework for evaluating consumer driven programs. Many of these initiatives were already underway as the customer loyalty strategy was being developed. There was a natural fit between the strategy and ongoing programs and operations. Thus the loyalty strategy was able to provide a strategic framework for both new and existing programs. The framework can also be used for designing a range of initiatives to address the health plan fundamentals provided by the research program. We believe that improving these fundamentals will not only add value to the target members in early stages of their relationship with BCBSIL, but will also apply to the vast majority of our customers. We also feel a need to

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continue to build on this progress in gaining deeper understanding of our customers, their employers and the underlying market trends.

Four major findings

Managerial implications The four major findings of this case study are: (1) Health plans can fundamentally change the way they do business by focusing on their current members and retention efforts. The first step to becoming consumer-centric is to concentrate on the customers. (2) The common management practice of segmenting markets and targeting specific customers can be used within health plans to better focus efforts on those members that can best benefit from the additional attention. This is similar to some of the new medical management approaches being implemented by health plans on the clinical side. (3) Broad involvement at senior levels of the organization within the Steering Committee can facilitate dissemination and implementation efforts. Much of the success of the loyalty program was owed to the dissemination of the findings throughout the organization. (4) The customer loyalty research that was conducted positioned the company to respond to the rising wave of consumerism in the health care marketplace. At the time of this research program, there were already a number of high-quality customer-driven initiatives being conducted throughout the organization. The loyalty strategy provided a framework to consider these programs and new ideas against member requirements.

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An executive summary for managers and executive readers can be found at the end of this issue

Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years David P. Paul Assistant Professor of Marketing and Health Care Management, Monmouth University, New Jersey, USA

Amy Handlin Associate Professor of Marketing, Monmouth University, New Jersey, USA

Angela D’Auria Stanton Assistant Professor of Marketing, James Madison University, Virginia, USA

Keywords Direct selling, Consumer, Advertising, Drugs companies, Doctors, Attitudes Abstract Based upon a national random sample of primary care physicians, this study updates earlier investigations of direct-to-consumer (DTC) advertising of prescription pharmaceutical drugs, in light of the explosive growth of such advertising since the late 1990s. The attitudes of the majority of primary care physicians surveyed remain strongly negative, with particular concern about the overstatement of efficacy/exaggerated benefit claims and inadequate risk information. There is, however, a minority of primary care physicians who might be favorably disposed toward DTC prescription drug advertising, provided the pharmaceutical industry addresses the expressed concerns of the medical profession.

Advertising is an effective stimulus

Introduction and literature review Direct-to-consumer advertising of prescription drugs is defined as any promotional effort by a pharmaceutical firm to present prescription drug information to the general public through the lay media (Kessler and Pines, 1990). This marketing approach is no longer the novel experiment it was during the 1980s and early 1990s. Thanks to progressive liberalization of FDA regulations, coupled with a substantial body of evidence that DTC advertising is an effective stimulus to consumer purchase behavior (for examples, see Pinto et al., 1998; Sherr and Hoffman, 1997; Roth, 1996), it is now a standard, rapidly growing component of every major pharmaceutical company’s marketing plan. By 1998, the industry was spending $1.3 billion on DTC advertising – a 20-fold increase over 1991 spending, and more than US companies spent on advertising beer (The Economist, 1998). In fact, in 1998 one company, Schering-Plough Corporation, spent more on advertising its flagship product, Claritin, than the Coca-Cola Company spent advertising Coke (Harris, 2000). DTC pharmaceutical sales were nearly $2 billion in 1999 and $2.5 billion in 2000 (Bittar, 2001). Overall, DTC advertising The authors gratefully acknowledge the support of this research by a Summer Research Grant from the Monmouth University Business Council.

The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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spending increased by 134 percent between 1997 and 2000 (National Institute for Health Care Management and Education Foundation, 2001), while DTC print expenditures rose from $573 million to $898 million, or 57.3 percent (Fetto, 2002). The Centers for Medicare and Medicaid Services anticipate that prescription drug spending over the next ten years will continue to be the fastest growing component of health care spending, even though the annual rate of growth is expected to fall from the approximately 17 percent observed in the last few years to perhaps 10 percent (Marketing Health Services, 2002). Research since the mid-1980s has compared consumers’ perceptions of DTC advertisements with physicians’ perceptions of DTC advertisements. While methodologically diverse, the results of many studies have been directionally consistent. The key findings are summarized below. Key findings

Consumers generally have positive attitudes toward DTC advertising (for examples, see Alperstein and Peyrot, 1993; Everett, 1991; Williams and Hensel, 1995; Pinto et al., 1998), viewing it as a valuable educational resource, which helps them become more involved in their health care. A significant proportion of DTC readers/viewers claim to have directly acted on the message by talking to their doctor about the advertised brand. Additionally, consumers report that they are more likely to take prescribed medication and/or get their prescriptions filled when prompted by DTC advertising. The major weakness of DTC advertising, according to consumers, is its failure to provide sufficient information, or to convey important information clearly (Levy, 1999; Roth, 1996; Smith, 1998). Thus, it is not surprising that a recent content analysis of product-specific DTC prescription drug advertisements in 18 divergent lay magazines from 1989 to 1998 concluded that the educational quality of advertisements was ‘‘highly variable’’ (Wilkes et al., 2000, p. 116), and a telephone survey of 1,000 consumers found that 45 percent thought that DTC advertisements lacked important information, specifically side effects (Dickinson, 2001) and information about available treatments (Levy, 1999). However, research as to the advisability for the inclusion of such additional information in DTC advertisements is mixed. One study found that inclusion of both promotional information and risk-related information in DTC advertisements may lead to problems with consumers learning each type of information (Schommer et al., 1998), while another found that adding information about side effects made DTC advertisements more trustworthy to consumers (Goetzl, 2000).

PCPs strongly opposed to DTC advertising

Doctors, however, have been far less enthusiastic about DTC advertising, with the majority expressing the wish that it be decreased or discontinued (Cohen, 1988). In most studies, only small minorities believe that it contributes in a positive way to the doctor-patient relationship (for examples, see Medical Marketing and Media, 1998; Sherr and Hoffman, 1997). An exception is Petroshius et al. (1995), but in their study primary care physicians (PCPs) accounted for less than one third of the physicians surveyed. Generally speaking, PCPs are strongly opposed to DTC advertising (Wilkes et al., 2000), as evidenced by a study in which about 80 percent of family practice physicians were determined to be opposed to DTC advertising (Lipsky and Taylor, 1997). It should come as no great surprise that health care professionals do not like DTC advertising, as they have for years had grave misgivings about pharmaceutical manufacturers’ claims in general. Information provided to physicians by pharmaceutical companies has been characterized as frequently biased and unbalanced (see, for example, Wilkes et al., 1992;

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Lexchin, 1997). Reasons for physicians’ concerns about pharmaceutical companies’ communications with them come in several forms. A study of pharmaceutical advertisements in ten leading medical journals examined both the accuracy of scientific data of 109 full-page prescription drug advertisements and the compliance of these advertisements with FDA standards (Wilkes et al., 1992). It concluded that 38 percent of the advertisements potentially violated five or more FDA standards, 40 percent did not present a fair balance between adverse effects and effectiveness, and 47 percent did not highlight potential problems with the drug in special populations (e.g. the elderly). A more recent study of pharmacists confirmed one of these conclusions, finding that 35 percent of DTC advertisements did not present a fair balance of risk and benefit information (Roth, 1996). An ongoing study that monitored the behavior of medical representatives with a pharmaceutical company found that adverse effects, contraindications, and drug interactions were not mentioned in 76 percent of visits (Bercel et al., 1997). Random telephone survey

Health care practitioners, with substantial advanced education and training, can at least hope to evaluate pharmaceutical advertisers’ claims and arrive at a considered evaluation of a drug’s risks and benefits (Hollon, 1999). But, clinicians do not believe that consumers, with little or no clinical and pharmacological background, could possibly understand and properly evaluate DTC advertisements (Cohen, 1988). In fact, consumers’ misperceptions about drug advertisements have been documented (Morris et al., 1986). Likewise, clinicians believe that many consumers have incorrect beliefs about how DTC advertising is regulated. In a random digit dialing telephone survey of 329 adults in Sacramento County, California, approximately 50 percent of respondents thought that governmental approval was required before a DTC advertisement could be shown, and 43 percent thought that only ‘‘completely safe’’ prescription pharmaceuticals could be advertised directly to the general public (Bell et al., 1999). Both statements are, of course, untrue. Perhaps most important to physicians is their belief that DTC advertising will lead to strain in the doctor-patient relationship (Bradley and Zito, 1997; Cohen, 1988; Lipsky and Taylor, 1997; Wilkes et al., 2000). It is, therefore, not surprising that physicians would feel negatively toward DTC advertising.

Promotional tool

Given developments in the industry, there seems to be little practical value in continuing to ask doctors whether they believe that DTC advertising should be decreased or stopped (see, for example, Sherr and Hoffman, 1997), or to exhort physicians to this viewpoint (Cohen, 1988; Hollon, 1999). The reality is that this promotional tool has long since become a permanent fixture in the US health care marketplace, and there has even been recent speculation that the European Union may be moving toward relaxing its long-standing ban on DTC pharmaceutical advertising (Advertising Age, 2001; Gopal, 2002). Even staunch critics such as the American Medical Association have admitted that DTC advertising of prescription pharmaceuticals is here to stay, and that the debate should move from pure opposition on philosophical grounds to how more responsible DTC promotion of prescription drugs can be achieved (Medical Marketing and Media, 1999; t’Hoen, 1998). Thus, it seems reasonable to believe that the time has come to consider shifting the research focus from mere examination of physicians’ attitudes toward DTC advertisements to more actionable dimensions of the debate (Handlin and Paul, 2002; Wilkes et al., 2000). Specifically, there is a need to explore further physicians’ opinions of the shortcomings of DTC

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advertisements. Previous evidence suggests that physicians are concerned both about the nature of the information that is included in most ads, and about the absence of information that they consider important (Roth, 1996). The present study has two goals: first, to explore whether physician opposition has abated as DTC advertising has become increasingly commonplace, and second, to measure the extent of physician concern about exaggerated benefit claims and inadequate risk/contraindication information.

Explosion in DTC broadcast advertising

Development of hypotheses In 1997, a revision in Food and Drug Administration rules permitted television commercials to identify a prescription drug together with its intended use. This critical regulatory change (previously, prescription pharmaceuticals could be named on TV but not linked to a specific disease or condition) led to an explosion in DTC broadcast advertising. Because DTC messages are now ubiquitous in both print and broadcast media, the concerns of physicians are likely to have intensified beyond earlier levels – when advertisements for popular drugs like Claritin or Celebrex were limited to the occasional magazine. Thus: H1. The majority of primary care physicians continue to express opposition to DTC pharmaceutical advertising. Some physicians have long worried that DTC advertising overstates the likely efficacy of prescription products. ‘‘Everything is being presented to them [consumers] as a wonder drug,’’ complained the past president of the New York Allergy Society in a 1998 interview (Braus, 1998). For example, of physicians who declared in a 1997 survey that they wished to see DTC advertisements reduced or stopped, 20 percent believed that the advertisements create unreasonable expectations for product performance (Sherr and Hoffman, 1997). In numerous studies, physicians have identified inadequate risk information as their leading criticism of DTC advertising (for examples, see Sherr and Hoffman, 1997; Pinto et al., 1998). We hypothesize that this criticism has intensified with the growing number and aggressiveness of DTC advertisements: H2. A majority of primary care physicians feel that DTC advertising conveys inadequate information about the risks/contraindications associated with prescription medications.

PCPs continue to have concerns

Given the sheer number of bold new DTC product claims now available to consumers, we suspect that PCPs continue to have concerns about the specific kinds of information communicated in DTC advertisements and the effects these kinds of information have on patients. Thus: H2a. A majority of primary care physicians feel that DTC advertising overstates the clinical efficacy of advertised pharmaceuticals. H2b. The proportion of primary care physicians who believed that direct-toconsumer pharmaceutical advertising creates unreasonable consumer expectations has increased since Sherr and Hoffman (1997). Physicians are trained in multiple treatment modalities, including the broad categories of medicine and surgery. Even if only ‘‘medical’’ treatments are considered, treatment options may include such non-pharmacological choices as weight loss, exercise, behavior modification, etc., in conjunction with various pharmacological choices. However, DTC advertisements virtually never offer information about treatment approaches other than the drug being advertised. Thus:

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H3a. A majority of primary care physicians will be unaware of research findings demonstrating a positive influence of DTC advertising on consumers’ health-related behaviors. H3b. Primary care physicians believe that DTC advertising oversells drug therapies when non-pharmaceutical alternatives exist. Increased volume of patient visits

It has been suggested that DTC advertising does influence patients to seek medical care (Appelby, 2001; Holmer, 1999; Mason and Rubin, 1999). Despite PCPs’ concerns about the appropriateness of the DTC advertisements themselves, we hypothesize that PCPs will be aware of the increased volume of patient visits resulting from DTC advertisements. Thus: H4. Primary care physicians believe that DTC advertising motivates patients to seek medical care. Whatever the reason(s) for their concerns about DTC advertising, physicians have demonstrated their opposition to this commercial approach to pharmaceutical companies’ communications with potential patients (Bradley and Zito, 1997; Cohen, 1988; Lipsky and Taylor, 1997; t’Hoen, 1998). Based on this demonstrated opposition, it would not be unreasonable that physicians might be frustrated by DTC advertisements. Thus: H5. A majority of primary care physicians describe themselves as ‘‘frustrated’’ with DTC advertising.

Extra time with patients

One cause of this potential frustration could be that physicians might need to explain that the drug in question would be inappropriate for the patient’s condition, or that the patient has some physical or mental condition that contraindicates the use of the drug suggested. Regardless of the particular reason, physicians may well find that they have to spend extra time with patients who request a particular drug about which they have seen a DTC advertisement. Thus: H5a. Primary care physicians spend a significantly longer time with patients who ask about a specific DTC advertised drug than they do if no DTC drug is mentioned by the patient. However, despite any increase in the sheer volume of office visits produced by DTC advertising, physicians’ perceptions are that DTC advertisements are poor educational vehicles (Sherr and Hoffman, 1997). When Consumer Reports convened an independent panel of physicians to assess the accuracy of an array of pharmaceutical advertisements in 1996, it concluded that fewer than half of the advertisements adequately communicated the risks associated with the advertised drugs (Consumer Reports, 1996). Thus: H5b. Primary care physicians believe that patients who ask about DTC advertised pharmaceutical products generally know little about the product prior to their office visit. H5c. Primary care physicians do not believe that DTC television advertising provides sufficient motivation for consumers to seek out more information about the drug from other sources.

Interference with doctor-patient relationship

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Physicians have traditionally believed in the sanctity of the doctor-patient relationship, and have fought vigorously against anything perceived to interfere with this relationship. It would seem quite reasonable that primary care physicians, being the ‘‘front line’’ of direct patient care, would object to increased DTC advertising on the grounds that it interfered with this doctorpatient relationship. Thus: JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

H6. The percentage of primary care physicians who believe that DTC advertising contributes negatively to the doctor-patient relationship has increased.

Survey developed

Methodology In order to test the above hypotheses, a survey was developed consisting of attitudinal statements that measured physicians’ opinions about DTC advertising and its impact on the doctor-patient relationship. There were also several questions about patients who inquire about advertised pharmaceuticals and about physician reaction to patient requests for advertised pharmaceuticals. Several demographic questions were also used to provide physician classification data. The items in the questionnaire were derived from previous research, and all attitudinal measures employed a fivepoint Likert scale (1 = strongly disagree; 5 = strongly agree). The sample selected for the study consisted of physicians practicing either internal medicine or family/general practice. A national mailing list of these physicians was purchased, and 500 respondents were chosen at random from the list. A total of 125 physicians returned the survey, resulting in a response rate of 25 percent. Results and findings Demographic profile of the respondents The majority of the physicians responding to the survey, 57 percent, said their primary area of practice was family or general practice. Of the remainder, 42 percent practiced internal medicine and 1 percent were employed in some other specialty. The overwhelming majority of respondents, 92 percent, stated they were board certified in their primary area of practice. The physicians surveyed have practiced medicine for an average of 18 years (sd = 11.0). On average, the physicians responding to this study saw an average of 354 patients in a typical month (sd = 157.5). This varied widely, though, with a low of 25 patients and a high of 900 patients.

Identify status and income

The mean age for the physicians surveyed was 48.3 years of age (sd = 10.9). Of those responding, 23 percent were younger than 40, 37 percent were between 40 and 49, 25 percent were between 50 and 59, while the remaining 15 percent were 60 years of age or older. When asked to identify their marital status, a large majority, 86 percent, said they were married. Of the remainder, 7 percent were single, 5 percent were divorced or separated and 2 percent were widowed. Of those responding, the majority, 60 percent, indicated their total household income before tax was $125,000 or more (26 percent with an income between $125,000 to $149,999 and 34 percent with an income $150,000 or higher). An additional 24 percent said their income was between $100,000 and $124,999. Of the remainder, 14 percent stated their annual income as between $75,000 and $99,999, while only 2 percent reported an income of less than $75,000 per year. Tests of hypotheses Previous research (see Sherr and Hoffman, 1997; Lowes, 1999) showed that the proportion of primary care physicians opposed to DTC advertising ranged from a low of about 55 percent to as high as 80 percent (among family practice specialists). In this study, 62 percent of respondents agreed or strongly agreed with the statement, ‘‘Advertising prescription drugs to the general public is not a good idea.’’ While this is significantly below the 80 percent ceiling (2 = 26.45, p = 0.000), it represents a solid majority.

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Moreover, it is a composite measure of the views of different types of primary care specialists, not just those in family practice. Thus, H1 is clearly supported: the majority of primary care physicians surveyed continue to express opposition to DTC pharmaceutical advertising. Inadequacy of information about possible contraindications

There was a strong consensus among physicians in this study that advertisements for prescription drugs do not adequately inform patients about possible contraindications: 82 percent of respondents either agreed or strongly agreed that this was the case. This is important because virtually all of the physicians surveyed, 92 percent, do not think that patients understand all of the risk-related information contained in prescription drug advertisements. Along the same lines, 70 percent of respondents believed that prescription drug advertisements do not present a fair balance of risks and benefits. Additionally, 59 percent of the respondents do not think that advertisements about prescription drugs specify how the drug should be used. These findings provide clear support for H2: a majority of primary care physicians feel that DTC advertising conveys inadequate information about the risks/contraindications associated with prescription medications. However, it is interesting to note that nearly half (49 percent) of respondents apparently remain somewhat open-minded. This substantial minority asserted that they would be receptive to DTC advertising if the pharmaceutical companies provided more information about the risks associated with their products.

Concern about exaggerated claims

Almost three-quarters of the physicians surveyed in this study (74 percent) believed that advertisements for prescription drugs overstate the efficacy of such drugs. This offers strong support for H2a: a majority of primary care physicians feel that DTC advertising overstates the clinical efficacy of advertised pharmaceuticals. It therefore appears that the continual increase in advertising for prescription drugs has caused an increased concern about exaggerated claims of benefits. Additionally, an earlier study by Sherr and Hoffman (1997) found that 20 percent of physicians believed that advertisements create unreasonable expectations for product performance. A significantly larger percentage of physicians in this study (73 percent) believed that direct-to-consumer advertising creates unreasonable consumer expectations about how well a product can perform (2 = 231.2, p = 0.000). Thus, H2b, which posited that the proportion of primary care physicians who believed that DTC pharmaceutical advertising creates unreasonable consumer expectations has increased since Sherr and Hoffman (1997) is accepted.

‘‘Magic bullets’’

Concerns about exaggeration of benefits clearly reverberated in other ways. A total of 73 percent of respondents felt that DTC advertisements lead patients to believe that advertised drugs are ‘‘magic bullets.’’ Over 72 percent agreed or strongly agreed that DTC advertisements overstate the assurances of efficacy. Of the respondents, 86 percent agreed that their patients believed the claims made by the pharmaceutical companies in their drug advertisements. Not surprisingly, almost 65 percent of physicians in this study believed that assurances of clinical efficacy in DTC advertisements should be decreased. The majority of respondents, 88 percent, said they were either unaware of or unsure about research findings that show the positive influence of direct-toconsumer advertising on consumers’ health-related behavior. Only 12 percent said they were aware of such research. Thus, H3a is supported: a majority of primary care physicians surveyed were unaware of research findings demonstrating a positive influence of DTC advertising on consumers’ health-related behaviors.

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Roth (1996) hypothesized that direct-to-consumer advertising may oversell drug therapies when non-pharmacological (and presumably cheaper) alternatives exist (H3b in this study). A total of 79 percent of the primary care physicians surveyed agreed with the statement ‘‘advertisements for prescription drugs typically do not mention lifestyle changes or other non-pharmacological interventions.’’ Thus, H3b is supported: the primary care physicians surveyed believe that DTC advertising oversells drug therapies when non-pharmaceutical alternatives exist. Results were mixed

H4 examined the perceived propensity of patients to seek medical care as a result of DTC advertised drugs, specifically suggesting that direct-toconsumer advertising motivates patients to seek office visits. Although the largest percentage of the respondents in this study, 45 percent, believed this to be the case, the results were somewhat mixed. While 25 percent disagreed that direct-to-consumer advertising encouraged people to seek medical care, an additional 30 percent were unable to make this determination. Thus, H4 is only partially supported. One-half of the primary care physicians surveyed in this study (50 percent) stated that direct-to-consumer advertising has been a source of frustration. Only 19 percent disagreed with this statement. Additionally, 63 percent of the physicians responding to this study reported feeling pressured to prescribe drugs they have seen advertised. These results provide support for H5: a majority of primary care physicians surveyed describe themselves as ‘‘frustrated’’ with DTC advertising.

Prescription drugs may be inappropriate

Of the respondents, 59 percent noted that direct-to-consumer advertising has caused them to spend a great deal of time explaining why an advertised prescription drug may be inappropriate for a patient’s specific situation. The physicians were asked to identify the typical visit length (in minutes) of patients who did and did not inquire about advertised prescription drugs. On average, these physicians stated that they spent 14.6 minutes with patients who did not inquire about an advertised prescription drug and 16.4 minutes with patients who did ask about a drug they learned about via DTC advertising. This difference was statistically significant (t = –4.685; p = 0.000). This provides strong support for H5a that primary care physicians feel they spend more time with patients who already have a particular drug in mind prior to presenting themselves for an office visit. The primary care physicians in this study did believe strongly that patients who ask about advertised prescription drugs generally know little about the product prior to their office visit (84 percent either agreed or strongly agreed). This provides support for H5b.

Direct-to-consumer TV

H5c posited that physicians did not believe that direct-to-consumer television advertising provided sufficient motivation for consumers to seek more information about the drug from other sources. Results from this study were mixed. While 35 percent of those responding thought that their patients would seek out additional information, 28 percent did not believe this to be the case. The largest percentage of responding physicians, 37 percent, were unsure as to whether or not a television advertisement would prompt a consumer to seek more information. Thus, H5c cannot be accepted. Although physicians have become more accustomed to DTC advertising, this does not mean that they feel it has had a positive impact on the doctor-patient relationship. In an earlier study (Medical Marketing and Media, 1998), 50 percent of physicians did not think that direct-to-consumer advertising made a positive contribution to the doctor-patient relationship. Here, it is

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posited that an increasing number of physicians believe that advertisements for prescription drugs contribute negatively to the doctor-patient relationship (H6). Although 52 percent the primary care physicians responding did not think that direct-to-consumer advertising made a positive contribution to the doctor-patient relationship, this percentage was not statistically different from the 50 percent obtained previously (2 = 0.131, p = 0.717). Thus, H6 is rejected: these results do not demonstrate that a higher percentage of PCPs surveyed believe that DTC prescription advertising has a negative effect on the doctor-patient relationship.

DTC advertising continues to be quite negative

Conclusions Primary care physicians’ attitudes and evaluations of DTC advertising of prescription pharmaceuticals continue to be quite negative. These results show PCPs to continue to be opposed to DTC advertising, with a clear majority feeling that such advertisements do not adequately inform patients about possible contraindications, do not represent a fair balance of risks and benefits, and continue to create unreasonable expectations on the part of consumers. PCPs are unaware of research findings demonstrating a positive influence of DTC advertising on consumers’ health-related behaviors and believe that DTC advertising oversells drug therapies when non-pharmaceutical alternatives exist. While 45 percent of PCPs agreed that DTC advertising does motivate patients to seek office visits, these visits are frustrating for the physicians, at least partially because these patients require extra time. PCPs believe that patients requesting particular DTC advertised drugs know little about the drug requested and do not have sufficient motivation to seek more information about the drug from other sources. Based upon these above responses, there should be little surprise that many PCPs continue to think that direct-to-consumer advertising does not make a positive contribution to the doctor-patient relationship. To the extent that PCPs are an important constituency for pharmaceutical companies engaging in DTC advertising, clearly a problem exists and is growing: these physicians appear to be increasingly alienated by existing DTC advertisements and their sequelae. Managerial implications As competition in the pharmaceutical marketplace continues to intensify, the gatekeeper role of PCPs will become increasingly important (Holmer, 1999; Pizor, 1998). Thus it is clearly in the pharmaceutical industry’s interest to respond to physicians’ multi-faceted, serious and enduring concerns about DTC advertising. While the data indicate that primary care physician attitudes currently remain strongly negative toward DTC prescription pharmaceutical advertising, some respondents did signal at least a degree of openness toward DTC advertising that might be redesigned to do a better job of communicating risks and contraindications to patients. Future research is needed to test alternative means of presenting and explaining such information.

Advertising copy largely seen as hype

The pharmaceutical industry must, however, acknowledge that its current DTC prescription pharmaceutical messages are widely perceived by physicians as promising ‘‘magic bullets.’’ An important area for research is the question of how to continue to convey hope to patients – without relying on advertising copy that comes across largely as hype to doctors. References Advertising Age (2001), ‘‘EU Pharmaceutical Reform Could Lead to DTC Ads’’, Advertising Age, July 30, p. 33.

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Alperstein, N.M. and Peyrot, M. (1993), ‘‘Consumer awareness of prescription drug advertising’’, Journal of Advertising Research, Vol. 33 No. 4, pp. 50-6. Appelby, J. (2001), ‘‘Prescriptions increase as drugmakers spend more on ads’’, USA Today, 21 February, p. 6B. Bell, R.A., Kravitz, R.L. and Wilkes, M.S. (1999), ‘‘Direct-to-consumer prescription drug advertising and the public’’, Journal of General Internal Medicine, Vol. 14 No. 11, pp. 651-7. Bercel, B., Bardelay, D. and t’Hoen, E. (1997), ‘‘A French physician’s network monitoring medical representatives’’, La Revue Prescribe, Paris. Bittar, C. (2001), ‘‘The message and the medium’’, Brandweek, Vol. 42 No. 28, pp. 33-8. Bradley, L.R. and Zito, J.M. (1997), ‘‘Direct-to-consumer drug advertising’’, Medical Care, Vol. 35 No. 1, pp. 86-92. Braus, P. (1998), ‘‘Selling drugs’’, American Demographics, Vol. 20 No. 1, pp. 26-9. Cohen, E.P. (1988), ‘‘Direct-to-the-public advertisements of prescription drugs’’, New England Journal of Medicine, Vol. 318 No. 6, pp. 373-6. Consumer Reports (1996), ‘‘Drug advertising: is this good medicine?’’, Consumer Reports, Vol. 61 No. 6, p. 62. Dickinson, J.G. (2001), ‘‘FDA: study suggests more DTC negative info; Relenza promised too much’’, Medical Marketing and Media, Vol. 35 No. 3, pp. 36, 38. (The) Economist (1998), ‘‘Go on, it’s good for you’’, The Economist, No. 348, 8 August, pp. 51-2. Everett, S.E. (1991), ‘‘Lay audience response to prescription drug advertising’’, Journal of Advertising Research, Vol. 31 No. 2, pp. 43-9. Fetto, J. (2002), ‘‘Drugged out’’, American Demographics, Vol. 24 No. 5, p. 11. Goetzl, D. (2000), ‘‘TVB study: DTC disclosures lend credibility to drug ads’’, Advertising Age, June 5, p. 6. Gopal, K. (2002), ‘‘Consumer communication in Europe stalls: the European commission wants to open the door to DTC, but Dutch officials plan to oppose changes’’, Pharmaceutical Executive, Vol. 22 No. 2, pp. 38-9. Handlin, A. and Paul III, D.P. (2002), ‘‘DTC advertising of Rx products: a review of the literature with suggestions for further research’’, in Thomas, J.L., Kellerman, B.J. and Tutor, R.K. (Eds), Proceedings of the Annual Meeting of the Association of Collegiate Marketing Educators, pp. 73-81. Harris, G. (2000), ‘‘Drug firms, stymied in the lab, become marketing machines’’, Wall Street Journal, 6 July, pp. A1, A12. Hollon, M.F. (1999), ‘‘Direct-to-consumer marketing of prescription drugs: creating consumer demand’’, Journal of the American Medical Association, Vol. 281 No. 4, pp. 382-4. Holmer, A.F. (1999), ‘‘Direct-to-consumer prescription drug advertising builds bridges between patients and physicians’’, Journal of the American Medical Association, Vol. 281 No. 4, pp. 380-2. Kessler, D.A. and Pines, W.L. (1990), ‘‘The Federal Regulation of prescription drug advertising and promotion’’, Journal of the American Medical Association, Vol. 264 No. 18, pp. 2409-15. Levy, S. (1999), ‘‘What do consumers really think about DTC ads?’’, Drug Topics, Vol. 146 No. 3, p. 23. Lexchin, J. (1997), ‘‘What information do physicians receive from pharmaceutical representatives?’’, Canadian Family Physician, Vol. 43 No. 4, pp. 941-5. Lipsky, M.S. and Taylor, C.A. (1997), ‘‘The opinions and experiences of family physicians regarding direct-to-consumer advertising’’, Journal of Family Practice, Vol. 45 No. 6, pp. 495-9. Lowes, R. (1999), ‘‘Doc, I saw this great new drug on TV,’’ Medical Economics, Vol. 76, 26 April, pp. 71-6. Marketing Health Services (2002) ‘‘Drug spending on the rise’’, Marketing Health Services, Vol. 22 No. 2, p. 10. Mason, A. and Rubin, P.H. (1999), ‘‘Matching prescription drugs and consumers’’, New England Journal of Medicine, Vol. 313 No. 8, pp. 513-5. Medical Marketing and Media (1998), ‘‘Exam time for DTC advertising, doctors ‘no’, consumers ‘yes’’’, Medical Marketing and Media, Vol. 33 No. 11, pp. 24-6. JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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Medical Marketing and Media (1999), ‘‘AMA accepts the inevitable: DTC ads are here to stay’’, Medical Marketing and Media, Vol. 34 No. 8, p. 28. Morris, L.A., Brinberg, D., Klimberg, R., Rivera, C. and Millstein, L.G. (1986), ‘‘Miscomprehension rates for prescription drug advertisements’’, Current Issues and Research in Advertising, Vol. 9 No. 1/2, pp. 93-113. National Institute for Health Care Management and Education Foundation (2001), Prescription Drugs and Mass Media Advertising, 2000, available at: www.nihcm.org (accessed 27 November 2001). Petroshius, S, Titus, P. and Hatch, K. (1995), ‘‘Physician attitudes toward pharmaceutical drug advertising’’, Journal of Advertising Research, Vol. 31 No. 2, pp. 43-9. Pinto, M.B., Pinto, J. and Barber, J. (1998), ‘‘The impact of pharmaceutical direct advertising’’, Health Marketing Quarterly, Vol. 15 No. 4, pp. 89-101. Pizor, T.C. (1998), ‘‘A medical published reminds us: don’t forget the gatekeepers’’, available at: www.amponline.org/MJA/Gatekeepers.html (accessed May 2002). Roth, M. (1996), ‘‘Patterns in direct-to-consumer prescription drug print advertising and their public policy implications’’, Journal of Public Policy and Marketing, Vol. 15, Spring, pp. 63-75. Schommer, J.C., Doucette, W.R. and Mehta, B.H. (1998), ‘‘Rote learning after exposure to a direct-to-consumer television advertisement for a prescription drug’’, Clinical Therapeutics, Vol. 20 No. 3, pp. 617-32. Sherr, M.K. and Hoffman, D.C. (1997), ‘‘Physicians – gatekeepers to DTC success’’, Pharmaceutical Executive, October, pp. 56-66. Smith, D. (1998), ‘‘Can DTC programs improve patient compliance?’’, DTC Times, September, pp. 14, 17. t’Hoen, E. (1998), ‘‘Direct-to-consumer advertising: for better profits or for better health?’’, American Journal of Health-System Pharmacy, Vol. 55, pp. 594-7. Wilkes, M.S., Bell, R.A. and Kravitz, R.L. (2000), ‘‘Direct-to-consumer prescription drug advertising: trends, impact, and implications’’, Health Affairs, Vol. 19 No. 2, pp. 110-28. Wilkes, M.S., Doblin, B.H. and Shapiro, M.F. (1992), ‘‘Pharmaceutical advertisements in leading medical journals: experts’ assessments’’, Annals of Internal Medicine, Vol. 116 No. 1, pp. 912-9. Williams, J. and Hensel, P. (1995), ‘‘Direct to consumer advertising of prescription drugs’’, Journal of Health Care Marketing, Vol. 15 No. 1, pp. 35-41.

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An executive summary for managers and executive readers can be found at the end of this issue

Patient/enrollee satisfaction with healthcare and health plan Karin Braunsberger Assistant Professor of Marketing, University of South Florida, St Petersburg, Florida, USA

Roger H. Gates President, DSS Research, Fort Worth, Texas, USA

Keywords Health care, Marketing, Customer satisfaction Abstract The findings of the present study show that healthier patients, older patients, males, those with a lower level of education, those who perceive system performance to be high and those with lower levels of system usage are more satisfied with both their healthcare and health plan than their opposite counterparts. Regarding the incremental effects of these variables, the most striking finding is the strong, pivotal role of physicians in influencing patient satisfaction with healthcare. In regard to satisfaction with health plan, the extent of the problems that members have had with their health plan has by far the largest statistical influence on their satisfaction with that plan. The effects of other independent variables including the three demographic variables, self-stated health status, number of visits to doctor’s office or clinic, and issues related to access, though significant, show relatively small statistical influences on overall satisfaction with healthcare and health plan.

Importance of service sector

Introduction In the USA, the service sector is of undeniable importance. It accounts for 76 percent of the gross domestic product and approximately 79 percent of employment (Zeithaml and Bitner, 2000). One of the largest and fastest growing industries in the service sector is the healthcare industry. To illustrate, healthcare expenditures in 1991 totaled $671 billion (Reynolds, 1991) and rose to $1.3 trillion in 2000 (Wechsler, 2002). Even though this increase appears to be impressive, healthcare expenditures as a percentage of the gross domestic product (GDP) have been fairly stable at about 13 percent from 1992 to 2000 (Carroll, 2002; Wechsler, 2002). It has been projected, however, that healthcare spending will grow faster than GDP during the coming decades (Carroll, 2002). That is, expenditures have been projected to reach a total of $1.5 trillion by 2002 (Shinkman, 1997), $2.6 trillion or 16 percent of GDP by 2010 (Healthcare Financial Management, 2001) and $2.8 trillion or 17 percent of GDP by 2011 (Wechsler, 2002). This trend has, in part, been attributed to consumers’ preference for better healthcare (Pham, 1998) and less restrictive forms of managed care (Wechsler, 2002). To gain a competitive edge and thus increase profitability, providers of healthcare and health plans should therefore be interested in investigating what constitutes ‘‘better healthcare’’ from a consumer’s point of view, what factors are important in determining patient/enrollee satisfaction with healthcare and health plan, and which of these factors can be managed and marketed. Further, considering the tremendous growth and importance of the healthcare industry in the US economy, these questions and relationships should be of equal importance to marketing scholars interested in consumer behavior. The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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Combining predictor variables

To that end, the main purpose of the present study is to investigate the construct patient/enrollee satisfaction comprehensively. That is, unlike previous studies that usually focused on either patient satisfaction or enrollee satisfaction, we are examining both. Further, we are combining predictor variables that have been previously identified by a number of different researchers and, thus, present a study that is more comprehensive than prior research in that it includes more independent variables than any preceding single study. Also, given the recent findings on the effects of self-perceived health status on satisfaction with care and plan (Gearon, 2000; Hall et al., 1998), this variable will receive special consideration. In addition, the effects of specific sociodemographic variables (e.g. age, educational level, gender) and a number of variables related to system performance (e.g. reported access to care, reported problem with care delivery) and system usage will be examined to shed light on the incremental effects of these variables. Here it is of importance to delineate between variables that are under the control of the provider (e.g. perceived system performance) and those that are not (e.g. age, self-perceived health status). That is, if it is found that the incremental effects of the former variables are larger than those of the latter ones, then an understanding of these relationships will aid providers of care and health plans to develop strategies that lead to more effective programs and thus to allocate resources more efficiently (Holcomb et al., 1998). If, however, the incremental effects of variables that are not under the control of the provider are found to be larger, then the situation becomes more problematic and it becomes questionable to what extent, if at all, marketers and managers of healthcare can step in and modify their offerings accordingly. Patient/enrollee satisfaction: definitions, measurements and predictors Traditionally, quality of healthcare has been defined from the provider’s point of view (Berwick, 1997; Kramer, 1997) because many healthcare professionals felt that patients lack the knowledge to evaluate care intelligently (Berwick, 1997; Decker, 1999). More recently, focus has shifted to patient perceptions of care delivery. It has been argued that this change is of critical importance to healthcare providers in a rapidly changing (Davis et al., 1995) and increasingly competitive market (Health Industry Today, 1999; Para, 1997). It has further been suggested that healthcare providers are dealing with increasingly sophisticated patients/customers who desire more control and are demanding greater focus on their needs and wants (Decker, 1999). Thus, it has finally been recognized that patients are consumers and that effective patient relations are a key to survival in today’s turbulent healthcare market (Para, 1997).

Healthier patients more satisfied

Quality of care from the consumer’s point of view is generally defined and measured as patient/customer satisfaction (Beatty et al., 1998; Dansky and Miles, 1997). Reasonably well-established predictors of patient satisfaction include patient sociodemographic characteristics such as age, education (Hall and Dornan, 1990) and gender (Cohen, 1996), and a variety of external factors. The latter include system usage (Langley and Cook, 2000) and perceived system performance (Zapka et al., 1995). Recent research has further established a relationship between patient health status and satisfaction. That is, it has been argued that healthier patients are generally more satisfied with the quality of care they receive (Cohen, 1996; Hall et al., 1998). Due to the movement to managed care and the accompanying discussions of its negative effects on consumer choices and quality of care (Reuters, 2000; Schmittdiel et al., 1997), managed care organizations have become interested in a different aspect of customer satisfaction, namely satisfaction

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with health plan (Druss et al., 1999). A variety of factors have been shown to affect customer satisfaction with their health plan, including system performance (Druss et al., 1999; Zapka et al., 1995) and system usage (Druss et al., 2000). It has also been suggested that patient health status has an effect on satisfaction with health plan, with healthier patients being more satisfied than their less healthy counterparts (Druss et al., 1999; Gearon, 2000; Ullman et al., 1997). However, some of the research focusing on this relationship has reported less conclusive outcomes (Druss et al., 2000). The relationship between health status and satisfaction with healthcare A number of studies have investigated the relationship between health status and satisfaction with healthcare. In general, it has been found that healthier patients, either emotionally or physically, tend to be more satisfied with their healthcare (Cohen, 1996; Druss et al., 1999; Hall et. al, 1998, 1996, 1993a, 1990; Holcomb et al., 1998; Schmittdiel et al., 1997). Agreement not entirely agreed

It is interesting to note that the direction of causality of this phenomenon has not been entirely agreed upon. Although some argue that satisfaction causes better health (DiMatteo and DiNicola, 1982; Falvo et al., 1980; Ley, 1982; Parkin, 1976; Pascoe, 1983), others have found that better health causes satisfaction (Hall et al., 1998, 1993b). The former conclusion is based on the observation that satisfied patients are better able to recall physicians’ advice, follow medical regimens more strictly and change doctors less often. In other words, patients who are more satisfied are more likely to participate more actively and effectively in the medical care process and behave in ways that promote better health (Hall et al., 1993b). It has further been suggested that satisfaction might consist of a more global dimension, in addition to domainspecific dimensions (Hall et al., 1990). That is, positive correlations have been found between higher satisfaction with healthcare and a variety of dimensions of life satisfaction such as leisure, marriage, consumer issues and money (Roberts et al., 1983). Consequently, Hall et al. (1990, p. 266) state that it might be conceivable that ‘‘dissatisfied patients are simply dissatisfied consumers.’’

Physicians less satisfied after visits with sicker patients

The view that poor health leads to dissatisfaction, on the other hand, has been tested by Hall et al. (1993b). Simultaneous equation modeling was used to detect the direction of causation. The findings of this longitudinal study strongly suggest that health status may affect satisfaction with healthcare over time, while there is no evidence that satisfaction determines later health status. These results are supported by a number of subsequent studies which have found that patient health status appears to impact physician behavior and communicational style (Hall et al., 1998, 1996, 1993a). First, it seems that physicians appear to like patients who are in better health more than those who are less healthy. Further, patients who feel that they are liked by their physicians report higher levels of satisfaction with care (Hall et al., 1993a). Second, it has been found that physicians tend to be less satisfied after visits with sicker patients. Considering that these same physicians may also convey greater negativity to patients who are physically or mentally less healthy, these low satisfaction ratings on the part of the physician and patient are not surprising. This effect is further enhanced by the observation that sicker patients tend to display more negative communication cues during physician visits (Hall et al., 1996). Third, a later study by Hall et al. (1998) appears to validate previous findings by establishing that poor health produces dissatisfaction directly and indirectly. The indirect relationship is mediated by the effect of physician behavior, which has been shown to be more negative when dealing with those who are less healthy.

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Differences between UK and US health systems

It should be noted that most of the previous research has focused on specific patient subgroups rather than the population at large. Hall et al. (1990) focused on older patients in an HMO setting; Hall et al. (1993b) only included the frailest patients; Hall et al.’s (1993a) sample consisted of patients 70 years of age or older; Foley et al. (1995) focused on HIV patients; Zapka et al.’s (1995) sample was drawn from HMO-enrollees and consisted mainly of patients with chronic diseases and those receiving referrals to specialists; Holcomb et al. (1998) investigated psychiatric patients; and Frost et al. (1999) studied women with breast cancer. Although these researchers had reasons for restricting their sampling frames, the generalizability of these results across more general populations is questionable. Though some studies have utilized more general populations, serious questions as to their external validity remain. Cohen’s (1996) study, for example, was carried out in the Lothian Region in southeast Scotland. It is conceivable that differences between the British and the US health systems as well as cross-cultural differences in patient perceptions might prevent the generalization of the results to the US population. Further, other studies drew their samples from fairly narrow geographic areas (Schmittdiel et al., 1997; Hall et al., 1998), thus limiting external validity as well. And finally, one study reporting conflicting results (Newsome et al., 1999) suffers from problems with the data analyses techniques used. Based on the above discussion, the present study investigates whether the relationship between patient health status and satisfaction with care, described above, can be replicated with a sample drawn from a general crosssection of the US population. Hence, the first hypothesis states: H1. Healthier patients, as compared to the less healthy, are more satisfied with the healthcare they receive. The relationship between health status and satisfaction with health plan A small number of recent studies have investigated the relationship between health status and satisfaction with health plan. Although some have found that enrollees in better health tend to be more satisfied with their health plan than those who are less healthy (Allen and Rogers, 1997; Langley and Cook, 2000; Schlesinger et al., 1999; Ullman et al., 1997), others have found this relationship to be mediated by type of health plan (Druss et al., 2002).

Decline in satisfaction

Allen and Rogers’ longitudinal study (1997), for example, shows an overall decline in satisfaction with health plan and willingness to recommend the plan for both the healthy and less healthy for the period from 1993-1995. These results, however, differ depending on type of health plan and across drivers of satisfaction (e.g. thoroughness of treatment, self-assessed outcomes, range of coverage and employee premium). Comparing the satisfaction ratings for the healthy and the less healthy, the former appear to be more satisfied than the latter by 4-5 percent. Likewise, Schlesinger et al. (1999) show that 8.5 percent to 22 percent of healthy enrollees tend to be dissatisfied with their plan, whereas 11.8 percent to 23.5 percent of functionally impaired enrollees report dissatisfaction (varies by type of health plan). Finally, Ullman et al. (1997) and Langley and Cook (2000) focus on managed care enrollees only. Both studies show that healthier HMO-enrollees are more satisfied with their plan than less healthy enrollees. Druss et al. (2000), however, show that poor health tends to predict dissatisfaction for managed care enrollees but not for fee-for-service enrollees. Considering that this area of research is still relatively new and some of the evidence for the proposed relationship between health status and

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plan satisfaction is not entirely clear, it seems worthwhile to replicate prior studies. Further, considering that health plan dissatisfaction has been associated with intended disenrollment and unwillingness to recommend the plan (Druss et al., 1999; Schlesinger et al., 1999), additional research is needed to aid decision makers in the design of more effective programs. Hence, the second hypothesis states: H2. Healthier enrollees, as compared to the less healthy, are more satisfied with their health plan.

Older patients more satisfied

Younger enrollees more likely to disenroll

The effects of age, gender, educational level and systems characteristics on satisfaction with healthcare and health plan The effect of age on satisfaction with healthcare and health plan Hall and Dornan’s (1990) meta-analysis shows that older patients tend to be more satisfied with the care they receive than younger patients. These results are supported by more recent work (Cohen, 1996; Zapka et al., 1995). It has been suggested that this effect might be due to a number of factors (Cohen, 1996): Older patients: .

remember how poor healthcare services used to be in the past, therefore have lower expectations of the current system and thus are more satisfied patients;

.

are generally treated with more respect than younger patients and are thus more satisfied with the quality of care they receive; and

.

might be more accepting and more reluctant to complain than younger patients.

Further, it has also been shown that younger enrollees tend to be less satisfied with their health plan than their older counterparts (for a discussion see Schlesinger et al., 1999). In addition, it has been found that younger enrollees are more likely to disenroll from their health plan (Schlesinger et al., 1999). Even though previous research does not attempt to explain these phenomena, it appears reasonable to suggest that older enrollees are more satisfied with their health plan for the same reasons they are more satisfied with their healthcare (see above). Thus, the next hypotheses state: H3. Older patients, as compared to younger patients, are more satisfied with the healthcare they receive. H4. Older enrollees, as compared to younger enrollees, are more satisfied with their health plan.

Female patients less satisfied with their care

The effect of gender on satisfaction with healthcare and health plan Even though some studies show that there is no conclusive difference in satisfaction ratings given by male and female patients (for a discussion see Hall and Dornan, 1990), more recent work has shown that female patients have a tendency to be less satisfied with their care than males (Cohen, 1996). Considering it has been found that physicians tend to like their male patients more than their female patients and that patient satisfaction with care is significantly correlated with how much they are liked by their physician (Hall et al., 1993a), the more recent findings are more intuitive. It has also been suggested that female enrollees tend to be less satisfied with their health plan than male enrollees (for a discussion see Schlesinger et al., 1999). Here again, previous research does not attempt to explain these phenomena. It, however, appears reasonable to suggest that female enrollees are less satisfied with their health plan – for similar reasons they are less

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satisfied with their healthcare. That is, it might be that female enrollees might perceive their contacts with health plan representatives as fairly unsatisfying and negative, and thus rate their health plans lower than their male counterparts. Therefore, the next hypotheses state: H5. Male patients, as compared to female patients, are more satisfied with the healthcare they receive. H6. Male enrollees, as compared to female enrollees, are more satisfied with their health plan. The effect of educational level on satisfaction with healthcare and health plan Tendency to be less satisfied

Hall and Dornan’s (1990) meta-analysis shows a negative correlation between level of education and satisfaction with care. That is, patients with lower educational levels tend to be more satisfied with the care they receive than those with higher levels of education. It has been suggested that more educated patients have a tendency to be less satisfied because ‘‘they have heightened expectations or apply stiffer standards in their evaluation of care (regardless of the nature of that care), and are consequently disappointed compared to less educated patients’’ (Hall and Dornan, 1990, p. 817). It could be argued that the same reasoning explains Zapka et al.’s (1995) findings which indicate that enrollees with lower educational levels tend to be more satisfied with their health plans as well. Thus, the next hypotheses state: H7. Patients with a lower level of educational attainment, as compared to those with a higher level of educational attainment, are more satisfied with the healthcare they receive. H8. Enrollees with a lower level of educational attainment, as compared to those with a higher level of educational attainment, are more satisfied with their health plan.

More likely to disenroll

The effects of system performance and system usage on satisfaction with healthcare and health plan System performance. Zapka et al.’s (1995) findings indicate a strong relationship between system performance (e.g. access to care, coordination of care and patient-provider information) and satisfaction with care and plan. Specifically, patients who perceive system performance to be poor are more likely to be dissatisfied. Zapka et al. (1995) further suggest that the less satisfied are more likely to disenroll from their health plan. Druss et al. (1999) lend support to this idea by showing that patients who are dissatisfied with management of access, management of coverage and overall management of services are more likely to disenroll from their health plan than those who are satisfied. Thus, the next hypotheses are: H9. Patients who perceive system performance as being high, as compared to those who perceive system performance as being low, are more satisfied with the healthcare they receive. H10. Enrollees who perceive system performance as being high, as compared to those who perceive system performance as being low, are more satisfied with their health plan. System usage. Langley and Cook (2000) suggest that patients/enrollees who have more contact with their healthcare provider and plan show a lower level of satisfaction with both than those with lower usage rates. In a similar vein,

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Schlesinger et al. (1999, p. 549) state that ‘‘it is only the less healthy enrollees who will have substantial experience with the delivery of healthcare’’ in the managed-care environment. Likewise, Druss et al. (2000) have found that chronically ill patients tend to be less satisfied with their health plans than healthy patients. It is suggested that the chronically ill are more aware of the clinical, administrative and financial mechanisms used by their managed care providers to constrain costs and, as a result, are more dissatisfied. It is further suggested that the chronically ill might attribute the poor state of their health to their health plan and thus be less satisfied. It appears that system performance and system usage have an impact on satisfaction with both healthcare and health plan. Therefore, the next hypotheses state: H11. Patients who display low levels of system usage, as compared to those who display high levels of system usage, are more satisfied with the healthcare they receive. H12. Enrollees who display low levels of system usage, as compared to those who display high levels of system usage, are more satisfied with their health plan.

Data obtained from alliance of health plans

Methodology The data set used for the research was obtained from an alliance of health plans with 76 participating plans across the country. Individual samples were drawn for each health plan to support their internal proprietary member satisfaction research. Completed interviews were obtained from 407 to 720 or an average 531 of the members of each health plan. These differences are largely due to different starting sample sizes for the various plans. All regions of the country and all of the top 25 metropolitan areas were covered by the samples. Data were collected during the summer of 2000. A combined mail-telephone approach was used for data collection with the following steps: (1) Initial mailing of questionnaire. The initial mailing included the questionnaire, a cover letter explaining the purpose of the survey, the importance of responding and the fact that data for individual respondents would be kept confidential. Postage-paid return envelopes were also included. (2) Reminder post card. A reminder post card was sent to non-responders ten days after the initial questionnaire mailing. (3) Second mailing of questionnaire. A second questionnaire, cover letter and return mail envelope were sent to non-responders 20 days after the initial questionnaire mailing. (4) Telephone follow-up. The process of attempting to survey mail nonresponders by telephone began 21 days after the initial questionnaire mailing. Computer Assisted Telephone Interviewing (CATI) was used and all interviewing was conducted from a single location. Interviewers were trained on the specific survey prior to the start of interviewing. All interviewing was conducted under supervision, and unobtrusive monitoring of interviewers was employed for quality control purposes. The protocol called for eight callbacks to all mail non-responders. Samples for the various plans were drawn from the sample frames of current members of each plan using simple random sampling procedures. The overall response rate across all markets was 46 percent with a total of 40,383

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returned surveys. Of these, 32,624 or 80.2 percent were mail surveys and 7,759 or 19.2 percent were from the telephone follow-ups. Data were not weighted to reflect relative plan membership or any other criteria. Extensive testing

The survey instrument utilized in the present study was based on a Member Satisfaction Survey instrument that is widely used in the healthcare coverage industry and has been subjected to extensive testing by members of this industry. The median internal consistency estimate was 0.74 in this sample. Data analysis and results Multiple item measures System performance was assessed by a number of questions relating to different dimensions of this construct. Considering that each of the previous studies measuring system performance used a different set of dimensions and questions (Druss et al., 1999; Zapka et al., 1995), it was decided to utilize a set of questions that combined the measures used in these previous studies. Accordingly, the dimension SYSTEM PROBLEMS was assessed by asking a series of questions that measured whether respondents had experienced problems: (1) getting a personal doctor or nurse they were happy with; (2) getting a referral to a specialist they needed to see; (3) getting the care they or their doctor believed to be necessary; (4) with delays in health care while waiting for approval; (5) finding or understanding information in written materials; (6) getting help when needed from customer service; and (7) with paperwork relating to their health plan. Based on Cronbach’s Alpha, the reliability of these seven items was satisfactory for new measures ( = 0.6884). The second dimension of system performance relates to accessibility (SYSTEM ACCESS). This dimension was measured by asking respondents to indicate how often they: (1) got the help/advice they needed when calling; (2) got an appointment for routine/regular care as soon as they wanted it; (3) got care for illness or injury as soon as they wanted it; and (4) waited more than 30 minutes past their appointment time. Based on Cronbach’s alpha, the reliability of these four items was satisfactory for new measures ( = 0.6119).

Quality of service

The third dimension of system performance measures the quality of service provided by the doctor and nurses (SERVICE BY DOCTOR/NURSE). This dimension was assessed by asking respondents to indicate how often the staff at a doctor’s office or clinic: (1) treated them with courtesy and respect; (2) was helpful; (3) listened carefully to them; (4) explained things understandably;

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(5) showed respect for what they had to say; and (6) spent enough time with them. Cronbach’s alpha indicates that the reliability of these six items was extremely high for new measures ( = 0.8935). Assessment of satisfaction

Further, to estimate a more complete model (Hall et al., 1993a) it was decided to include single-item measures to assess satisfaction with personal doctor or nurse and satisfaction with specialist. System usage was assessed in two different ways. Usage of healthcare was measured by asking respondents to indicate how often they had been to their doctor’s office or clinic in the previous 12 months. Usage of health plan, on the other hand, was assessed by a number of questions that related to specific health plan contacts (CONTACTS WITH PLAN). Respondents were asked to indicate whether, during the previous 12 months, they had: (1) sent claims to their health plan; (2) looked for information in written materials from their health plan; (3) called their health plan’s customer service; (4) called their health plan with a complaint or problem; or (5) had experiences with paperwork for their health plan. According to Cronbach’s Alpha, the reliability of these five items was satisfactory for new measures ( = 0.6103). Regression analysis: satisfaction with healthcare as the dependent variable The dependent variable satisfaction with healthcare, was measured by asking respondents to indicate their level of satisfaction on an 11-point itemized rating scale with the anchoring points ‘‘worst health care possible/best health care possible’’. As such, the dependent variable is metric, and multiple regression analysis was used to analyze the hypothesized relationships (Hair et al., 1995). As can be seen in Tables I and II, the estimated statistical model is significant (adjusted R2 = 0.733; F = 4488.607; p = 0.001).

Link between level of education and satisfaction

Further, all independent variables are statistically significant (see Table II). Thus, H1 is confirmed (see Table III for a complete report on all hypotheses). Respondents who are healthier are more satisfied with their healthcare. H3 is also confirmed, older patients tend to be more satisfied with their healthcare than younger patients. Further, male respondents are more satisfied than female respondents, thus H5 is confirmed. H7 can also be confirmed. That is, patients with a lower level of education, as compared to those with a higher level of education, are more satisfied with their healthcare. The variables that had been developed to measure systems performance included rating of personal doctor or nurse, rating of specialist, system problems, system access and service by doctor/nurse. Accordingly, patients who express higher levels of satisfaction with their personal Model Regression Residual Total

Sum of squares

df

Mean square

F

Sig.

26,193.632 9,537.090 35,730.722

10 16,343 16,353

2,619.363 0.584

4,488.607

0.001

Table I. ANOVA – dependent variable: satisfaction with healthcare JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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Model

Coefficients Unstandardized Standardized coefficients coefficients B Std. Error Beta

(Constant) 4.929 Rating of personal doctor or nurse 0.297 Rating of specialist 0.185 Number of visits to doctor’s office or clinic –6.699E-03 Rating of overall health 4.761E-02 System problems –6.413E-02 System access –6.045E-02 Service by doctor/nurse –0.176 Age 3.975E-03 Gender –8.178E-02 Educational level –1.222E-02

0.061 0.004 0.004

0.352 0.229

0.003 0.007 0.003 0.003 0.003 0.000 0.013 0.005

–0.011 0.030 –0.102 –0.089 –0.370 0.034 –0.026 -0.010

t

Sig.

80.195 0.001 72.194 0.001 52.097 0.001 –2.614 6.942 –22.365 –17.435 –67.869 7.976 –6.455 –2.405

0.009 0.001 0.001 0.001 0.001 0.001 0.001 0.016

Note: Adjusted R Square = 0.733

Table II. Multiple regression model – dependent variable: satisfaction with healthcare

doctor or nurse tend to be more satisfied with their healthcare. Likewise, those who are more satisfied with their specialist are also more satisfied with the healthcare they receive. The variables system problems, system access and service by doctor/nurse were reverse-coded. Thus, those patients who experience more problems with their healthcare system are less satisfied with their healthcare. Likewise, those who perceive that their access to the healthcare system is restricted are also less satisfied with the healthcare they receive. And finally, those who perceive service quality provided by their doctor or nurse to be low are less satisfied with their healthcare. In summary, H9 is confirmed. In other words, patients who perceive system performance to be high, as compared to those who perceive system performance to be low, are more satisfied with the healthcare they receive. Contacts with the plan excluded

Level of satisfaction indicated

The variables developed to measure system usage included number of visits to the doctor’s office or clinic in the previous 12 months and the summary variable, contacts with plan. However, since prior theory does not give us reason to believe that specific contacts with one’s health plan should affect satisfaction with healthcare, it was decided to exclude contacts with plan from the analysis. As hypothesized, the more often patients have been to the doctor’s office the less satisfied they are with their healthcare. Thus, H11 finds support. Specifically, increased contact with the healthcare provider tends to lead to decreased satisfaction with healthcare. Regression analysis: satisfaction with health plan as the dependent variable The dependent variable satisfaction with health plan was measured by asking respondents to indicate their level of satisfaction on an 11-point itemized rating scale with the anchoring points ‘‘worst health plan possible/best health plan possible.’’ Multiple regression analysis was used to analyze the hypothesized relationships. As can be seen in Tables IV and V, the estimated statistical model is significant (adjusted R2 = 0.549; F = 2031.859; p = 0.001). All independent variables are statistically significant (see Table V). Specifically, H2 is confirmed. Respondents who are healthier are more

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0

Hypotheses H1. Healthier patients, as compared to the less healthy, are more satisfied with the healthcare they receive H2. Healthier enrollees, as compared to the less healthy, are more satisfied with their health plan H3. Older patients, as compared to younger patients, are more satisfied with the healthcare they receive H4. Older enrollees, as compared to younger enrollees, are more satisfied with their health plan H5. Male patients, as compared to female patients, are more satisfied with the healthcare they receive H6. Male enrollees, as compared to female enrollees, are more satisfied with their health plan H7. Patients with a lower level of educational attainment, as compared to those with a higher level of educational attainment, are more satisfied with the healthcare they receive H8. Enrollees with a lower level of educational attainment, as compared to those with a higher level of educational attainment, are more satisfied with their health plan H9. Patients who perceive system performance as being high, as compared to those who perceive system performance as being low, are more satisfied with the healthcare they receive

Overall results

Results by measure (if multiple measures were used or the measures differ for the dependent variables)

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

N/A

Confirmed

System problems – confirmed System access – confirmed Service by doctor/nurse – confirmed Rating of personal doctor or nurse – confirmed Rating of specialist – confirmed System problems – confirmed System access – confirmed Service by doctor/nurse – confirmed Rating of personal doctor or nurse – confirmed Rating of specialist – confirmed Number of visits to doctor’s office or clinic – confirmed

H10. Enrollees who perceive system Confirmed performance as being high, as compared to those who perceive system performance as being low, are more satisfied with their health plan Confirmed H11. Patients who display low levels of system usage, as compared to those who display high levels of system usage, are more satisfied with the healthcare they receive Confirmed H12. Enrollees who display low levels of system usage, as compared to those who display high levels of system usage, are more satisfied with their health plan

Contacts with plan – confirmed

Table III. Summary of hypotheses and results JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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Model Regression Residual Total

Sum of squares

df

Mean square

F

Sig.

30,544.451 25,567.125 55,611.577

10 16,675 16,685

3,054.445 1.503

2,031.859

0.001

Table IV. ANOVA – dependent variable: satisfaction with health plan

Model

Coefficients Unstandardized Standardized coefficients coefficients B Std. Error Beta t Sig.

(Constant) 5.797 Rating of personal doctor or nurse 0.193 Rating of specialist 0.128 Rating of overall health 8.630E-02 System problems –0.387 System access –3.158E-02 Service by doctor/nurse –4.570E-02 Contacts with plan –3.920E-02 Age 9.482E-03 Gender –4.987E-02 Educational level –8.293E-02

0.094 0.006 0.005 0.011 0.005 0.005 0.004 0.007 0.001 0.020 0.008

0.192 0.134 0.044 –0.499 –0.038 –0.079 –0.031 0.065 –0.013 -0.056

61.802 31.194 24.126 7.952 –76.133 –5.757 –11.432 –5.235 12.005 –2.483 –10.272

0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.013 0.001

Note: Adjusted R Square = 0.549

Table V. Multiple regression model – dependent variable: satisfaction with health plan

satisfied with their health plan. H4 is also confirmed, older enrollees tend to be more satisfied with their health plan than younger enrollees. Further, H6 is confirmed, male enrollees are more satisfied with their health plan than female enrollees. Likewise, H8 is confirmed. That is, as hypothesized, those enrollees with a lower level of education are more satisfied with their health plan than enrollees with a higher level of education. The variables that had been developed to measure systems performance included rating of personal doctor or nurse, rating of specialist, system problems, system access and service by doctor/nurse. Enrollees who express higher levels of satisfaction with their personal doctor or nurse tend to be more satisfied with their health plan. Likewise, those who are more satisfied with their specialist are more satisfied with their health plan. The variables system problems, system access and service by doctor/nurse were reversecoded. Accordingly, those patients who experienced more problems with the health care system are less satisfied with their health plan. Likewise, those who perceive that their accessibility to the healthcare system is restricted are less satisfied with their health plan. Finally, those who perceive the quality of service provided by their doctor or nurse to be low are less satisfied with their health plan. In summary, H10 is confirmed. In other words, patients who perceive system performance to be high, as compared to those who perceive it to be low, are more satisfied with their health plan. The variables that had been developed to measure system usage included number of visits to the doctor’s office or clinic in the previous 12 months and the summary variable contacts with plan. However, since prior theory does not give us reason to believe that specific contacts with one’s healthcare provider should affect satisfaction with one’s health plan, it was decided to 586

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exclude number of visits to the doctor’s office or clinic in the previous 12 months from the analysis. The variable contacts with plan, on the other hand, was designed to measure how much exposure to their health plan respondents had during the previous 12 months. As hypothesized, the more exposure enrollees had the less satisfied they were with their health plan. Thus, H12 is confirmed.

Findings conformed to expectations

Discussion and managerial implications Satisfaction with healthcare In regard to satisfaction with healthcare, our findings support the fact that healthier patients, older patients, males, those with a lower level of education, those who perceive system performance to be high and those with lower levels of system usage are more satisfied with their healthcare than their opposite counterparts. These findings conform to our expectations and the findings of various other, albeit less comprehensive, studies. The multivariate analysis provides further insight for those interested in influencing patient satisfaction with their healthcare. The most striking finding is the strong and pivotal role of physicians in influencing patient satisfaction with their healthcare. Though the confirmation of the importance of physicians in general did not come as a surprise, the magnitude of the relationship was, perhaps, greater than we expected. In the multivariate analysis, the three physician-related variables – service provided by doctors and doctor’s office (service by doctor/nurse), rating of personal doctor or nurse, and rating of specialist – show the largest statistical influence on satisfaction with healthcare. The effects of other independent variables including the three demographic variables, self-stated health status, number of visits to doctor’s office or clinic, whether they had problems with their health plan and issues related to access, though significant, show relatively small statistical influences on overall satisfaction with healthcare received.

Quality of interactions critical

The message for those interested in improving patient satisfaction with the healthcare they receive is fairly clear and that is to improve patient satisfaction you must improve the quality of the interactions with and services provided by physicians and their office staff. There is really no getting around this finding. The problem for policy makers in governmental agencies, health plans and organizations that provide healthcare services is that they have limited direct control and influence over how doctors deliver care, interact with patients and run their offices. Though many of these entities evaluate physician credentials, the focus of these evaluations is technical in nature – degrees, residencies, board certifications, malpractice claims and the like. These reviews very rarely include any type of patient satisfaction input. Unless organizations interested in patient satisfaction with the healthcare they receive can find ways to sensitize physicians to the needs of patients, then it is difficult to see how patient satisfaction can be substantially improved. A case in point is that doctors and medical personnel need to be educated/trained to view ‘‘less liked patients’’ in a more positive way. This is of importance in light of recent findings that indicate that medical students tend to think poorly of elderly patients (Bryant, 2002) and are a cause of concern, because patient satisfaction with care is significantly correlated with how much they are liked by their physician (Hall et al., 1993a). Satisfaction with health plan Certainly, health plans are interested in improving member satisfaction with the services they provide. As with satisfaction with healthcare, the research

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demonstrated that healthier members, older members, males, members with a lower level of education, members who perceive system performance to be high and members who have low usage of services are more satisfied with their health plan when compared to their opposite counterparts. Problems with health plans largest influence

Importance of ‘‘bedside manner’’

The multivariate analysis shows that the extent of the problems that members have had with their health plan has by far the largest statistical influence on their satisfaction with that plan. Next in importance are the three doctor related variables that were shown to be most important in influencing satisfaction with healthcare. These items are, in order of estimated statistical influence from highest to lowest, rating of personal doctor or nurse, rating of specialist and service received from the doctor and his/her office staff. Certainly, these findings give health plans something to work on, the reduction of problems experienced by members. Health plans have been criticized for having rules that are too complicated, doing a poor job of communicating those rules to members and their own employees, and being erratic in their administration of the rules (Reuters, 2000; Schmittdiel et al., 1997). To reduce enrollees’ negative perceptions HMOs should probably explore any or all of the following suggestions: .

provide enrollees with contact personnel that have been trained to answer enrollee questions in a polite and comprehensive manner;

.

examine enrollee expectations and how realistic these expectations are;

.

place greater emphasis on educating enrollees about certain aspects of their health plan (e.g. administration, rules and regulations, etc.) and how to navigate their plan;

.

find out what type of information their consumers would like to receive and then supply that information in the form of a newsletter; and

.

try to influence physician interaction with and service to patients (see discussion in the previous section).

Conclusion In conclusion, the findings of the present study are of interest to providers of both healthcare and health plans. Interestingly, the variables with the greatest effect on satisfaction with healthcare and health plan are under the direct control of physicians and HMOs and focus on communication efforts with patients and enrollees. First, to increase satisfaction with healthcare it is pivotal for doctors and their staff to work on their ‘‘bedside manners.’’ As strongly suggested, most of the variables that have been found to affect satisfaction with healthcare can be positively influenced by doctors and nurses treating patients with courtesy and respect, being helpful, listening, explaining understandably and spending time with their patients. As previously suggested, such an improvement in bedside manners might also help less healthy, younger, female or more educated patients to become more satisfied with the healthcare they receive. Second, managers of health plans should work on reducing the problems their members apparently are experiencing. Considering that especially HMOs have been the target of continuous criticism (Reuters, 2000; Schmittdiel et al., 1997), renewed focus on customer satisfaction with health plan seems to be called for. References Allen, H.M. and Rogers, W.H. (1997), ‘‘The consumer health plan value survey: round two – how plan satisfaction and consumer health can change over time’’, Health Affairs, Vol. 16 No. 4, July/August, pp. 156-66.

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Beatty, P.W., Richmond, G.W., Tepper, S. and DeJong, G. (1998), ‘‘Personal assistance for people with physical disabilities: consumer direction and satisfaction with services’’, Archives of Physical Medicine and Rehabilitation, Vol. 79 No. 6, June, pp. 674-7. Berwick, D.M. (1997), ‘‘Patient’s perspective: the total customer relationship in health care: broadening the bandwidth’’, The Joint Commission Journal on Quality Improvement, Vol. 23 No. 5, May, pp. 245-50. Bryant, M. (2002), ‘‘Med students think poorly of elderly, survey finds’’, Reuters, 13 May, available at: story.news.yahoo.com/nm/20020510/hl_nm/elderly_medstudents_1 Carroll, J. (2002), ‘‘Health-care outlays accelerated in 2000 with a jump of 6.9 percent to $1.3 trillion’’, Wall Street Journal, 8 January, p. A4. Cohen, G. (1996), ‘‘Age and health status in a patient satisfaction survey’’, Social Science and Medicine, Vol. 42 No. 7, pp. 1085-93. Dansky, K. and Miles, J. (1997), ‘‘Patient satisfaction with ambulatory healthcare services: waiting time and filling time’’, Hospital and Health Services Administration, Vol. 42 No. 2, Summer, pp. 165-77. Davis, K., Collins, K.S., Schoen, C. and Morris, C. (1995), ‘‘Choice matters: enrollees’ views of their health plans’’, Health Affairs, Vol. 14, Summer, pp. 99-112. Decker, P.J. (1999), ‘‘The hidden competencies of healthcare: why self-esteem, accountability, and professionalism may affect hospital customer satisfaction scores’’, Hospital Topics: Research and Perspectives on Healthcare, Vol. 77 No. 1, Winter, pp. 14-26. DiMatteo, M.R. and DiNicola, D.D. (1982), Achieving Patient Compliance: The Psychology of the Medical Practitioner’s Role, Pergamon, New York, NY. Druss, B.G., Schlesinger, M., Thomas, T. and Allen, H. (1999), ‘‘Depressive symptoms and plan switching under managed care’’, American Journal of Psychiatry, Vol. 156 No. 5, May, pp. 697-701. Druss, B.G., Schlesinger, M., Thomas, T. and Allen, H. (2000), ‘‘Chronic illness and plan satisfaction under managed care’’, Health Affairs, Vol. 19 No. 1, January/February, pp. 203- 9. Falvo, D., Woehlke, P. and Deichmann, J. (1980), ‘‘Relationship of physician behavior to patient compliance’’, Patient Counselling and Health Education, Vol. 2, pp. 185-8. Foley, M.E., Fahs, M.C., Eisenhandler, J. and Hyer, K. (1995), ‘‘Satisfaction with home healthcare services for clients with HIV: preliminary findings’’, The Journal of the Association of Nurses in AIDS Care: JANAC, Vol. 6 No. 5, September/October, pp. 20-5. Frost, M.H., Arvizu, R.D., Jayakumar, S., Schoonover, A., Novotny, P. and Zahasky, K.A. (1999), ‘‘Multidisciplinary healthcare delivery model for women with breast cancer: patient satisfaction and physical and psychosocial adjustment’’, Oncology Nursing Forum, Vol. 26 No. 10, pp. 1673-80. Gearon, C. (2000), ‘‘Health plan complaints common’’, Reuters, 7 June, available at: dailynews.yahoo.com/htx/nm/20000607/hl/insurance_5.html Hair Jr, J.F., Andersen, R.E., Tatham, R.L. and Black, W.C. (1995), Multivariate Data Analysis, 4th ed., Prentice-Hall, Englewood Cliffs, NJ. Hall, J.A. and Dornan, M.C. (1990), ‘‘Patient sociodemographic characteristics as predictors of satisfaction with medical care: a meta-analysis’’, Social Science and Medicine, Vol. 30 No.7, pp. 811-8. Hall, J.A., Milburn, M.M. and Epstein, A.M. (1993b), ‘‘A causal model of health status and satisfaction with medical care’’, Medical Care, Vol. 31 No. 1, January, pp. 84-94. Hall, J.A., Epstein, A.M., DeCiantis, M.L. and McNeil, B.J. (1993a), ‘‘Physicians’ liking for their patients: more evidence for the role of affect in medical care’’, Health Psychology, Vol. 12 No. 2, pp. 140-6. Hall, J.A., Feldstein, M., Fretwell, M.D., Rowe, J.W. and Epstein, A.M. (1990), ‘‘Older patients’ health status and satisfaction with medical care in an HMO population’’, Medical Care, Vol. 28 No. 3, March, pp. 261-70. Hall, J.A., Milburn, M.A., Roter, D.L. and Daltroy, L.H. (1998), ‘‘Why are sicker patients less satisfied with their medical care? Tests of two explanatory models’’, Health Psychology, Vol. 17 No. 1, pp. 70-5. Hall, J.A., Roter, D.L., Milburn, M.A. and Daltroy, L.H. (1996), ‘‘Patients’ health as a predictor of physician and patient behavior in medical visits: a synthesis of four studies’’, Medical Care, Vol. 34 No. 12, pp. 1205-18.

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Health Industry Today (1999), ‘‘HIGPA Expo attendees told ‘the smartest will win’ as BBA pressures, disintermediation change biz’’, Vol. 62 No. 11, November, pp. 20-1. Holcomb, W.R., Parker, J.C., Leong, G.B., Thiele, J. and Higdon, J. (1998), ‘‘Customer satisfaction and self-reported treatment outcomes among psychiatric inpatients’’, Psychiatric Services, Vol. 49 No. 7, July, pp. 929-34. Kramer, A.M. (1997), ‘‘Rehabilitation care and outcomes from the patient’s perspective’’, Medical Care, Vol. 35 No. 6, pp. JS48-JS57. Langley, D.A. and Cook, L.B. (2000), ‘‘Impact of health on satisfaction: a customer segmentation case study’’, Quirk’s Marketing Research Review, June, pp. 22-30. Ley, P. (1982), ‘‘Satisfaction, compliance and communication’’, British Journal of Clinical Psychology, Vol. 21, pp. 241-54. Newsome, B., Retchin, S.M., Juergensen, M., Rossiter, L., Glasheen, W. and Colley, L. (1999), ‘‘Factors associated with changes in satisfaction with care’’, Clinical Performance and Quality Health Care, Vol. 7 No. 2, April/May/June, pp. 56-62. Para, P.J. (1997), ‘‘Patient relations for modern times’’, Journal of Health Risk Management, Vol. 17 No. 4, Fall, pp. 23-9. Parkin, D.M. (1976), ‘‘Survey of the success of communications between hospital staff and patients’’, Public Health (London), Vol. 90, pp. 203-9. Pascoe, G.C. (1983), ‘‘Patient satisfaction in primary health care: a literature review and analysis’’, Evaluation Program Planning, Vol. 6, pp. 185-210. Pham, A. (1998), ‘‘Health care outlay seen doubling’’, Boston Globe, September 1, p. D1. Reuters (2000), ‘‘HMOs provide good care to elderly’’, 22 June, available at: dailynews.yahoo.com/h/nm/20000622/hl/medicare_home_1.html Reynolds, L. (1991), ‘‘Healthcare costs: the prognosis looks bleak’’, HR Focus, Vol. 68 No. 11, November, pp. 1-2. Roberts, R.E., Pascoe, G.C. and Attkisson, C.C. (1983), ‘‘Relationship of service satisfaction to life satisfaction and perceived well-being’’, Evaluation Program Planning, Vol. 16, pp. 373-83. Schlesinger, M., Druss, B. and Thomas, T. (1999), ‘‘No exit? The effect of health status on dissatisfaction and disenrollment from health plans’’, Health Services Research, Vol. 34 No. 2, June, pp. 547-76. Schmittdiel, J., Selby, J.V., Grumbach, K. and Quesenberry, C.P. (1997), ‘‘Choice of a personal physician and patient satisfaction in a health maintenance organization’’, JAMA, Vol. 278 No. 19, November, pp. 1596-9. Shinkman, R. (1997), ‘‘Price surge on the way: study says healthcare costs will jump in next five years’’, Modern Healthcare, Vol. 27 No. 23, June 9, p. 8. Ullman, R., Hill, J.W., Scheye, E.C. and Spoeri, R.K. (1997), ‘‘Satisfaction and choice: a view from the plans’’, Health Affairs, Vol. 16 No. 3, May/June, pp. 209-17. Wechsler, J. (2002), ‘‘Healthcare costs to escalate’’, Managed Healthcare Executive, Vol. 12 No. 4, April, p. 8. Zapka, J.G., Palmer, R.H., Hargraves, J.L., Nerenz, D., Frazier, H.S. and Warner, C.K. (1995), ‘‘Relationships of patient satisfaction with experience of system performance and health status’’, Journal of Ambulatory Care Management, Vol. 18 No. 1, pp. 73-83. Zeithaml, V.A. and Bitner, M.J. (2000), Services Marketing, McGraw-Hill, New York, NY.

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An executive summary for managers and executive readers can be found at the end of this issue

Buyer beliefs, attitudes and behaviour: foods with therapeutic claims Suku Bhaskaran Australian Food Marketing Centre, Victoria University, Australia

Felicity Hardley Australian Food Marketing Centre, Victoria University, Australia

Keywords Food, Health care, Consumers, Attitudes, Consumer behaviour Abstract Builds on past studies in the USA and assesses the market potential for functional goods through investigating consumer needs and attitudes. Aims to add to past research through: assessing consumer knowledge and beliefs on nutrition and diet-health relationships; analysing the influence of such knowledge and beliefs of information and sources of information; and evaluating the effectiveness and implications of government preventative health campaigns on purchase behaviour. Concludes that issues regarding personal and national health are extremely important because of the financial costs and human suffering that could be involved; and that functional goods, as a relatively new phenomenon, still need to be examined further with regard to their influence on trust and legitimacy in buyer behaviour.

Preventative health care products

Caution needed

Introduction Background The 1994 Food Technology Trend Report forecast that customer expectations and usage of food and food-ingredients in self-medication and disease prevention would be the most significant influence on the US food industry in 1995 (Sloan, 1994; Childs and Poryzees, 1997). Subsequent events show that this forecast was not over optimistic. In 1995, the retail sales of preventative health care products and services in the USA reached a staggering US$1 trillion (Jayanti and Burns, 1998). Thereafter, the market for preventative health care products and services increased even more substantially with 1999 retail sales of nutraceutical products alone valued at US$16 billion. The US nutraceuticals sector is forecast to grow at 9 percent to 10 percent annually with retail sales in 2010 estimated to reach US$34 billion. The above data, while providing evidence of significant changes to food consumption, trends must be accepted cautiously because the term nutraceutical is used non-specifically and includes any ‘‘substance that may be considered a food or part of a food and provides medical or health benefits, including the prevention and treatment of disease’’ (Hunt, 1994). According to Hunt (1994), nutraceuticals can include genetically engineered foods, raw foods, processed foods with added ingredients and processed foods without added ingredients and the only criteria is that the foods have medical or health benefits. In this study we are adopting a much narrower definition and use the term functional foods, a terminology more commonly used in some European countries. Functional foods are ‘‘foods sold for health benefits or ‘processed foods’ defined by the main ‘functional ingredient’ (oligosaccharides, fibres, The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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minerals, etc.) that are claimed to perform specific health roles such as preventing, treating and curing various diseases, and which fall into a category somewhere between food, dietary supplements and drugs’’ (Hunt, 1994).

Trends replicated in Australia

Research implications and significance Already, an increasing range and volume of products with health claims are appearing in Australian supermarkets thus suggesting that, perhaps, trends in the USA are being replicated in Australia. Changes in consumer beliefs, attitudes and responses to the consumption of functional foods would impact on the food industry and would influence company-level product development and marketing strategies and because of this, this is an important study. Research objectives Against this background of significant changes in demand trends and, perhaps, industry strategies, this article builds on past studies in the USA (Childs and Poryzees, 1997) and assesses the market potential for functional foods through investigating consumer needs and attitudes. The majority of past studies on diet-health relationships have focussed on the effects of the introduction of the ‘‘Nutrition Labelling and Education Act’’ on consumer nutrition knowledge and purchase decisions, and the development of legislation on health claims and the effect of health claims on information interpretation and purchase behaviour. This study aims to add to past research through: .

assessing consumer knowledge and beliefs on nutrition and diet-health relationships;

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analysing the influence of such knowledge and beliefs in switching to functional foods;

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analysing consumer trust and beliefs of information and sources of information; and

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evaluating the effectiveness and implications of government preventative health campaigns on purchase behaviour.

Literature review A detailed literature review was undertaken to draw on the findings of past studies and also identify knowledge gaps in past studies. The findings of the literature review and its implications for this study are as follows.

Nutrition fact panels

Knowledge and beliefs on nutrition and diet-health relationships Much of the extant literature on nutrition has focussed on the introduction of nutrition fact panels. Some studies conclude that the adoption of nutrition fact panels have increased consumer knowledge (Moorman, 1998) whereas other studies argue that greater availability of information has exacerbated consumer uncertainties because of the widespread use of product differentiation strategies by food companies (Chryssochoidis, 2000; Roddy et al., 1996). However, it seems that health and/or nutrient claims on product labels can also encourage information search with some consumers relying entirely on information on the packaging whereas others also checking the fact panel. Thus, it could be contended that some consumers use the fact panel as a

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legitimising tool in evaluating health claims. Keller et al. (1997) using the accessibility/diagnosticity framework (Alba et al., 1991; Feldman and Lynch, 1988) suggest that nutrition fact panels are a diagnostic tool for consumers to evaluate products and, therefore, minimise their reliance on health claims on product packaging.

Motivation

Consumer deception and education

Lack of success in changing consumption behaviour

Consumer characteristics and switching behaviour According to Jayanti and Burns (1998) the antecedents to preventative health care behaviour are motivation, knowledge and consciousness which are mediated by self efficacy (a ‘‘belief that target behaviours that mitigate health threats can be successfully implemented’’ (Jayanti and Burns, 1998, p. 8)), response efficacy (‘‘the extent to which a person believes a particular health care action mitigates a health threat’’ (Jayanti and Burns, 1998, p. 9)) and health value (‘‘an individual’s assessment of benefits relative to costs in engaging in preventative health care behaviour’’ (Jayanti and Burns, 1998, p. 8)). Jayanti and Burns suggest that, contrary to extant literature, consumers with greater health knowledge do not exhibit greater levels of general preventative health care behaviours. Also, Jayanti and Burns (1998, p. 10) propose that health consciousness (‘‘the degree to which health concerns are integrated into a person’s daily activities’’, significantly influence preventative health behaviours but do not influence response efficacy. In sum, according to Jayanti and Burns, education is critical to promoting health-promoting behaviour. Several studies (Burke et al., 1997; Burton et al., 1999; Ford et al., 1996; Mitra et al., 1999) have analysed consumer deception and education in relation to nutrient content and implied health claims. These studies conclude that educational standing does not influence the ability to interpret nutrition fact panels and that manufacturer health claims do not influence the interpretation of nutrition information by consumers. Ford et al. (1996), based on a study of college students, concludes that health claims do not influence the processing of nutrition information but health claims increase customer expectations. Roe et al. (1999, p. 89) examined ‘‘the impact of health claims on consumer search and product evaluation outcomes’’ and found some evidence that consumers truncate their information search in the presence of a health claim and that possible halo effects can arise (where respondents rate the product higher on other health features not mentioned in the claim). Roe et al. (1999) also distinguished between health and nutrition claims and concluded that there was little difference in consumer evaluation processes in comparing health and nutrition information. Trust and beliefs of information sources Even though it seems that government preventative health campaigns are believed, this has not significantly altered the consumption behaviour of the general population. Rothschild (1999) attributes the lack of success of preventative health campaigns in changing consumption behaviour to the pre-eminent focus of public health managers on education and legislation. Rothschild (1999) argues that preventative health practices can only succeed if consumer self-interest is considered in planning the programs. Marketing messages could be used to highlight benefits or rewards that appeal to the self-interest of consumers. In sum, education, law and marketing all have a role in managing consumer behaviour and policy

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makers need to adopt an integrated approach in their behavioural change strategies. Ippolito and Mathios (1990, 1991) attribute consumer knowledge of the fibre-cancer relationship to industry-based research and the consumer friendly way in which the research findings were disseminated. This indicates that manufacturers are useful conduits for information on diet and health. However, it would seem that consumers are sceptical of manufacturer claims because of claims and counter-claims regarding diet-health relationships by different manufacturers (Keller et al., 1997; Silverglade, 1996). Unremitting influx of conflicting scientific evidence

The notion of schema schemas, whereby consumers fashion theories or beliefs regarding marketers, particularly the persuasive intentions of marketers (Bousch et al., 1994; Friestad and Wright, 1994), has been discussed in several studies that examine nutrition information and consumer product evaluations (Keller et al., 1997; Moorman, 1996). It seems that the unremitting influx of conflicting scientific evidence, regulations and marketing information regarding diet-health relationships have made consumers highly sceptical of information on diet-health relationships (Keller et al., 1997; Silverglade, 1996). This conforms to Moorman’s (1996) longitudinal quasi experiment on the Nutrition and Labelling Education Act where she canvasses the value of the nutrition label in helping consumers to verify health claims. However, it seems that challenges of these claims by competitors and other stakeholders may exacerbate consumer mistrust and consumer acceptance of the nutrition label as a legitimist of health claims. Hackman and Moe (1999) suggest that newspapers are an important source of health and nutrition information with Byrd-Bredbenner and Grasso (1999, 2000) making similar claims for television. The literature does not indicate consumer concerns regarding the believability of media information. Methodology Beliefs and attitudes are highly subjective notions (Fishbein and Ajzen, 1975) and past studies on diet-health relationships indicate difficulties in developing reliable and valid measurement items for these constructs. For example, Parmenter and Wardle (2000) report that problems such as vagueness in terminology, respondent knowledge gaps and respondent bias constrained their survey of consumers. Shortcomings reported in past studies and the potential to understand the dimensionality of preventative behaviour (Jayanti and Burns, 1998) encouraged us to use focus group interviews in this study.

Obtain sample

Participation in the focus groups was restricted to the primary household grocery shopper. In order to obtain a representative sample but maintain homogeneity in individual focus groups, five focus groups segmented on the basis of age class and purchase behaviour (regular users/non-users of functional foods) were convened. Based on discussions with key informants, we decided that a popular brand of functional margarine, a popular brand of functional cereal and a popular brand of functional yoghurt would be used to show-case to focus group participants the functional properties and claims that characterise functional foods and differentiate these products from other products. Because many

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food products now make implicit claims, we decided that an explicit health claim was necessary to class a product as a functional food (ByrdBredbenner and Grasso, 2000; Wallack and Dorfman, 1992). The margarine, yoghurt and cereal brands that were selected as representative of functional foods made explicit health claims. Focus groups

A total of 35 individuals participated in the focus group interviews. In order to control for environmental noise, such as new information that could influence participant responses, the groups were run concurrently over a period of two days. The focus groups were segmented as follows: two groups in the 25 to 39 years age class differentiated on the basis of users and non-users of functional foods; two groups in the 40 to 59 years age class differentiated on the basis of users and non-users of functional foods; and a final group comprising of persons in the over 55 years age class. The age class categorisation was adopted to sample a cross-section of customers and evaluate differences between younger consumers, who would be expected to experience less problems with health, middle-aged consumers who often have greater time pressures and are either beginning to experience more health problems or are starting to take preventative measures, and older persons who often are themselves experiencing some ailment or who have friends/family with ill health.

Unobtrusive video and audio facilities

The interviews were conducted in a room that had unobtrusive video and audio recording facilities and a two-way observation mirror. To maximise respondent comfort and to increase informality, the discussions were conducted in a dining room setting and respondents were served refreshments all through the discussions. Results Health status and purchase behaviour As expected, factors such as taste, quality, value (price) and convenience were reported by most younger age participants to be the primary influencer of their purchase decisions. A minority of the younger participants (say about 20 per cent), reported that health attributes influence purchase decisions. Generally, such influence translates into actions such as seeking products labelled low fat, light, low sugar, low salt and natural, as well as no additives, preservatives and looking out for ‘‘too many code numbers’’ (indicating that the product contains artificial additives). Even among this group, most participants indicated that they were reactive rather than pro-active or preventative in their purchase decision-making.

Older people tended to make preventative decisions

However, older age participants (more than 55 years) tended make decisions that can be described as preventative. The behaviour of older age participants could be influenced by their perceived vulnerability as a result of seeing more sick people around them and their awareness that they are at higher risk than younger age individuals. High cholesterol readings or doctors’ warnings were enough to encourage information search and taking action such as dietary changes. The following comments from the over 55 age participants highlights this behaviour pattern: (1) Example 1: I want to keep my health, that’s all, I don’t want cholesterol problems or high blood pressure and I want to stay that way. Health wise, I’m overweight and I want to not put on any more.

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(2) Example 2: My husband has a serious heart condition. He has had a few strokes too and he has had bypass surgery, very expensive, so it makes me more aware . . . so that’s why I read labels.

(3) Example 3: I saw an ad on TV that said ‘‘it helps reduce your cholesterol’’ and I thought OK, because I’d just been told my cholesterol was up to 7.5 and that is too high, so I started looking at products and thinking, well, I’ve got to get mine down. As I said I’ve got health problems, I’m not as active, and I thought I’m doing it for me, but then the whole family’s got to be healthy as well. And that’s what made me start really reading about it. Plus dad had two minor heart attacks, and as I said mum would just buy the cheapest and the no brands and all of that and do the best. She’s changed too now because of dad’s heart attacks.

(4) Example 4: I think you hear a lot because of what happens to other people. You might know of someone who has had a heart attack and they have been told by their doctor to eat such and such and you listen to them and you think well, if they’re told by their doctor to have this particular margarine I might as well start having it before anything happens to me.

Information search limited

Manufacturers’ claims not trusted

Information search Most respondents claimed that they read nutritional fact panels and that they based food purchase decisions on nutritional information. However, further probing suggested that this information search was limited to identifying the content of fat, sugar, salt or calories, not any other nutritional information (unless the respondents have specific knowledge about or interest in other ingredients). Those with known health problems had become more informed and searched for specific nutritional information. For example, arthritis sufferers knew to look for calcium and omega 3, and those with high cholesterol and with (or at risk of) heart disease sought out cholesterol free and low fat foods. Attitude to manufacturers’ claims Most respondents (about 80 percent), even those who had already reacted to health claims by switching to a functional product, claimed that they do not trust manufacturer claims. Their purchase decision was based on the hope that the product had a therapeutic attribute but they did not necessarily believe that it would help with an existing health problem. The following are some examples of comments from purchases of functional products: (1) Example 1: Obviously you’d go for that one, even though you might not totally believe what was on the packet, at least there’s a chance! You haven’t got the time to check out if it was actually true or not but it could be a powerful thing. It would be a plus over something that didn’t have it on the packet.

(2) Example 2: I bought it because it was supposed to lower your cholesterol and it probably does, like that guy on the ad says. On the bridge doing the bungy jump, maybe he was doing other things as well, eating certain foods. That butter on its own couldn’t do it. You couldn’t be eating fried food every night and then expect this butter to save you. 596

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Functional foods

A majority of the participants also indicated that functional foods seemed to be laying claim to a health effect that its competitors could just as easily lay claim to and wanted to know why or how functional foods are different to other cereals or yoghurts. They were aware that other brands of yoghurts were being marketed as containing acidophilus and cereals as being high in fibre but these brands did not make any curative claims. In what way are functional foods different to these products? Many of the participants were of the opinion that the functional foods used as examples in the group discussions were not different to other products that contain similar ingredients. Some examples of participant comments are as follows: (1) Example 1: The products aren’t really different, they’re just claiming more.

(2) Example 2: I use Yakult. I believe what the manufacturer says about that. I totally believe what they say, it just sounds right, whereas the claims on each of those yoghurts, I can handle that, same as Yakult . . . but as for the other claims . . . those brands, they claim to lower your cholesterol . . . But just by eating that won’t lower your cholesterol!

(3) Example 3: Hasn’t bran always has those benefits, when did that change? What makes a $7 box of bran different to a $1.50 bag of bran with a home brand thing on it. Is it enhanced, is it organic, what’s different about it. Bran is bran. It’s good for you but it tastes like huh, cardboard.

(4) Example 4: All margarines are made with plant oils, sterols are oils! They’re canola oils. So what extra has that got.

Prioritized attributes

Although the participants claimed that they did not believe manufacturers’ claims they indicated that they took cognisance of what was printed on packaging and the advertising messages and this suggests that, notwithstanding their comments, manufacturers’ claims influenced product evaluation and purchase decisions. However, it was obvious that younger age participants prioritised attributes such as price, taste, packaging and promotional offerings ahead of the functional attributes of the product. Participants reported that they would consider manufacturer claims in their decision process if they were shopping for a product with a health attribute but that they would also evaluate whether the functional food satisfied their needs in terms of other attributes that they prioritised. Thus, ‘‘functionality’’ was only of importance to shoppers who were seeking out products with health attributes. Some examples of participant comments are as follows: (1) Example 1: Well that one [breakfast cereal] if you saw that on the shelf and you see ‘‘for your heart and health’’, well you’re either going to buy that one or another one so you may as well go for that one.

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(3) Example 3: The Healthwise one, I’ve got a bowel problem so I need to watch my fibre and everything, so went to shop saw that, thought great I’ll buy it and then thought oohhhh [at the cost] now I just buy some plain bran and stick it on top on my other cereal. And then the Pro-Activ [functional margarine] my mum bought it and I thought oh, that’s really good and then went to buy it and it’s too expensive. Being 30 I don’t know if I need to worry about cholesterol just yet. That can wait till later.

(4) Example 4: That’s the only reason you’d buy it, like if you already know, like I recognised the words acidophilus and bifidus because of that ad. They’re good for you and now all the yoghurts go acidophilus, bifidus. The third one you mentioned on there (lactobacillus GG), no idea what it does, couldn’t give a damn, but obviously if acidophilus and bifidus are good, that (third one) would be good, so that’s what you go for.

Need to manage systematically dietary habits

Diet-health relationships Some participants, particularly those in the older age class, demonstrated elementary knowledge of diet-health relationships and the need to systematically manage dietary habits. For example, they know that highfibre diets reduce the probability of bowel cancer and calcium-rich diets reduce the probability of osteoporosis. However, such knowledge was the outcome of their own health conditions or the health conditions of friends or relatives and these personal situations are what encouraged information search. The most common sources of such knowledge are medical practitioners and media sources. In most instances, the participants did not see the need to search for detailed information as they felt that they would receive such guidance from their doctors. Functional foods and food supplements The participants did not regard functional foods as being of the same genre as health food products. The majority of participants reiterated that the only difference between functional foods and competitive products were unsubstantiated claims by manufacturers. The participants were of the opinion that functional foods could not be used as a therapeutic or dietary supplement. They contended that even if, after substantial research and development, the disease preventing capability of functional foods was confirmed, there were several issues to be addressed. For example:

Current medical practices

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How concentrated must the food be to have a therapeutic impact?

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How much and how frequently must the food be consumed?

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How would one know if the dosage were correct?

It is obvious that participants are thinking in the context of current medical practices where the doctor would prescribe the medicine, the dosage and times of consumption, and would periodically examine the patient and reevaluate the medication. The participants could not picture therapeutic practices outside the present medical system. Information search and sources of information The discussions revealed that individuals who actively undertook information search are those with health problems or a family history of

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health problems. In most instances these individuals were already practising preventative health care through dietary changes. Reservations about reliability of information

The majority of participants indicated that manufacturers are a good trigger point for information on diet-health relationships but that they would have reservations on the reliability of such information. Overall, the participants were unsure whether there were regulations controlling manufacturer claims and, if there were such laws, whether manufacturers are policed effectively. The feeling that manufacturers could make inaccurate claims exacerbated the participants’ confidence in information from manufacturers. All participants indicated that the most trusted sources of advice on nutrition and diet-health relationships are doctors, dieticians, educational institutions and family members. The participants said that most of their basic knowledge on diet and healthy eating came from their mothers and from school (e.g. carrots are good for your eyes, need to drink your milk and eat your veggies).

Trustworthiness of information

In addition, the participants indicated that information and accreditation from organisations such as The Heart Foundation increased the reliability and trustworthiness of the information. Surprisingly, businesses such as Weight Watchers that focussed on diet and wellbeing were also regarded to be reliable sources of dietary information. About 80 percent of the respondents also indicated that the Internet was a good source of information with about 20 percent expressing concern about the reliability of information on the Internet. The comments demonstrate that organisations and individuals that are promoting health, diet and well-being (be they government, businesses or associations) are considered to be reliable and trusted sources of information but food companies and manufacturers of functional foods are not regarded as reliable and trusted sources of information. The following comments by participants highlight these findings: (1) Example 1: I come from a family with a background of high cholesterol so whatever I pick I make sure the cholesterol level is really low, that it’s got the heart tick on it. I’m not a health freak but I’m more conscious for the rest of my family because I do the grocery shopping, so half the time I’m looking for the heart tick, is everything OK with that, the level of cholesterol for that, and that mainly is the deciding factor for me. I don’t mind paying that extra bit as long as I know that it’s safe.

(2) Example 2: It’s something in my mind that I have with me and I think for them to have that heart tick they would have had to go through a certain criteria that is set which is safe.

Newspapers and television primary sources of knowledge on health

Participants with no health problems (most members of the less than 55 years age groups) indicated that newspapers and television were their primary sources of knowledge on health and well-being. They indicated that they trusted the information from these sources as the articles and shows were written or presented by health and well-being specialists. Participants with an active interest in health and diet issues tended to seek out programs and magazines that provided such information. Some examples of participant comments are as follows: (1) Example 1: Friends, a particular friend is on a protein diet so she’s cut out all of her carbohydrates, she’s got some American book. There’s always someone that’s on

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some diet or who has found out something. Through work or uni or someone you know.

(2) Example 2: If I read something in a magazine or something, by some doctor, you might take notice of something like that or you see doctor so and so on TV and you think that might be OK. Someone who looks professional and knows what they’re talking about. The credibility of the person telling you.

(3) Example 3: And like Good Medicine (TV show), they’re brilliant for educating people and I think they have a more unbiased point of view because they cover so many areas. They just provide you with information and you can make up your own mind.

Almost all participants demonstrated a high level of awareness of the following health and lifestyle campaigns by various organisations and industry bodies:

Promote use of certain products

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Life Be In It;

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osteoporosis prevention;

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anti-smoking;

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weight loss;

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skin cancer prevention.

These promotions or campaigns were regarded as being different to commercial advertising as they appeared to be targeted at increasing the health and well-being of the community. Even though the advertisements promote the use of certain products (e.g. sunscreen, milk, etc.), the advertisements were observed to be not promoting a particular brand of product and were therefore viewed as being of a ‘‘public good’’ nature. As evidenced by the following comments, generic messages even if done on behalf of a business are viewed as trustworthy and reliable: (1) Example 1: They’re creating good health and we all want to live to 80 and see our grandchildren grow up and we all want to go through that, and usually they don’t push any product – they’re pushing good health.

(2) Example 2: But they’re more concerned for actual welfare and they’re not trying to sell you a product, they say ‘‘don’t do this, get healthy’’ whereas the other ones are like ‘‘come to us and we’ll make you skinnier’’.

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Even infomercials such as the milk campaign by the Australian Dairy Corporation were not perceived as being targeted at increasing milk consumption but were seen as promoting health and well-being by encouraging individuals to adopt better dietary habits. The participants observed that these campaigns were informative and did not come across as advertisements. As much as 80 percent of the participants reported that some of these campaigns influenced their behaviour and that they now, for example, consume more milk and monitor calcium intake more closely. Almost all participants with children confirmed that the health campaigns reinforced the importance of diet and this influenced their behaviour in regard to purchasing products that were showcased as being beneficial to JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

health. This suggests that targeted campaigns impact on consumer and buyer behaviour. Graphic and effective message

While the campaign message needed to be relevant, it seems that it is not necessary or important for the messages to explicitly showcase someone in the participants’ socio-economic or age group. In fact, the participants believed that it might be necessary to show what could happen in the future. For example, the participants observed that the osteoporosis prevention campaign showed an old man not being able to answer the door in time because of his crippling osteoporosis condition and that this was a very graphic and effective message and influenced their behaviour. Discussion of findings Health/functional food claims Analyses of the discussions indicate congruence with the conclusions of Ippolito and Mathios (1990, 1991) that manufacturer claims are not only an important source of information but influence purchase decisions. Even though many participants claimed to be sceptical of manufacturer claims, the majority believed that manufacturer claims were an important starting point that triggered information search. It seems that, because of the influence of manufacturer claims, and consequent consumer behaviour, there is need to protect consumer welfare through introducing stricter regulations and enforcement of these regulations, a recommendation made in Roe et al. (1999) and Silverglade (1996) as well. Information sources and legitimacy Overwhelmingly, the participants suggested that nutritional and health claims need to be verified by independent sources and only then would they believe the message. Thus, it would seem that consumers would only trust manufacturer claims that are legitimised by independent sources. Some studies (Ippolito and Mathios, 1990, 1991; Moorman, 1998) recommend that food manufacturers, because of resource strengths and closeness to consumers, have a major role in educating the public on health, diet and well-being issues. It seems that a symbiotic relationship between governments/health organisations and food manufacturers may need to evolve to encourage wider preventative health behaviour.

Changes in dietary habits

Consumer knowledge and motivation The discussions clearly demonstrated that knowledge of diet-health relationships encouraged changes in dietary habits. Older age participants were aware of diet-health relationships and indicated that they had changed dietary habits and purchase behaviour. In this instance, knowledge was the outcome of personal experiences, experiences of peers or advice from health care professions and to this extent the findings in this study differed from the conclusions of Jayanti and Burns. According to Jayanti and Burns (1998) health knowledge, motivation and consciousness are antecedents to preventative health behaviour but better knowledge did not translate into preventative health behaviour. The discussions also suggested that, notwithstanding substantial differences in the knowledge levels of individuals, legitimised promotional messages tended to induce information search and, in some instances, even among younger age consumers, encouraged behavioural changes. For example, promotional campaigns on milk and beef consumption increased participant awareness of the benefits of calcium or iron intake and were reported as

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having encouraged consumption (for personal use) and buyer behaviour (for the use of family members).

Need to control and legitimise manufacturer claims

Preventative health campaigns The discussions indicate that some promotional messages were not believed and did not lead to behavioural changes. This demonstrates the need to control and legitimise manufacturer claims. Thus, our findings concur with Rothschild (1999) that promotional information, education and legislation must supplement one another to induce behavioural changes that can benefit the community. Analysis of comments by participants suggest that self-interest, benefits of the exchange (e.g. temporally close pay offs) and constraining forces of competition (e.g. free choice, apathy and inertia) all influence their beliefs and attitudes. Therefore, we concur with the conclusions of Rothschild (1999) that consumer self-interest motivates behavioural changes. More importantly, we conclude that the benefits of behavioural changes need to be evident or, if not, at least soon become obvious for behavioural changes to take place and be sustained. In our opinion, this explains the switching behaviour (to health foods) and growth in consumption among younger age consumers, despite several targeted campaigns encouraging greater consumption of fruits and vegetables, to low fat foods and not to fruits and vegetables. Younger age participants indicated that problems such as bowel cancer and cholesterol were not pre-eminent health concerns for them. This may explain their switching behaviour to low fat products (the benefits of which are quickly evident in terms of weight loss) compared to consuming high-fibre or calcium-fortified foods. The attitude of younger age participants to preventative health behaviour conforms to findings in other studies (Kahneman et al., 1982) that dramatic lifestyle changes cannot be effected quickly and that behavioural changes must be seen to be easy to adopt.

Convenience in information search critical

The discussions also suggested that younger age customers are unlikely to undertake information search beyond reading information on product packaging or obtaining such information from the popular media (TV and magazines). Therefore, it can be argued that convenience in information search is critical to communicating diet-health relationships, a conclusion that parallels Rothschild’s (1999) view that apathy and inertia would influence information search and behavioural changes. The participants also indicated that they would be likely to take action to change behaviour (or become more interested/less apathetic) if the information was supported by a well recognised/respected media personality. Some of the younger participants indicated that they would be more likely to adopt a product with a health attribute if high achieving sportsmen endorsed it. The findings conform to the conclusions of Daneshvary and Schwer (2000) that consumers respond positively to association endorsements and to Ohanian (1991) that endorsement of a product by a credible celebrity would influence purchase behaviour. Guidance especially from health professionals was also cited as being important and this to some extent concurs with the conclusions of Gettleman and Winkleby (2000) although Gettleman and Winkleby particularly referred to lower socio-economic groups.

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Market segments Our analyses suggest that participants in each focus group have fairly homogeneous beliefs and attitudes but that the five focus groups demonstrate significant differences from one another in terms of overall attitudes and belief. For example, individuals in the group that do not use functional products were most uncertain about the therapeutic qualities of these products and manufacturer claims. Many of the participants in this group indicated awareness of diet-health relationships and believed that high fibre cereals and fortified foods are good for health and wellbeing. However, it appears that with members of this group, firm beliefs about healthy lifestyle and knowledge of diet-health relationships are not sufficient to encourage switching behaviour. Older age group less sceptical of claims

Younger consumers unlikely to switch

Skeptical of manufacturer claims

Generally, knowledge of diet-health relationships and actions in regard to this tended to be greatest among older age participants (> 55 years class) with younger age participants tending to concentrate on the intake of low fat food or, in the case of individuals with children, concentrating on information search and purchasing products with health attributes not for themselves but for their children. The focus group consisting of older age participants demonstrated the greatest knowledge on nutrition and diet-health relationships and also the most significant switching behaviour to functional foods. The older age group also seemed least sceptical of manufacturer claims. Conclusions The results of this study suggest that consumers, particularly younger age consumers, are unlikely to switch to functional foods as a major disease preventative initiative and this, of course, has major implications for the food industry and for public policy. Public health costs are increasing and government(s) would naturally want to support preventative health programs and would be keen to see greater acceptance of functional foods by the community. It is our opinion that for greater community acceptance of functional foods, as a means of disease prevention and control, there must be a symbiotic relationship between manufacturers and health/government organisations in providing legitimacy and encouraging preventative health behaviours. Even though sales of functional foods are increasing rapidly, consumers seem to be sceptical of manufacturer claims. In some cases, there appears to be a paradox in that, although consumers are sceptical, they want to believe the claims and often chose to buy products with functional claims in preference to products that do not make such specific claims. However, younger age consumers in particular indicated that price, taste and promotional offers influenced their buying decision and their switch to functional food was only if they had decided to buy a health product. We believe that convenience and lifestyle factors would increase the consumption of functional foods. The fast pace of work and social schedules are leading ever more short cuts in cooking and food consumption and it could be that consumers are looking more and more to functional foods to make up for nutritional deficiency in their diets. The exploratory nature of this study means that there are a number of limitations in this study. This study was primarily based on focus group interviews and in all there were only 35 participants in the focus groups. Although focus groups have been recognised as ‘‘being inexpensive, data

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rich, flexible, stimulating to respondents, recall aiding and cumulative and elaborative’’ (Fontana and Frey, 1994, p. 365), there is an inherent risk in attempting to generalise the results to the population. Focus groups tend to be undertaken in an environment where participants would demonstrate a greater tendency to guard their feelings as they would not want to appear naı¨ve or gullible, and there is also a risk that participants will bias their responses in order to conform to peers in their group. Issues of research ethics meant that we advised focus group participants, at the onset, of the research objectives and we believe that this may have biased their responses. Also, the participants in the focus groups were predominantly females and, therefore, there could have been some level of gender bias in the responses. These limitations mean that the findings cannot be conclusively used to generalise the beliefs, attitudes and behaviour of the population being studied (Churchill, 1995; Kinnear et al., 1994). Relatively new phenomenon

Notwithstanding these limitations, this study should form a valuable starting point for an in-depth and more broad-based study. Issues regarding personal and national health are extremely important because of the financial costs and human suffering associated with ill health and we recommend that this study be extended into a detailed survey of a larger sample of the population, quantitative analysis of the data, repeating the survey and comparing the findings over time. Also, there are several theoretical implications in this study. In particular, functional foods are still a relatively new phenomenon and the influence of trust and legitimacy in buyer and consumer behaviour would need to be probed in detail. References Alba, J.W., Hutchinson, J.W. and Lynch, J. (1991), ‘‘Memory and decision making’’, in Robertson, T.S. and Kassarjian, H.H. (Eds), Handbook of Consumer Behavior, PrenticeHall, Englewood Cliffs, NJ, pp. 1-49. Bousch, D.M., Friestad, M. and Rose, G.M. (1994), ‘‘Adolescent skepticism toward TV advertising and knowledge of advertiser tactics’’, Journal of Consumer Research, Vol. 21, June, pp. 167-75. Burke, S.J., Milberg, S.J. and Moe, W.W. (1997), ‘‘Displaying common but previously neglected health claims on product labels: understanding competitive advantages, deception, and education’’, Journal of Public Policy & Marketing, Vol. 16 No. 2, pp. 242-55. Burton, S., Garretson, J.A. and Velliquette, A.M. (1999), ‘‘Implications of accurate usage of nutrition facts panel information for food product evaluations and purchase intentions’’, Journal of the Academy of Marketing Science, Vol. 27 No. 4, pp. 470-80. Byrd-Bredbenner, C. and Grasso, D. (1999), ‘‘A comparative analysis of television food advertisements and current dietary recommendations’’, American Journal of Health Studies, Vol. 15 No. 4, pp. 169-80. Byrd-Bredbenner, C. and Grasso, D. (2000), ‘‘What is television trying to make children swallow?: content analysis of the nutrition information in prime-time advertisements’’, Journal of Nutrition Education, Vol. 32 No. 4, pp. 187-95. Childs, M.N. and Poryzees, G.H. (1997), ‘‘Foods that help prevent disease: consumer attitudes and public policy implications’’, Journal of Consumer Marketing, Vol. 14 No. 6, pp. 433-47. Chryssochoidis, G. (2000), ‘‘Repercussions of consumer confusion for late introduced differentiated products’’, European Journal of Marketing, Vol. 34 Nos 5/6, pp. 705-22. Churchill Jr, G.A. (1995), Marketing Research: Methodological Foundations, 6th ed., The Dryden Press, Fort Worth, TX. Daneshvary, R. and Schwer, R.K. (2000), ‘‘The association endorsement and consumer’s intention to purchase’’, Journal of Consumer Marketing, Vol. 17 No. 3, pp. 203-13.

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Feldman, J.M. and Lynch Jr, J.G. (1988), ‘‘Self-generated validity and other effects of measurement on belief, attitude, and behavior’’, Journal of Applied Psychology, Vol. 73, August, pp. 421-35. Fishbein, M. and Ajzen, I. (1975), Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, J. Wiley & Sons, New York, NY. Fontana, A. and Frey, J.H. (1994), ‘‘Interviewing: the art of science’’, in Denzin, N.K. and Lincoln, Y.S. (Eds), Handbook of Qualitative Research, Sage, Thousand Oaks, CA, pp. 361-76. Ford, G.T., Hastak, M., Mitra, A. and Jones Ringold, D. (1996), ‘‘Can consumers interpret nutrition information in the presence of a health claim? A laboratory investigation’’, Journal of Public Policy & Marketing, Vol. 15 No. 1, pp. 16-27. Friestad, M. and Wright, P. (1994), ‘‘The persuasion knowledge model: how people cope with persuasion attempts’’, Journal of Consumer Research, Vol. 21, June, pp. 1-31. Gettleman, L. and Winkleby, M.A. (2000), ‘‘Using focus groups to develop a heart disease prevention program for ethnically diverse, low-income women’’, Journal of Community Health, Vol. 25 No. 6, pp. 439-53. Hackman, E.M. and Moe, G.L. (1999), ‘‘Evaluation of newspaper reports of nutrition-related research’’, Journal of the American Dietetic Association, Vol. 99 No. 12, pp. 1564-6. Hunt, J.R. (1994), ‘‘Nutritional products for specific health benefits: foods, pharmaceuticals, or something in between?’’, Journal of the American Dietetic Association, Vol. 94 No. 2, pp. 151-4. Ippolito, P.M. and Mathios, A.D. (1990), ‘‘The regulation of science-based claims in advertising’’, Journal of Consumer Policy, Vol. 13, pp. 413-45. Ippolito, P.M. and Mathios, A.D. (1991), ‘‘Health claims in food marketing: evidence on knowledge and behaviour in the cereal market’’, Journal of Public Policy & Marketing, Vol. 10 No. 1, pp. 15-32. Jayanti, R.K. and Burns, A.C. (1998), ‘‘The antecedents of preventative health care behaviour: an empirical study’’, Journal of the Academy of Marketing Science, Vol. 26 No. 1, pp. 6-15. Kahneman, D., Slovic, P. and Tversky, A. (1982), Judgement Under Uncertainty Heuristics and Biases, Cambridge University Press, Cambridge. Keller, S.B., Landry, M., Olson, J., Velliquette, A.M., Burton, S. and Andrews, J.C. (1997), ‘‘The effects of nutrition package claims, nutrition facts panels, and motivation to process nutrition information on consumer product evaluations’’, Journal of Public Policy & Marketing, Vol. 16 No. 2, pp. 256-69. Kinnear, T.C., Taylor, J.R., Johnson, L. and Armstrong, R. (1994), Australian Marketing Research, McGraw-Hill Book Company Australia, Sydney. Mitra, A., Hastak, M., Ford, G.T. and Jones Ringold, D. (1999), ‘‘Can the educationally disadvantaged interpret the FDA-mandated nutrition facts panel in the presence of an implied health claim?’’, Journal of Public Policy & Marketing, Vol. 18 No. 1, pp. 106-17. Moorman, C. (1996), ‘‘A quasi experiment to assess the consumer and informational determinants of nutrition information processing activities: the case of the nutrition labeling and education act’’, Journal of Public Policy & Marketing, Vol. 15 No. 1, pp. 28-44. Moorman, C. (1998), ‘‘Market-level effects of information: competitive responses and consumer dynamics’’, Journal of Marketing Research, Vol. 35, February, pp. 82-98. Ohanian, R. (1991), ‘‘The impact of celebrity spokespersons’ perceived image on consumers’ intention to purchase’’, Journal of Advertising Research, Vol. 31, February/March, pp. 46-54. Parmenter, K. and Wardle, J. (2000), ‘‘Evaluation and design of nutrition knowledge measures’’, Journal of Nutrition Education, Vol. 32 No. 5, pp. 269-77. Roddy, G., Cowan, C.A. and Hutchinson, G. (1996), ‘‘Consumer attitudes and behaviour to organic foods in Ireland’’, Journal of International Consumer Marketing, Vol. 9 No. 2, pp. 41-63. Roe, B., Levy, A.S. and Derby, B.M. (1999), ‘‘The impact of health claims on consumer search and product evaluation outcomes: results from FDA experimental data’’, Journal of Public Policy & Marketing, Vol. 18 No.1, pp. 89-105. JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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Rothschild, M.L. (1999), ‘‘Carrots, sticks, and promises: a conceptual framework for the managment of public health and social issue behaviors’’, Journal of Marketing, Vol. 63 No. 4, pp. 24-37. Silverglade, B.A. (1996), ‘‘The Nutrition Labeling and Education Act – progress to date and challenges for the future’’, Journal of Public Policy & Marketing, Vol. 15 No. 1, pp. 148-50. Sloan, E. (1994), ‘‘Top ten trends to watch and work on’’, Food Technology, July, pp. 89-100. Wallack, L. and Dorfman, L. (1992), ‘‘Health messages on television commercials’’, American Journal of Health Promotion, Vol. 6, pp. 190-6.

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An executive summary for managers and executive readers can be found at the end of this issue

Using data mining/data repository methods to identify marketing opportunities in health care Edward Rafalski Vice President, Planning, Sinai Health System, Chicago, Illinois, USA

Keywords Data mining, Data storage, Obstetrics Abstract Using data mining techniques, opportunities for improving continuity of care, improving patient satisfaction, and enhancing system revenue were discovered at Sinai Health System, Chicago by analyzing the compliance of patients in prenatal care and subsequent delivery at the hospital with which their primary care clinic was affiliated. This led to the development of a telephone survey used to determine why patients who were receiving prenatal care at the health system’s affiliated primary care sites chose to deliver their baby at other non-affiliated hospitals. The results of the survey are being used by management and marketing in order to improve processes in ways that would minimize the lost business.

Health care marketing

Introduction The purpose of this case study is to provide the health care marketing professional a method by which to use proprietary consumer data to analyze consumer behavior and use the information gained to expand market opportunities. The elegance of the approach discussed is that improving quality also created competitive advantage provided by integrating multiple databases and analyzing consumer behavior across a continuum of services in multiple geographic locations over time. With the evolution of health care information technology and its available underlying databases, vertically integrated health care systems can now better understand their own consumers and their health care needs. Vertically integrated health care systems are composed of multiple levels of patient services including primary care, specialty care, inpatient hospital care, rehabilitation and home care. These services are typically organized within separate corporations held by a parent company and usually include multiple primary care clinic locations and hospitals. Very often, despite the corporate controls and mutual interests, clinical and billing data gathered by these disparate corporations are not integrated, nor are they shared.

Integrated data warehouse

An integrated data warehouse and the ‘‘mining’’ of its component data have been coupled with customer telephone surveying at Sinai Health System, Chicago in an effort to improve continuity of care and increase market share. A case example – continuity of care in obstetrics Opportunities for improving continuity of care were discovered by analyzing the compliance of patients in prenatal care and subsequent delivery at the hospital with which their primary care clinic was affiliated. This led to the development of a telephone survey used to determine why patients who were receiving prenatal care at the health system’s affiliated primary care sites The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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chose to deliver their baby at other non-affiliated hospitals. The loss/ potential recovery of revenue to the parent company has been estimated to be between $3-6 million per year. Background Sinai Health System, a vertically integrated health care provider composed of a 432 bed, teaching, tertiary care, not-for-profit hospital, a 125 bed rehabilitation hospital, A 190 physician multi-specialty medical group and a non-medical community health services organization, began the development of a data warehouse in 1994. Single master database

Initially, the warehouse contained primarily demographic information from disparate billing databases within multiple physician groups affiliated with the parent company. An algorithm was developed to match patients from these disparate databases using certain fields of data such as last name, first name, address and birth date. The matching process resulted in a single master database containing one record per individual representing most of the patient billing activity associated with the parent company and its multiple subsidiaries. The prototype warehouse was created for the purpose of enabling coordinated communication with patients served by the health system. Subsequently and over time, clinical data were added to the warehouse allowing for retrospective analysis of health care service utilization across the continuum of care – from the time a patient had their first encounter in the health system (regardless of where) to an appointment with their primary care physician in an outpatient clinic, through an inpatient encounter at the hospital, through inpatient and outpatient rehabilitation and to any of the follow-up visits with the primary care physician, or any other system service.

One captive system

The competitive advantage of Sinai’s analytical approach is in the integration of its data across multiple business enterprises. Many health care organizations’ physician billing operations are separate from the parent company and data are typically considered proprietary and not shared. In Sinai’s case, physicians are employed by, or contracted full time through, one of two major groups controlled or affiliated with the health system. All billing services, including physician and hospital(s), are within one captive system using a master patient index and are therefore integrated. The uniform master patient index allows for tracking patients across the continuum of care in the data warehouse. Analyzing data across the continuum of care and vertical integration Gathering outcomes data and analyzing it to provide useful information is critical to improving the quality of process, whether in manufacturing or health care. In the US health care system, until recently, this activity has been more aggressively pursued by health plans and insurance companies wanting to track, analyze and manage costs and clinical outcomes. As the primary aggregators of claims data, health plans have been quick to mine it to better understand and measure the cost-effectiveness of various medical treatments (Stammer, 2002). However, the rising number of large, vertically integrated, multi-hospital systems with employed physicians provides another viable source of outcomes measurement. Increasingly, provider organizations are being pressured to collect clinical data, particularly at the point of care, as governmental and private regulatory agencies add quality of care measures and outcome measurement to their accreditation, funding and patient safety process.

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Vertically integrated systems are arguably better positioned than are their stand-alone disparate competitors to meet this challenge because of their inherent ability to warehouse multiple billing databases throughout the continuum of care.

Differences between data warehousing and data mining

Data warehousing vs data mining It is important to clarify the difference between data warehousing and data mining. A data warehouse consists of a set of programs that extract data from the operational environment; it is a term for what you do when you bring together all the data you have collected in a useful form. Through data mining, health care providers (and other businesses) can use a warehouse to distill the often-valuable information buried within. Data mining is a term used to describe analysis of warehoused data to generate new insights. It is a much more undirected kind of analysis (Fiske, 2002). Data mining begins with trend analysis and the search for patterns in the underlying data. Once a pattern of interest is identified, statistical analysis is applied to determine whether the pattern is significant. If it is found to be of significance, root cause analysis is applied to determine the cause of the trend. Interviews, telephone surveys and further data/statistical analysis are techniques that are applied during the root cause process. This is the point at which service quality improvement and marketing/communication begins.

Success depends on quality service

Marketing and data mining Marketing should begin with an understanding of the product being presented and the target marketplace. The exchange between patient and health care provider (including physician/nurse, alternative medicine professional) is the essence of most products being offered in traditional health care. The success of the exchange depends on the quality of service perceived by the patient and the clinical outcome. Often, the two are unrelated. In the case of obstetrics, a patient may have successfully delivered a healthy baby, but the quality of the nursing care, pain management and physical environment may not have met the patient’s expectations and therefore led to a poor perception of quality during the delivery process. These poor perceptions of quality undermine an organization’s ability to increase market share in an increasingly competitive health care industry. Understanding specifically where the patient’s perception was negatively affected and constructing a positive response should be at the core of a successful marketing approach. Conversely, identifying positive perceptions and outcomes and communicating both to the marketplace are equally important in growing market share. Data mining can assist in both instances during the marketing process.

Three key trends identified

Case example – continuity of care in obstetrics During the fall of 2001 three key trends were identified in the organization’s obstetric service using data mining. First, during a normal review of consumer activity, it was noted that volumes in inpatient deliveries were trending downward, particularly during the period July through December, 2001 (Figure 1). Second, upon reviewing consumer survey results, patient perceptions of overall quality in the hospital were trending downward during the same period, particularly in obstetrics (Figure 2).

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Figure 1. Deliveries by month

Figure 2. Overall quality of care

Control-charting methods

Third, the most significant trend was that a significant number of patients receiving prenatal care were not delivering at their primary care clinic’s affiliated hospital during the same period (Figure 3). In fact, using controlcharting methods adopted from total quality management principles applied in the manufacturing industry, it was determined that the prenatal care/ delivery trend fell below two standard deviations about the mean rate indicating a statistically relevant event had occurred. The fact that all three analyses reinforced each other made the desire to understand and correct the problem of particular interest and the focus of marketing efforts. Data mining methods Physician billing data were matched against hospital billing data in this analysis. Billing codes used for prenatal care were used to identify women who were seen at least twice during the course of their pregnancy in a primary care clinic owned by the parent company. Every month, cohorts of women were followed prospectively for nine months to determine if they delivered at the hospital of preference that was also owned by the parent company. The incentives for performing this analysis were multiple: improving the continuity of care, improving quality birthing outcomes and minimizing unnecessarily lost revenue.

Figure 3. Percentage of patients delivering with 2+ prenatal visits 610

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Improving the birthing outcome

Assuring that a patient receives prenatal care throughout her pregnancy and successfully delivers her baby is generally accepted as good clinical practice and demonstrably improves the birthing outcome. Assuring that the patient stays within the family of health care providers, specifically the employed physician and affiliated hospital, is also good business practice. It has been demonstrated within public health that the provision of complete prenatal care services to expectant mothers is of benefit to the mother and baby and leads to healthier birthing outcomes. From a marketing perspective, the provision and frequency of prenatal care promotes a bonding experience between physician/midwife and patient. The greater the bond between provider and patient, the greater the probability the patient will deliver her baby at the provider’s facility of choice.

Improving processes

After performing the prenatal care/delivery analysis, results were presented to senior management by marketing with the recommendation that a customer satisfaction survey be designed and implemented to determine the root causes for the disturbing downward trend in prenatal/delivery rates. Approximately 1,400 patients who received prenatal care over a period of 18 months but did not deliver at the parent company’s hospital were identified. This number did not account for fetal losses that would have to be taken into account in the development of any survey. After factoring in an assumption for these rates, it was determined that between $3 and $6 million of service revenue was involved in redirecting this volume back to the affiliated hospital. The results of the survey were used by management and marketing by improving processes in ways that would minimize the lost business. Prenatal services assessment survey A prenatal services consumer survey was developed jointly by the health system’s marketing staff and Professional Research Consultants (PRC) of Omaha, Nebraska. A telephone-based instrument was prepared with input provided by nursing staff, physicians, case management staff and management. Advantages of a telephone-based approach With PRC’s telephone-based approach, the patient completes the questionnaire with a trained interviewer. PRC uses a computer-aided telephone interviewing (CATI) system that ensures consistency in the research process and a high level of quality. PRC’s methodology allows the surveyor to achieve a random sample that yields scientifically valid results. A high participation rate of 90 percent or more provides a sample that is highly representative of the targeted population. A random sample (and therefore a representative sample) of respondents contacted by telephone are more likely to truly represent the opinions and perceptions of the target respondent segment than those who choose of their own volition to respond to a mailed instrument. Because the disconnected/bad number fail rate is highly correlated to the length of time which has passed between the patient encounter and patient interview, the telephone methodology brings the added advantage of rapid turnaround time to the surveyor.

Concern regarding patient confidentiality

Patient confidentiality Particular concern was expressed regarding the issue of patient confidentiality and sensitivity for those who may have miscarried or aborted. If it was determined that a patient did not deliver, interviewers were instructed to express sympathy to the patient and their families and terminate the interview.

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Great care to ensure compliance with the law

The sample of 1,400 patients included fields of information necessary for the interviewer to appropriately identify them including: name, zip code, physician providing prenatal care, location of last prenatal encounter and age. Because of recent developments regarding patient confidentiality under legislation written under the auspices of the Health Insurance Portability and Accountability Act (HIPAA), great care was given to ensure compliance with the law as currently interpreted. PRC was asked to sign a non-disclosure confidentiality agreement and all records were encrypted to prevent a third party from obtaining the underlying data. Lastly, patients were given an opportunity to ‘‘opt out’’ where they could indicate that they did not wish to participate, be called in the future or participate in any future survey. Descriptive characteristics of the telephone sample Of the 1,400 records provided, 86 percent (1,209) were usable. Discarded records either had unusable telephone numbers or incomplete information. A sample of 10.5 percent (127) of the interviews was completed providing a confidence interval of + 8 percent. Of the remaining records: 31 percent (381) had a disconnected telephone number; 24 percent (288) respondents indicated that no one by the patient’s name lived in the household; 8.7 percent (105) were not being answered; 2.6 percent (31) were to businesses (PRC does not interview people at business numbers); 1.2 percent (15) patients responded that they did not or did not remember receiving prenatal care at the clinic of record; and 8.3 percent (100) patients refused to participate in the interview altogether. Summary results The top three reasons given by patients who had received at least two prenatal care visits at an affiliated primary care clinic but chose to deliver at a non-affiliated hospital were: close to home (25.6 percent), doctors recommendation (17.9 percent) and emergency situation (17.9 percent). Other reasons cited were past experience, insurance requirements, no choice, better quality care and comfort. Additional key findings in the survey included: 92 percent of the patients surveyed never attended a childbirth class, 86 percent never received a tour of the obstetrics unit and 71 percent had more than one child.

Continuity of care

Marketing implications of results While little could be done to influence geographic distance to the hospital, the remaining drivers were actionable. Most physicians delivering babies at the hospital in the study were from one of two medical groups affiliated with the parent company. All physicians were salaried or contracted. The fact that 17.9 percent of the patients responded that their system physician recommended that they deliver elsewhere (with the detail of which patient and physicians easily retrievable) provides marketing and case management staff, such as social workers, with an opportunity to educate the medical staff and re-enforce the importance of continuity of care. The health system has contracted with an ambulance service for the purpose of ensuring that patients in prenatal care have access to the hospital of choice, upon the beginning of labor. In this case, 17.9 percent of the patients were taken elsewhere because of an emergency situation that provides an opportunity for marketing and case management staff to educate/remind patients, physicians and clinic staff that such transportation service exists.

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Obvious marketing opportunities exist for promoting childbirth classes and obstetric unit tours. Finally, physician/patient bonding with women who had multiple births can be improved through a variety of means, including regular reminders generating subsequent visits to pediatricians and obstetricians providing routine ongoing care to both the mother and child. Patient and hospital bond

If marketing, in conjunction with other key clinical staff, is successful in reducing the number of women citing emergency situations and doctors recommending that they deliver elsewhere, more than 200 additional mothers in prenatal care will deliver at the affiliated hospital. Encouraging participation in prenatal care and obstetric unit tours will further improve the bond between patient and the hospital. All of these efforts will require a shift in organizational culture. Summary Integrating proprietary databases can be successfully used to identify key trends in healthcare organizations. This becomes more achievable when organizations can functionally integrate from a corporate perspective, share information technology services and migrate databases into compatible formats/structures. Once key trends are identified, marketing departments can work successfully with management to affect operational performance, improve clinical outcomes and expand business. Managerial implications and applications Marketing professionals have a critical role to play with management in the improvement of health care operations – marketing is not simply advertising, as it is commonly perceived to be in the health care industry. The development of integrated proprietary databases can lead to a wealth of information that can be used to successfully expand marketing opportunities. It is important to note that, in an era of increased regulatory scrutiny of customer privacy, extreme caution must be used to ensure that privacy is not compromised either while analyzing the data or surveying customers during root cause analysis. Lastly, database skill development is central to the success of the approach discussed. While it is important to possess writing, graphic design and advertising skills, database development and analysis skills can only enhance the marketing professional’s ability to work with management to improve quality and grow business, which is a common goal shared by both. References Fiske, H. (2002), ‘‘Mining your own business: unearthing the treasures in your database’’, For The Record, May, pp. 26-8. Stammer, L. (2002), ‘‘Compounding interest in data banks: the key to outcomes management is having data from across the continuum of care’’, Healthcare Informatics, May, pp. 53-8.

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An executive summary for managers and executive readers can be found at the end of this issue

The American Hospital Association’s Annual Survey of Hospitals: a critical appraisal Ross Mullner Associate Professor, Health Policy and Administration, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, USA

Kyusuk Chung University Professor, Division of Health Administration and Human Services, College of Health Professions, Governors State University, University Park, Illinois, USA

Keywords Hospitals, Statistics, Surveys, Error cause identification Abstract Data from the American Hospital Association’s Annual Survey of Hospitals, which are used to produce the AHA Guide, Hospital Statistics, and other data products, are widely used by hospital administrators, academic researchers, and healthcare marketers. Although they are widely used, many who use data from the survey are unaware of their limitations and problems. Such problems include: inaccuracies and inconsistencies in reporting; low response rates to certain data items; biases in reporting; and a lack of publicly available technical documentation concerning the statistical methodology of the survey, particularly its estimation and imputation procedures for missing data. Failure to be sophisticated consumers of data products can misdirect the outcome of important planning and marketing efforts.

Traditional marketing sciences

As the business of health care becomes of greater concern to health care managers throughout the industry, they are turning to traditional marketing sciences to improve their business outcomes. This often leads to a search for competitive market place data on which to base planning. Perhaps the most elementary and widely used database consulted has been the annual Guide Issue data published by the national organization of hospitals – the American Hospital Association. The American Hospital Association (AHA) is the oldest, largest, and most prestigious hospital association in the USA. Founded in 1898, the AHA ‘‘seeks to advance the health of individuals and communities.’’ It ‘‘leads, represents, and serves health care provider organizations that are accountable to the community and committed to health improvement.’’ Much of the AHA’s efforts are devoted to developing healthcare policies, and lobbying the federal government on behalf of the nation’s hospitals. The AHA is headquartered in Chicago. It also has a large Washington, DC office, and numerous smaller regional offices. The not-forprofit association has a staff of 884, and a yearly budget of $79 million. Most of the AHA’s budget comes from institutional dues from its nearly 5,000 member hospitals, while other funds come from 37,000 individual members (Ballard, 2001).

Annual Survey of Hospitals

Since 1946, the AHA has conducted an Annual Survey of Hospitals. The survey, which is conducted in the fall of each year, asks hospitals to report data for the past 12-month operating period. Hospitals may complete the survey either online or by mailed questionnaire. Most hospitals The research register for this journal is available at http://www.emeraldinsight.com/researchregisters The current issue and full text archive of this journal is available at http://www.emeraldinsight.com/0736-3761.htm

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(approximately 70 percent) complete it online. Data from each survey are extensively checked for internal consistency by computer and manually by staff members of the association. The survey has a high overall response rate (83 percent for the year 2000). However, response rates vary greatly by question. For non-reporting hospitals or those that submit incomplete survey questionnaires, data are estimated. Collected information

Other data items collected

Over the years, the AHA annual survey has consistently collected information on hospital facilities and services, utilization, expenses, and staffing patterns. Examples of specific items include: .

geographic location (state, county, city, and zip code);

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control (government nonfederal, non-government not-for-profit, investor-owned (for-profit), and government federal);

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service (general, special, rehabilitation and chronic disease, and psychiatric);

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facilities (blood bank, cardiac intensive care unit, CT scanner, diagnostic radioisotope facility, emergency department, home health department, etc.).

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number of beds, cribs, and pediatric bassinets set up and staffed for use;

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utilization data (total inpatient admissions, average daily inpatient census, total number of outpatient visits, and total number of births);

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financial performance (total yearly expenses, payroll expenses, revenue, unrestricted funds, restricted funds, and capital expenditures); and

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total number of hospital personnel.

More recently other data items have been collected. They include membership in a health care system or health network, type of physician arrangements, insurance products, managed care contracts, and the degree of involvement and community orientation of the hospital. Data from the annual survey are available online, on CD-ROM, and are published in two publications the AHA Guide (AHA, 2000) and Hospital Statistics, AHA, 2002). The AHA Guide is a large comprehensive directory that lists every hospital in the nation by state, city, and county. It provides such information as the hospital’s address, telephone number, Web address, name of the hospital’s president or chief executive officer, accreditation status by various private and governmental organizations, facilities and services offered by the institution, total payroll and yearly expenses, and the total number of hospital personnel. Hospital Statistics, on the other hand, reports aggregate statistical hospital data. The publication provides national historical trend data on hospital utilization, personnel, and finances for selected years from 1946 to 2000. It reports hospital data by eight bed size categories (6-24, 25-49, 50-99, 100199, 200-299, 300-399, 400-499, and 500+) and various geographic regions (e.g. total US, census divisions, states, and Metropolitan Statistical Areas). It lists various community health care activity indicators (i.e. beds, admissions, inpatient days, and emergency room outpatient visits) per 1,000 of the population. Hospital Statistics also provides information on the total number of selected hospital facilities and services by geographic area. Lastly, it includes a comprehensive glossary of terms and a copy of the annual survey questionnaire.

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Identifying emerging trends

Because of their long standing presence, and persistent collection and availability these resources have been well established in the hospital management community. Both the AHA Guide and Hospital Statistics are widely used by hospital administrators, academic researchers, and healthcare marketers, and are afforded a sense of reliability. Healthcare marketers, for example, frequently use data from these two publications to segment hospital markets, analyze their territories, conduct marketing campaigns, and identify emerging trends occurring at local, regional, and national levels. Most people who use these publications and other data products that are produced from the annual survey, however, are unaware of their limitations and problems. Those problems include inaccuracies and inconsistencies in reporting, low response rates to certain data items, biases in reporting, and a lack of publicly available technical documentation of the survey’s methodology. Perhaps the greatest limitation of the AHA’s annual survey is the fact that it contains voluntarily reported data. The survey literally relies on the goodwill and altruism of hospital administrators to supply complete and accurate responses. Most administrators probably complete the survey accurately. However, many others do not. Some administrators refuse to report data that reflects unfavorably upon them and the institutions they manage. Administrators frequently do not report low occupancy rates, and financial data when their hospitals are experiencing problems. For example, in an analysis of annual survey data for hospitals that closed in the Chicago Metropolitan Area from 1950-2000, researchers found that most of the hospitals stopped reporting data five years or more prior to their closure (Mullner et al., 2002).

Lack of independent validation

Another important problem is the lack of independent validation of annual survey data. The AHA review is much more focused on the internal consistency or reliability of the data it collects than its validity or truthfulness. The AHA spends most of its data collection efforts conducting computer checks and manual reviews and edits of the data. For example, when a hospital enters its survey data online it is subjected to approximately 900 computer checks. Specific responses are compared to those reported previously, and the totals in rows and columns are checked for accuracy. The association, however, does not attempt to independently verify the validity of the data that it receives by comparing it to other data sources. Thus, the validity of the annual survey data submitted is unknown.

Little agreement between datasets

In one recently published study of changes in hospital ownership in California, researchers comparing reported data from the AHA’s annual survey to that of mandated Hospital Disclosure Reports found little agreement between the two data sets. Their study concluded: ‘‘Overall, our analysis indicates that the AHA database is limited in its ability to identify hospital ownership changes. Researchers using AHA data to examine issues related to changes in hospital ownership or consolidation should take into account the limits with which ownership is reported’’ (Mitchell et al., 2001, 2002). Another source of inaccuracies and inconsistencies in the annual survey data is due to respondent error. Although the AHA sends the survey to the hospital’s president or chief executive officer to complete, he/she frequently does not fill it out. Because the survey questionnaire is long (16 pages in 2000), time consuming, and requires information from many departments, the survey is often given to a hospital administrative intern, clerk, or in some

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cases a secretary to complete. In many cases that person may have very little knowledge of the institution and its operations. Many hospitals refuse to report financial data

Although the overall response rate to the AHA’s annual survey is relatively high, response rates to individual questions are frequently very low (50 percent or less). Many hospitals, for example, refuse to report financial data. Or, if they do report it to the association, they refuse to allow that data to be released to others. Hospital administrators in many cases are fearful their hospital’s revenue and expense data may be obtained by their competitors, or that state regulators may obtain the data and use it against them. The annual survey also has problems with biases in reporting. Some categories of hospitals are much more likely to respond to the survey than others. For example, non-government not-for-profit hospitals tend to respond to the survey more frequently than investor owned or for-profit hospitals. The presumably more competitive for-profit institutions’ failure to respond may be because they do not want to give their competitors the advantage of knowing what they are doing. Similarly, larger hospitals (200 or more beds) tend to respond more frequently than smaller hospitals (six to 99 beds). Larger institutions may respond more frequently because they have a larger staff available to complete the survey.

Tightly integrated

Fundamental structural changes in the nation’s hospital industry are also causing problems in reporting. During the first few decades the AHA annual survey was conducted most of the nation’s hospitals were independent standalone institutions with few affiliations. And each hospital responded for itself. Starting in the 1980s and continuing in the 1990s, however, hospitals increasingly became members of healthcare systems and networks. Today, many of these systems are so tightly integrated that the individual hospitals in them can no longer meaningfully report data for their institutions. Further, some healthcare systems that could report hospital specific data frequently refuse to do so because of the cost and time constraints. The growing creation of large integrated health systems may be making participation in and reliance on a national association less desirable. Lastly, the AHA does not publish any publicly available technical reports documenting the annual survey’s statistical methodology, particularly for its estimation and imputation of missing data. Unlike other organizations that publish numerous technical reports concerning their surveys (i.e. National Center for Health Statistics, and the Agency for Health Care Policy and Research), the AHA provides only a terse one page methodological note in Hospital Statistics (American Hospital Association, 2002, p. xix). The note briefly informs that missing data for some variables (beds, bassinets, and facilities and services) from the annual survey are not estimated. Other variables (e.g. revenue, expenses, admissions, births, inpatient days, surgical operations, outpatient visits, and full-time-equivalent personnel) are estimated using statistical regression models. And all other variables are estimated using ratios derived from similar reporting hospitals. In order to understand these estimates, and their possible impact upon an analysis, a user must have much more detailed information on the AHA estimation and imputation procedures. Voluntary, membership surveys provide much important understanding about a competitive marketplace. Such surveys, however, have intrinsic flaws that must be carefully considered when using their data. Like all other voluntary surveys, the AHA’s annual survey from its inception has been an

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admirable effort to provide consistent and useful information for hospital professionals. But, it is voluntary and therefore is not ‘‘perfect.’’ It is critical to know its strengths and weaknesses in order to prevent distorted and inaccurate conclusions. Only with that knowledge can it be a truly valuable resource. References American Hospital Association (AHA) (2000), AHA Guide to the Health Care Field, AHA, Chicago, IL. American Hospital Association (AHA) (2002), Hospital Statistics, AHA, Chicago, IL. Ballard, P. (2001), Encyclopedia of Associations: National Organizations of the US, Vol. 1, Part 2, Gale Group, New York, NY. p. 12859. Mitchell, S., Spetz, J. and Seago, J. (2001/2002), ‘‘Errors in data on hospital ownership’’, Inquiry, Vol. 38 No. 4, Winter, pp. 437-8. Mullner, R., Greenspan, B. and Rafalski, E. (2002), Hospital Closures in the Chicago Area: 1950-2002, Sinai Health Systems, Chicago, IL.

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This summary has been provided to allow managers and executives a rapid appreciation of the content of the articles in this issue. Those with a particular interest in the topics covered may then read the articles in toto to take advantage of the more comprehensive description of the research undertaken and their results to get the full benefit of the material present

Executive summary and implications for managers and executives Good marketing results in better healthcare Enormous sums of money are spent on buying healthcare – Braunsberger and Gates set the scene, at least for the USA: . . . healthcare expenditures in 1991 totalled $671 billion . . . and rose to $1.3 trillion in 2000. Even though this increase appears to be impressive, healthcare expenditures as a percentage of the gross domestic product have been fairly stable at around 13 percent from 1992 to 2000.

To put this a different way, $13 of every $100 dollars earned by US citizens is spent on healthcare. There are few, if any industries, that can claim this degree of significance within the US economy. As we will see later, this figure is actual healthcare expenditure and excludes a vast expenditure on products and services that are, in truth, health related. A further context needs to be applied – the USA has a bigger healthcare sector than almost anywhere else and US citizens spend more on providing themselves with decent healthcare. For all its faults, the US ‘‘health service’’ is the biggest and most sophisticated in the world. The argument in the UK, for example, is round the best way for the Government to match continental European levels of healthcare spending at 8-10 per cent of GDP! Even in the USA, where health care provision is dominated by private concerns (both not-for-profit and for profit), we should note that the market for providing health care is dysfunctional. This imperfection results from the, quite proper, view that providing decent health provision is an important concern of government whether national or local. In the UK, this concern is reflected in a centralised, nationalised health service, elsewhere we see compulsory health insurance, complicated social security systems and other complicated and difficult combinations of private provision and state funding. No other market is more interfered with (except perhaps the defence industry) than healthcare for the simple fact that most people view the availability of medical and social care as a right. In some places this interference almost wholly negates the action of the market whereas in others (such as the USA) the market is constrained and limited by regulation and the considerable impact of state-funded provision. In this context, marketing becomes constrained and restricted and the practitioner negotiates the tangled path of regulatory requirements (often contradictory), the independence of the medical profession and the requirements of government whether regulatory or funding-related. US healthcare – an untypical system This special issue places most of its focus on the provision of healthcare in the USA. Applying the lessons drawn from the work must be treated cautiously since the US system of healthcare is unusual. Unlike most places the USA has a healthcare system that isn’t either directed centrally or subject to the domination of Government. This is not to say that the US system is outside the influence of Government – a significant proportion of the USA’s total healthcare expenditure comes in the form of payments directly or indirectly from the taxpayer. But it is to say that the provision of healthcare and the payment for healthcare are sufficiently separate for a reasonable approximation to a market to develop.

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Elsewhere the provision of healthcare is dominated by a culture of command and control within the national government dominating the funding and, in many cases, the organisation of the ‘‘health service’’. This special issue, concerned as it is with marketing (with a focus on the situation in the USA), cannot begin to address the wider public policy issues that surround healthcare. Suffice it to say that these issues remain and cannot be completely ignored when we consider the marketing of healthcare. In reviewing the work within this special issue, I intend to concentrate on the marketing issues raised, to avoid (so far as I can) any attempt to put right the failings of anybody’s healthcare system (my name is not Hilary!) and to try and transfer some of this learning to healthcare markets that are less free than that in the USA. In doing so there are a number of important points for debate and I hope to make some small contribution to this. .

Should doctors learn some marketing skills?

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If I pay for some healthcare does this give me any say in what I get?

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Why do doctors (and other people involved in providing healthcare) treat customers as unable to deal with information about medical issues? Or do they?

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Where is the focus – on using direct marketing to target healthcare intervention or on using regulation to hamper the targeting of individuals at risk?

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Are satisfied healthcare customers healthy or ill? Or both?

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Why do some satisfied customers still switch (not just a problem for healthcare providers)?

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Is healthcare about ’medical intervention’ or the promotion of healthy living? Should we pay any attention to the claims of advertisers of supposedly healthy products?

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Why is it that hospitals in the USA are reluctant to tell the whole truth about their performance? How does this contrast with the other extreme – hospital league tables?

All these questions, as well as some others, derive from reading the work in this special issue of JCM. It is interesting to note from the reading that there remains a significant dichotomy within the work between the marketers that focus on the prosaic concerns of customer retention, targeting and service quality and the actual service providers who (it seems) focus on sustaining a traditional relationship between the customer and the supplier of medical services. Would a marketing course help doctors do a better job? Paul, Handlin and Stanton report the findings from a survey of primary care physicians seeking their views about the advertising of prescription drugs directly to consumers by pharmaceutical companies. It is no surprise to find that doctors (or at least the primary care physicians surveyed) are less than keen on direct-to-consumer (DTC) advertising by drug companies. Two questions strike me at this point. Are doctors right to be concerned – is DTC advertising of prescription drugs a recipe for misinformation? Given that the doctor has to prescribe the drug, why should additional consumer information be a problem? 620

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In the first case there is plainly some justification for the concern expressed by doctors – drug companies are concerned to put across the most positive impression of their product and this can mean that the side effects of using a given prescription drug are played down by the advertiser. The role of advertising regulation becomes important here and it is significant that US regulatory controls (both self-regulation and statutory regulation) are weak and inconsistent. Better advertising regulation (of either type) would help to ameliorate the concerns expressed by medical professionals about the accuracy and/or completeness of information in DTC advertising of prescription drugs. However, doctors need also to recognise that the media is as significant an influence on consumer attitudes as advertising. Yet doctors appear less critical of secondary promotion of prescription drugs as a result of public relations activity. It is interesting to note that in Bhaskaran and Hardley’s article on foods with therapeutic claims, the media (TV especially) is very important in determining consumer attitudes to the health claims made by food manufacturers for their products. There is a problem here – the doctor/patient relationship is very important, yet too few doctors recognise that the way in which many consumers consume services (and healthcare is a service) has changed with the consumer becoming more critical and challenging. There is an expectation that the supplier will provide comprehensive and consumable information allowing the individual to make an informed purchase decision. The traditional doctor/patient relationship (seen as being threatened by DTC advertising) was too often characterised by the patient as supplicant since the doctor controlled all the information about the treatment of the patient’s condition. The mass media, advertising and the press have created a situation where the individual consumer can, if they so wish, gather a substantial body of knowledge about their physical condition – enough to question the decisions and recommendations of a doctor. Paul et al. report that doctors are uncomfortable with this situation. Indeed, we could suggest that this finding reflects the failure of the medical profession to recognise the evolution of the US consumer. These consumers are less willing to accept what’s offered at face value and more likely to inform themselves before seeking advice from the expert. All this suggests to me that doctors could use some basic marketing training it’s not just a question of getting a better ‘‘bedside manner’’ but securing a broader understanding of the consumer. It could be argued that the medical profession is uncomfortable with DTC advertising because it undermines their gatekeeper role in respect of drugs and provides the consumer with information about a drug (however flawed). Put bluntly, DTC advertising represents a power shift from doctor to patient and it is this that is undermining the doctor/patient relationship not the accuracy or otherwise of the DTC advertising. Nevertheless, the issue for the advertiser is less subtle. Doctors still represent a key gatekeeper – it is still a prescription drug. The drug companies cannot afford to alienate the doctor – especially where there are recognised alternatives to the drug being promoted. This means that advertisers of prescription drugs have a responsibility to be comprehensive about the information given to consumers and to set out the fact that drugs of the sort being advertised require the co-operation of doctors. Reducing the JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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power of the doctor – making the doctor/patient relationship more equitable – may be very desirable but it should not be done at the expense of being comprehensive and honest about the drug being advertised. Communicating with patients – an urgent concern for healthcare professionals If we are right to argue for greater understanding of marketing from doctors and others in healthcare provision, we need to consider what aspects of marketing are of greatest significance. Braunsberger and Gates, in looking at the drivers of patient satisfaction with healthcare and health plan, shed some light on where the marketing priority lies when they argue that: . . . to improve patient satisfaction you must improve the quality of the interactions with and services provided by physicians and their office staff.

The weakness in the healthcare marketing process lies in poor communications between the doctor and the patient. This isn’t about the doctors ’bedside manner’ (although this matters enormously) but about the wider issues relating to communication with the patient. If we get communications right we will affect levels of patient satisfaction. Such a change should create a virtuous circle since, as Braunsberger and Gates remark: . . . patients who are more satisfied are more likely to participate more actively and effectively in the medical care process and behave in ways that promote better health.

So what should doctors and their staff be doing? Some of the improvements lie in better systems – more timely communications, fewer inaccuracies and a fuller appreciation of the stressful situation in which most patients find themselves. But doctors should also consider improving the content of their communications. Braunsberger and Gates point out that patients are becoming more sophisticated, desire more control and demand a greater focus on their needs and wants. The doctor may know best but patients want to have more information about the doctors recommendations and this requires a more sensitive and comprehensive approach to communications. Doctors require a marketing and communications plan and, where they are associated with a HMO or other wider organisation, these organisations should commit themselves to providing marketing support. Healthcare organisation should not forget that the biggest driver of satisfaction or dissatisfaction is the doctor. Targeting healthcare using database marketing Some 12 years ago, I presented a marketing study to a UK area health authority that recommended (among other things) the use of geodemographic systems as a means of targeting health promotion messages more accurately. Since certain groups were clearly at greater risk than others, it made sense for us to target these at risk groups more directly. At this time the UK’s Health Service was uncomfortable with the idea of targeting in this way but since then the principle of directly reaching out to at risk groups has gained greater credence. Rafalski describes a related but more sophisticated approach employing data mining and data repository methods to target identified groups of patients. The example described, of obstetrics, shows how the use of sophisticated database marketing techniques and technologies can enable healthcare providers to identify weaknesses or breaks in a process. 622

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Rafalski notes the privacy concerns associated with the detailed analysis of medical or medical-related information and marketers in healthcare situations will have to proceed with caution. But the opportunities presented by database marketing – even where specifically medical data is excluded – are considerable both from the commercial perspective and from the viewpoint of promoting better public health. Indeed, it is in this latter area that the opportunities presented by database marketing are perhaps most significant. Whether it’s targeting groups at risk from conditions such as sickle cell anaemia or creating different messages targeted at different ‘‘lifestyles’’ the opportunity to make a significant impact on public health outcomes are considerable. Whether the systems within healthcare services are strong enough remains a major question and it is undoubtedly true that database marketing skills are lacking. A further opportunity – both in improving communications and in getting better targeting of healthcare messages – lies in the use of the Internet. These more sophisticated patients are, in addition to getting information from DTC advertising, the media and doctors themselves, making use of the Internet as a source of information. This information comes in the form of web sites set up by the drug manufacturers, online presence from medical providers themselves and from a growing number of special interest groups concerned with particular medical conditions. Self-help groups have long existed and, in many cases, have been seen as very positive by the medical profession. What the Internet has done is to give a new impetus to these organisations by enabling the wider dissemination of information and a greater sharing of experiences with different drugs and treatments. It is very important that doctors and healthcare managers are aware of these organisations since they represent another indication of growing patient interest in healthcare. Good health, happy patient – the drivers of satisfaction Braunsberger and Gates investigate the drivers of patient satisfaction with healthcare itself and health plans. I have already noted their most important finding – that it is the service we get from the doctor that matters more than anything else in determining satisfaction. I have also described how Braunsberger and Gates found that more satisfied patients take a greater interest in their individual healthcare. However, there were some other significant finds that merit examination – not least the impact of demographics and the individual’s actual state of health. Braunsberger and Gates report that: . . . healthier patients, older patients, males, those with a lower level of education, those who perceive system performance to be high and those with lower levels of system usage are more satisfied with their healthcare than their opposite counterparts.

Some of the ‘‘drivers’’ of satisfaction are more important than others and some drivers should be treated with a degree of caution. The fact that older people are more likely to be satisfied is less likely to be a factor of age itself but reflects improvements in healthcare provision over the past three or four decades. Older people relate their healthcare experiences today to experiences in the past and can be seen to be gaining satisfaction from the improvement over time rather than from the objective quality of current healthcare provision. JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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We also know from other markets that the ‘‘baby boomer’’ generation – being better educated and wealthier than their parents’ generation – are far more demanding of service quality. As this generation ages we may well see levels of satisfaction among older people declining. Similar contentions could be made for less well educated people (although their ‘‘trusting nature’’ is mirrored in other areas of consumer behaviour research) and men in general. In the latter case, the huge success of magazines focusing on men’s health suggests that younger men are becoming more concerned about their health than was the case in the past. Nevertheless, it remains the case that men are less likely to make use of medical services than women. In addition, some women might argue that, with a male dominated medical profession, men will receive a different kind of attention – especially when it comes to what are perceived as patronising attitudes. This leaves us to consider the finding that people with better health are more likely to be happy with the service they receive from doctors and other healthcare providers. Obviously there is a link between good health and satisfaction but this link – direct though it seems – need not be seen either as inevitable. Healthier people have fewer and simpler contacts with health services which reduces the opportunity for error, confusion or system failure. Which brings us back to the issue of systems and the imperative for healthcare providers to reduce error rates, eliminate confusion and improve the quality of communications with the patient. It also raises a concern that exists in other service sectors – whether measuring customer satisfaction alone is the best guide to understanding the behaviour of patients. Is satisfaction enough? Cooley reports on the development of loyalty strategies by one US health insurer. In examining the question of satisfaction, Cooley observes that: . . . Although many companies that had adopted customer satisfaction programmes saw increases in their satisfaction scores, they were still seeing customers leaving their business.

Cooley also reports that, for the insurer studied, supposedly satisfied customers were just as likely to switch to another insurer as other customers. Satisfied they may be but loyal they were not! The question here is to establish what factors make people stick or switch and to develop strategies that aim to increase the propensity for customers to remain loyal. The majority of customers are neither fickle nor very loyal. We have little involvement with our healthcare financing – like financial services we tend to assume that all the providers are much the same. Our decision is as much about price and the range of services as it is about our actual experience of health care. Indeed, many customers will be like me, paying out for health insurance but having made just one visit to the doctor in three years. Cooley’s argument is that health plans and insurers should focus more on the retention of current customers which requires several actions:

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Attention to the provision of service since we know that satisfaction derives primarily from the experience of healthcare provision.

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Added value services, information and a focus on well-being can all assist in keeping people within the scheme.

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Engagement and involvement of customers is important as is making accessing healthcare simpler and more user-friendly

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The same principles apply to healthcare marketing as apply elsewhere and Cooley describes how focusing on those customers who respond to additional attention links well with some of the management practices being used by clinicians and their managers. Cooley comments that consumers are ‘‘seeking a holistic approach, not just physical health but mental and spiritual health’’. This leads us to discuss some of the wider issues surrounding healthcare and, in particular, the issues researched by Bhaskaran and Hardley around foods with therapeutic claims. From healthcare to healthy living There is a view that the concentration on bio-medical intervention in Western medicine and healthcare has helped to create the ‘‘them and us’’ situation of professional arrogance and the dismissal of any therapies that do not use pharmacological or surgical intervention. Indeed, it has been argued that health promotion and the development of healthy living strategies have lost out to the detriment of all as a result of healthcare systems dominated by the traditional medical profession. Over the last two centuries the biggest improvements in health have come as a result of improved sanitation, clean water supplies, improved diet and the control of carrier animals such as mosquitoes. We could also cite better housing and improved education (especially of women). Set against these achievements is the development of mass immunisation, antibiotics and surgical technology. At this point we have to consider whether the next improvement is health will come from medicine or from the more general aspects of ‘‘healthy living’’ or well-being. Campaigns against smoking, the promotion of physical exercise (will we ever see a US president again who does not run?) and the encouragement of healthier diets. The challenge probably lies in dealing with the side-effects of prosperity and especially obesity and other eating-related conditions. All the evidence suggests that an increasing number of US citizens are seriously overweight – in too many cases to the point of obesity. Medicine can provide some help in addressing this problem but the real effort has to lie in changing people’s lifestyles. Healthy eating – the next healthcare revolution? Bhaskaran and Hardley report on an Australian study into public attitudes to the health claims made by food manufacturers. What becomes clear is that people want to believe the claims made but find it difficult to do so when those claims are unsubstantiated and made by the manufacturer. Nevertheless, this disbelief doesn’t stop people from buying the products making the health claim. We are, generally speaking, aware of the issues related to healthy eating – less fat, a good range of fruit and vegetables, fewer sweets and sugary drinks and avoiding eating between meals. At the same time we cheerfully ignore these and munch on a hamburger while slurping a large cola! Another concern that emerges from Bhaskaran and Hardley’s work is that consumers buy products labelled as low fat, light or low cholesterol but still eat too few green vegetables and lean meats (and for that matter too many cakes and biscuits). JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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Those charged with the promotion of health need to recognise that behavioural change comes about only slowly – it is 30 years and more since the link between smoking and cancer was first identified. Equally, we should recognise that I have the right to fill my face with junk food but that individuals who suffer health problems as a result of excess weight should expect to pay for the consequences of their indulgence in the same way that smokers and heavy drinkers do. Which brings us to the very vexed question of paying for healthcare. As many models as nations – all with their problems I said earlier that I did not intend to try and redesign anybody’s health system but we should consider how the sophisticated marketing of healthcare that is developing in the USA can be transferred to places with centralised, state-led systems of healthcare. I have already noted that the use of database marketing and other targeting tools in health promotion is long overdue. Just because these techniques were developed for application in the wicked world of private business doesn’t mean they cannot be put to use by those whose objectives do not involve the sale of products. Similarly, the improvements in communications between doctors and patients could prove as valuable in a wholly centralised, state-controlled system such as the UK’s National Health Service. In the UK, the idea of a general practitioner speaking (in any way) to his patients other than when they book an appointment does not seem to have occurred to doctors or managers. The only communication from my doctors’ in the last three years has been a badly spelled, photocopied letter that failed entirely to communicate to me the implications of the practice splitting into two and relocating. Also, the application of marketing techniques to the promotion of healthy living and the mistrust of commercial, ‘‘healthy living’’ messages are applicable wherever we go. It is true to say that the UK, Germany and Canada all have similar problems to the USA in terms of over-indulgence and obesity – strategies to respond to this problem should be shared regardless of the significant differences between the healthcare systems of these countries and in the source of funding for health promotion. Finally, and this is pertinent to the critical appraisal of the American Hospital Association’s Annual Survey of Hospitals, there is a need to share measurement, targets and public access to information about healthcare provision and its performance. In the UK, the Government has introduced a hospitals league table based on a range of measured criteria. The emphasis is on health outcomes and administrative efficiency - slightly confusing but more useful than incomplete data or information about inputs (staff, money, etc.) Healthcare marketing is not a threat to doctors or consumers Some people get very worried about the application of marketing techniques to something as sensitive as the provision of healthcare. However, this special issue makes clear that the role of marketing within the healthcare sector is, in general, benign. It is important that doctors and other medical professionals recognise the value that better marketing can bring to their jobs – especially in allowing for better informed and more responsive patients. 626

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Equally, and this is especially important where public policy issues are considered, the marketing of healthcare products and services is largely of benefit to consumers. As a result of less constrained advertising for drugs, consumers are aware of the choices in the marketplace – this doesn’t take away the ability of doctors to exercise clinical judgment but it does require them to justify and explain their choice of treatment. Better-informed, more involved patients are more likely to stay and, importantly, are more likely to take an active interest in their own health. It is this last benefit that derives from food marketing that should persuade the naysayers that investing in superior communications, good targeting and quality service is worthwhile for the patients’ health alone. (A pre´cis of the special issue ‘‘Health care marketing’’. Supplied by Marketing Consultants for Emerald.)

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Internet currency Edited by Dennis A. Pitta University of Baltimore

A source of protection against Internet fraud: the FTC Marketers in the entertainment industry are painfully aware of the cost of piracy. Their estimates of lost revenues are staggering. Executives in telecommunications industries are feeling the financial costs of pirates who can ‘‘clone’’ a cellular telephone’s unique identification and use it to run up huge bills, which cannot be collected. Consumers feel a different kind of pain. The Internet has become a potential trap for innocent consumers and a potential problem for the companies that serve them. There are some consumer watchdogs that assemble advice and information to help Internet surfers negotiate the cyberspace equivalents of Scylla and Charybdis. The Federal Trade Commission maintains an Internet fraud site, which is of value to both business and consumers. The Federal Trade Commission’s Consumer Protection Site [http://www.ftc.gov/bcp/menu-internet.htm] The FTC is located in the USA capital, Washington, DC. Its Consumer Protection Site offers information of relevance to both businesses and consumers. Visitors are greeted by an archive of specific Internet fraud topics and several different information modes. The site offers printed material in Adobe Acrobat (PDF) files as well as text format. In addition, there are one-minute MP3 audio files narrated by a Washington, DC based consumer affairs reporter for a local radio station. The archive is substantial, containing 45 consumer-focused topics and 17 e-commerce and business focused topics. They really represent only a part of the information. There are numerous items of staff opinions, testimonial evidence and archives of workshops and seminars. All of it is relevant to the growing battlefield of Internet fraud. Consumer topics What is impressive about the list of consumer topics is its breadth. They range from warnings about scams perpetrated via bulk email to schemes aimed at deceiving receivers. The material is described with attractive titles like, ‘‘FTC Names Its Dirty Dozen: 12 Scams Most Likely to Arrive Via Bulk Email.’’ That topic begins with an introduction; ‘‘Email boxes are filling up with more offers for business opportunities than any other kind of unsolicited commercial email. That’s a problem, according to the Federal Trade Commission, because many of these offers are scams.’’ It then goes on to convey the source of the information. Proactively, the FTC asked email users to forward their unsolicited commercial e-mail for evaluation. Its staff found that a majority of bulk email offers appeared to be fraudulent. The implication is that if consumers pursued them, they might cost unsuspecting individuals billions of dollars. The Dirty Dozen includes:

(1) business opportunities; (2) bulk email; (3) chain letters; (4) work-at-home schemes; (5) health and diet scams; (6) effortless income; (7) free goods; (8) investment opportunities; 628

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(9) cable descrambler kits; (10) guaranteed loans or credit, on easy terms; (11) credit repair; and (12) vacation prize promotions. There are clear descriptions of each scam. For example, the investment opportunity scam promises outrageously high rates of return with no risk. One version seeks investors to help form an offshore bank. Others are purposely vague about the nature of the investment, concentrating on the rates of return. ‘‘Many are Ponzi schemes, in which early investors are paid off with money contributed by later investors. This makes the early investors believe that the system actually works, and encourages them to invest even more.’’ The description is even more extensive and the scam, the fact that Ponzi schemes always collapse at the end, harming latecomers to the pyramid, is clearly outlined. Another popular topic, Internet con artists, is covered in the topic, ‘‘Dot con.’’ The issue is important because the Internet has spawned a whole new lexicon and brought the world to consumers’ homes, ‘‘24/7/365,’’ namely, all the time. Con artists have capitalized on the usefulness of the Internet for consumers and have used it to defraud consumers in a variety of clever ways. The material is fascinating. The site highlights windows of vulnerability that the scam artists exploit as they lurk, just a click away. There are other scams like exploiting Internet auctions to entice consumers into parting with their money then never delivering. It also cites the practice of applying new technology to promote the old business opportunity scams. A particularly effective practice is to use bulk email to entice large numbers of people with false promises about earnings through day trading or another business scheme. A relatively new and insidious practice is to offer consumers a free program like a viewer then hijacking consumers’ modems and cramming hefty long-distance charges onto their phone bills. The Dot.con material is encyclopedic in its coverage and a must visit for consumers who have Internet connections. With a bit of humor, the FTC promotes Dot.com stating that the police are on the ‘‘cyber-case.’’ It maintains a complaint server called, Consumer Sentinel, a consumer fraud database. Using complaints sent to Consumer Sentinel, ‘‘law enforcement officials have identified the top 10 dot cons facing consumers who surf the Internet, as well as many of the fraudsters behind them.’’ The use of the top 10 is highly reminiscent of the Federal Bureau of Investigation’s top 10 wanted criminals list. The similarity is intentional. The FTC has put many online con artists out of business. To protect unwary consumers, the Commission, wants them to know how not to be scammed. Each of the ten Dot.com scams are identified with three sections, one called the Bait, the second called the Catch (the scam), and a third called the Safety Net (a remedy). One of the scams, International Modem Dialing serves as a good example. The site identifies, ‘‘The Bait: Get free access to adult material . . . by downloading a ‘viewer’ or ‘dialer’ computer program.’’ It then explains the criminal activity, ‘‘The Catch: Consumers complained about exorbitant long-distance charges on their phone bill. Through the program, their modem is disconnected, then reconnected to the Internet through an international long-distance number.’’ Finally, it warns consumers how to avoid being a victim, ‘‘The Safety Net: Don’t download any program to access a so-called ‘free’ service without reading all the disclosures carefully for cost information.’’ It goes on to stress the importance of reading the phone bill carefully and challenging any charges that were not authorized. The FTC offers more general tips, like being wary of extravagant claims about performance or earnings potential. It cautions consumers to get all promises in writing and review them carefully before making a payment or signing a contract. Other tips should be common sense but are nonetheless helpful. B2B topics The site also has informational items that can help businesses conduct their operations without victimizing consumers or being victimized by the B2B scam JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

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artists. That archive is also impressive. The articles range from, ‘‘Advertising and Marketing on the Internet: The Rules of the Road,’’ to the FTC’s ‘‘Businessperson’s Guide to the Mail and Telephone Order Mdse Rule,’’ to others pertinent to the conduct of Internet business. Overall evaluation Spatial restrictions prohibit us from investigating each of the voluminous pieces of information. In summary, the FTC site is very helpful for both consumers and businesses. As criminals refine their methods, the website is structured to keep abreast of their techniques and provide advice somewhat analogous to the updated definitions provided by virus protection software. It also serves as a reference that businesses can use to keep within the rules. In our next issue, we will investigate other informative sites and invite readers to submit their favorite Internet sites for our consideration. Reader requests Please forward all requests to review innovative Internet sites to: Dr Dennis Pitta, University of Baltimore, 1420 North Charles Street, Baltimore, MD 21201-5779, USA. Alternatively, please send e-mail to: [email protected] for prompt attention.

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A note from the publisher

Forthcoming in 2003 Volume 20 will include a special issue on the topic of privacy versus personalisation. This issue will cover such topics as: .

New strategies for mining information as it pertains to developing effective one-to-one (consumer) marketing communications.

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Can we create effective consumer profiles without being too intrusive?

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Has the Internet really transformed global business in terms of our ability to collect personal data?

The full call for papers for this issue is available on the journal home page at www.emeraldinsight.com/journals/jcm/cfp.htm and the closing date for submission of articles is 1 June 2003. All relevant submissions will be welcomed for consideration by the Editor. The first issue of 2003 will contain articles covering the following topics; .

A ‘‘misplaced marketing’’ piece focusing on medical care marketing.

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A piece on consumer preferences for commercial Web site design.

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An examination of automobile lease versus finance motivational processes.

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An exploration of ‘‘Diderot unities’’ – the article attempts to draw links between products consumed in a group and which have an internal consistency based on lifestyle with ‘‘impulse purchases’’ as key departure products.

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An examination of children’s perception of their influence over purchases and the role of parental communication patterns.

The past 12 months have seen an excellent growth in the usage of the Emerald Fulltext database. In this time the database has been accessed over 20 million times, from which in excess of 5.5 million articles have been downloaded. Over 800 universities, corporate and public institutions now subscribe to the Fulltext database. Between September 2001 and September 2002 this journal has registered 125,315 article downloads (i.e. users accessing full text of articles on to their PCs These downloads have been registered from a total of 144 countries worldwide. During this period the top three articles in terms of usage were as follows: .

‘‘The boundaries of strategic corporate social responsibility’’, by Geoffrey P. Lantos (Book Reviews Editor for this journal). The article appeared in Vol. 18 No. 7 and has so far registered 2,028 downloads.

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‘‘The effects of brand associations on consumer response’’, by A. Belen del Rio, Rodolfo Vazquez and Victor Iglesias. This article appeared in Vol. 18 No. 5 and has so far registered 1,967 downloads.

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‘‘Customer loyalty strategies’’, by Dennis L. Duffy. This article appeared in Vol. 15 No. 5 and has so far registered 1,930 downloads.

As the Emerald database represents a living archive we would expect the number of downloads of these and all articles contained within the database to continue to grow for as long as the research remains pertinent to the field. Over the past 12 months we have initiated many changes at Emerald which we hope will be of benefit to our readers, our authors and, hopefully, our new authors. I would like to take this opportunity to highlight a summary of these enhancements: .

We have improved and expanded our authors resources Web sites (www.emeraldinsight.com/literaticlub). Here you will find no end of useful information on how to get published, your copyright rights, call for papers, Literati Awards, etc. We also have a new section called ‘‘Conference Central’’, which will continue to grow to be a one-stop shop to find the most relevant conference to attend.

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Our Research Register (www.emeraldinsight.com/researchregister/ index.htm) continues to grow. This is an online forum for the circulation of pre-publication information. By registering and broadcasting your current research activities you will gain exposure to potential collaborators and this will also put you in the spotlight with regard to Editors. It also informs our readers as to what is the cutting edge of current research.

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The managing editors at Emerald (myself included) have been running author workshops, both at international conferences and by invitation to university departments. These workshops provide an insight into the world of scholarly publishing and give advice to new authors on how to transform their research findings into publishable work. If you feel that this service would be of use to your department or conference, then please do get in touch with me via the e-mail address below.

Electronic access is available not just to subscribers to the Fulltext database but also to all individual subscribers. No matter when your subscription to the journal commenced, by logging on to the journal you will have access to the full journal archive. Richard Whitfield Managing Editor, Emerald [email protected]

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Alphabetical listing of authors and titles, Vol. 19, 2002

AUTHORS

Index

AGEE, T., see MARTIN, B.A.S BEATTY, S.E., see LEE, C.K.C. BENDALL-LYON, D. and POWER, T.L., The impact of gender differences on change in satisfaction over time, No. 1, pp. 12-23. BHASKARAN, S. and HARDLEY, F., Buyer beliefs, attitudes and behaviour: foods with therapeutic claims, No. 7, pp. 591-605. BHIMY, A.C., see MARTIN, B.A.S BRAUNSBERGER, K. and GATES, R.H., Patient-enrollee satisfaction with healthcare and health plan, No. 7, pp. 575-590. ¨ BBEN, H., Increasing margins by joining your customers, von CAMPENHAUSEN, C. and LU No. 6, pp. 514-523. CHOUDHURY, P., see CUI, G. CHUNG, K., see MULLNER, R. COOLEY, S., Loyalty strategy development using applied member-cohort segmentation, No. 7, pp. 550-563. COSENZA, R.M., see TAYLOR, S.L. CUI, G. and CHOUDHURY, P., Marketplace diversity and cost-effective marketing strategies, No. 1, pp. 54-73. D’AVRIA STANTON, A., see PAUL, D.P. DAVIS, S., Brand Asset Management2: how businesses can profit from the power of brand, No. 4, pp. 351-358. DAVIS, S., Implementing your BAM2 strategy: 11 steps to making your brand a more valuable business asset, No. 6, pp. 503-513. DAVIS, S. and HALLIGAN, C., Extending your brand by optimizing your customer relationship, No. 1, pp. 7-11. FORSYTHE, S., see KIM, J.-O. FOUCAULT, B.E. and SCHEUFELE, D.A., Web vs campus store? Why students buy textbooks online, No. 5, pp. 409-423. GATES, R.H., see BRAUNSBERGER, K. GORDON, G.L., see SCHOENBACHLER, D.D. GRAEFF, T.R. and HARMON, S., Collecting and using personal data: consumers’ awareness and concerns, No. 4, pp. 302-318. GU, Q., see KIM, J.-O. HALLIGAN, C., see DAVIS, S. HANDLIN, A., see PAUL, D.P. HARDLEY, F., see BHASKARAN, S. HARKER, D., see VOLKOV, M. HARKER, M., see VOLKOV, M. HARMON, S., see GRAEFF, T.R. HENRY, P., Systematic variation in purchase orientations across social classes, No. 5, pp. 424-438. JANDA, S., see TROCCHIA, P.J. KAUFMAN-SCARBOROUGH, C. and LINDQUIST, J.D., E-shopping in a multiple channel environment, No. 4, pp. 333-350. KIM, J.-O., FORSYTHE, S., GU, Q. and MOON, S.J., Cross-cultural consumer values, needs and purchase behavior, No. 6, pp. 481-502. KRANENDONK, C.J., see NICHOLLS, J.A.F. LANTOS, G.P., The ethicality of altruistic corporate social responsibility, No. 3, pp. 205-230. LEE, C.K.C. and BEATTY, S.E., Family structure and influence in family decision making, No. 1, pp. 24-41. LEPKOWSKA-WHITE, E., see PAGE, C. Li, F., see NICHOLLS, J.A.F. LINDQUIST, J.D., see KAUFMAN-SCARBOROUGH, C. ¨ BBEN, H., see von CAMPENHAUSEN, C. LU MARTIN, B.A.S., BHIMY, A.C. and AGEE, T., Infomercials and advertising effectiveness: an empirical study, No. 6, pp. 468-480. MOON, S.J., see KIM, J.-O. MULLNER, R. and CHUNG, K., The American Hospital Association’s Annual Survey of Hospitals: a critical appraisal, No. 7, pp. 614-617. NICHOLLS, J.A.F., Li, F., KRANENDONK, C.J. and ROSLOW, S., The seven year itch? Mall shoppers across time, No. 2, pp. 149-165.

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PAGE, C. and LEPKOWSKA-WHITE, E., Web equity: a framework for building consumer value in online companies, No. 3, pp. 231-248. PARKER, P., see ROWLANDS, I.H. PARSONS, A.G., Non-functional motives for online shoppers: why we click, No. 5, pp. 380-392. PAUL, D.P., HANDLIN, A. and D’AVRIA STANTON, A., Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years, No. 7, pp. 564-574. POWER, T.L., see BENDALL-LYON, D. RAFALSKI, E., Using data mining/data repository methods to identify marketing opportunities in health care, No. 7, pp. 607-612. ROSLOW, S., see NICHOLLS, J.A.F. ROTFELD, H.J., Misplaced marketing: ‘‘mine is the blue one on the left’’: function and dysfunction of pharmaceutical brand names, No. 5, pp. 377-379. ROTFELD, H.J., Misplaced marketing: the real reason for the real bad advertising, No. 4, pp. 299-301. ROTFELD, H.J., Misplaced marketing: the social harm of public service advertising, No. 6, pp. 465-467. ROTFELD, H.J., Misplaced marketing: training book for the new store clerk: ‘‘Go and be charming!’’, No. 3, pp. 185-187. ROWLANDS, I.H., PARKER, P. and SCOTT, D., Consumer perceptions of ‘‘green power’’, No. 2, pp. 112-129. SCHEUFELE, D.A., see FOUCAULT, B.E. SCHOENBACHLER, D.D. and GORDON, G.L., Multi-channel shopping: understanding what drives channel choice, No. 1, pp. 42-53. SCOTT, D., see ROWLANDS, I.H. SEATON, B., see SHEPHERD, P.L. SHEPHERD, P.L., TSALIKIS, J. and SEATON, B., An inquiry into the ethical perceptions of sub-cultural groups in the US: Hispanics versus Anglos, No. 2, pp. 130-148. TAN, B., Understanding consumer ethical decision making with respect to purchase of pirated software, No. 2, pp. 96-111. TAYLOR, S.L. and COSENZA, R.M., Profiling later aged female teens: mall shopping behavior and clothing choice, No. 5, pp. 393-408. TROCCHIA, P.J. and JANDA, S., An investigation of product purchase and subsequent nonconsumption, No. 3, pp. 188-204. TSALIKIS, J., see SHEPHERD, P.L. VOLKOV, M., HARKER, D. and HARKER, M., Complaint behaviour: a study of the differences between complainants about advertising in Australia and the population at large, No. 4, pp. 319-332. WILLIAMS, T.G., Social class influences on purchase evaluation criteria, No. 3, pp. 249-276.

TITLES

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(The) American Hospital Association’s Annual Survey of Hospitals: a critical appraisal, MULLNER, R. and CHUNG, K., No. 7, pp. 614-617. Brand Asset Management2: how businesses can profit from the power of brand, DAVIS, S., No. 4, pp. 351-358. Buyer beliefs, attitudes and behaviour: foods with therapeutic claims, BHASKARAN, S. and HARDLEY, F., No. 7, pp. 591-605. Collecting and using personal data: consumers’ awareness and concerns, GRAEFF, T.R. and HARMON, S., No. 4, pp. 302-318. Complaint behaviour: a study of the differences between complainants about advertising in Australia and the population at large, VOLKOV, M., HARKER, D. and HARKER, M., No. 4, pp. 319-332. Consumer perceptions of ‘‘green power’’, ROWLANDS, I.H., PARKER, P. and SCOTT, D., No. 2, pp. 112-129. Cross-cultural consumer values, needs and purchase behavior, KIM, J.-O., FORSYTHE, S., GU, Q. and MOON, S.J., No. 6, pp. 481-502. E-shopping in a multiple channel environment, KAUFMAN-SCARBOROUGH, C. and LINDQUIST, J.D., No. 4, pp. 333-350. (The) ethicality of altruistic corporate social responsibility, LANTOS, G.P., No. 3, pp. 205-230. Extending your brand by optimizing your customer relationship, DAVIS, S. and HALLIGAN, C., No. 1, pp. 7-11. Family structure and influence in family decision making, LEE, C.K.C. and BEATTY, S.E., No. 1, pp. 24-41. (The) impact of gender differences on change in satisfaction over time, BENDALL-LYON, D. and POWER, T.L., No. 1, pp. 12-23. Implementing your BAM2 strategy: 11 steps to making your brand a more valuable business asset, DAVIS, S., No. 6, pp. 503-513. ¨ BBEN, H., Increasing margins by joining your customers, von CAMPENHAUSEN, C. and LU No. 6, pp. 514-523. JOURNAL OF CONSUMER MARKETING, VOL. 19 NO. 7 2002

Infomercials and advertising effectiveness: an empirical study, MARTIN, B.A.S., BHIMY, A.C. and AGEE, T., No. 6, pp. 468-480. (An) inquiry into the ethical perceptions of sub-cultural groups in the US: Hispanics versus Anglos, SHEPHERD, P.L., TSALIKIS, J. and SEATON, B., No. 2, pp. 130-148. (An) investigation of product purchase and subsequent non-consumption, TROCCHIA, P.J. and JANDA, S., No. 3, pp. 188-204. Loyalty strategy development using applied member-cohert segmentation, COOLEY, S., No. 7, pp. 550-563. Marketplace diversity and cost-effective marketing strategies, CUI, G. and CHOUDHURY, P., No. 1, pp. 54-73. Misplaced marketing: ‘‘mine is the blue one on the left’’: function and dysfunction of pharmaceutical brand names, ROTFELD, H.J., No. 5, pp. 377-379. Misplaced marketing: the real reason for the real bad advertising, ROTFELD, H.J., No. 4, pp. 299-301. Misplaced marketing: the social harm of public service advertising, ROTFELD, H.J., No. 6, pp. 465-467. Misplaced marketing: training book for the new store clerk: ‘‘Go and be charming!’’, ROTFELD, H.J., No. 3, pp. 185-187. Multi-channel shopping: understanding what drives channel choice, SCHOENBACHLER, D.D. and GORDON, G.L., No. 1, pp. 42-53. Non-functional motives for online shoppers: why we click, PARSONS, A.G., No. 5, pp. 380-392. Patient-enrollee satisfaction with healthcare and health plan, BRAUNSBERGER, K. and GATES, R.H., No. 7, pp. 575-590. Primary care physicians’ attitudes toward direct-to-consumer advertising of prescription drugs: still crazy after all these years, PAUL, D.P., HANDLIN, A. and D’AVRIA STANTON, A., No. 7, pp. 564-574. Profiling later aged female teens: mall shopping behavior and clothing choice, TAYLOR, S.L. and COSENZA, R.M., No. 5, pp. 393-408. (The) seven year itch? Mall shoppers across time, NICHOLLS, J.A.F., Li, F., KRANENDONK, C.J. and ROSLOW, S., No. 2, pp. 149-165. Social class influences on purchase evaluation criteria, WILLIAMS, T.G., No. 3, pp. 249-276. Systematic variation in purchase orientations across social classes, HENRY, P., No. 5, pp. 424-438. Understanding consumer ethical decision making with respect to purchase of pirated software, TAN, B., No. 2, pp. 96-111. Using data mining/data repository methods to identify marketing opportunities in health care, RAFALSKI, E., No. 7, pp. 607-612. Web equity: a framework for building consumer value in online companies, PAGE, C. and LEPKOWSKA-WHITE, E., No. 3, pp. 231-248. Web vs campus store? Why students buy textbooks online, FOUCAULT, B.E. and SCHEUFELE, D.A., No.5, pp. 409-423.

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Call for papers Journal of Consumer Marketing – Vol. 20 Special issue on

Privacy versus personalization The Editor of The Journal of Consumer Marketing invites practitioners and academics to submit papers worthy of contribution to the literature for a special issue. Papers should provide practitioners and academics with new ideas and concepts and be written in the style of the journal. Where do we as marketers draw the line between anonymity and one-to-one communication? Globally, there is a definite concern by various governmental bodies that consumers’ rights to control the amount of information that is collected about them and how that information is to be used is one issue that must be addressed. This special issue will include papers on privacy versus personalization from an organization’s [marketing] perspective. With this perspective in mind, possible topics for coverage include, but are not necessarily limited to: . New strategies for mining information as it pertains to developing effective one-to-one [consumer] marketing communications. . The capability to correlate anonymous information obtained over the Internet with established databases. . Can determining ‘‘customer lifetime value’’ make a difference in a marketing strategy? .

Can the process of Customer Data Management (CDM) enable an organization to achieve greater returns on its customer centric business investments?

Can we create effective consumer profiles without being too intrusive? . Has the Internet really transformed global business in terms of our ability to collect personal data? . Can mass marketers effectively use one-to-one relationship marketing? .

.

How will the Telecommunications Act of 1996 further impair the use of customer proprietary network information?

Papers may be the result of empirical research, comprehensive literature reviews, case studies, business practices, or thoughtful analysis. However, to be accepted for publication, all papers must provide practical applications of material presented. Article length should not exceed 30 typewritten pages, although exceptions can be made. All material is reviewed on a double-blind basis by at least three reviewers. Full notes for contributors can be found on the journal homepage at http:// www.emeraldinsight. com.uk/jcm.htm Please send submissions (4 copies) to the Editor by 1 June 2003. Dr Richard C. Leventhal, The Journal of Consumer Marketing, 7678 Upham Street, Arvada, Colorado 80003, USA