Dissertation - Chapter 2

Tomorrow's leaders in health promotion are being educated at American University today.

CHAPTER II

THE REVIEW OF THE LITERATURE

Introduction to the Literature

The purpose of this study was to design a model health promotion informatic system that could lead to improvements in the health status and quality of life of Americans. The premise of this research project is that a state-of-the-art informatic system that features the world's best computing, information, and telecommunication technologies could be developed to influence the health behaviors and lifestyle choices of individuals. Moreover, the ground breaking work of some of the pioneers in this field has produced a substantial body of evidence to support a hypothesis that the efficiency of a model system would be superior to most of the traditional health programs (Dijkstra & DeVries, 1999; Kreuter et al., 1999; Orleans et al., 1999; Scientific Panel on Interactive Communication and Health, 1999; Strecher, 1999; Velicer et al., 1999; University of Wisconsin-Madison, 1998; Street et al., 1997; Harris et al., 1995). For example, historically, many of the most profound changes in health status and medicine have been directly attributable to advances in technology (Prochaska, 1997; McDonald, 1995). However, most health information system products that are currently on the market do not measure up to the standard that was proposed by Rhodes: "The most successful computer health promotion interventions will be those that are both theoretically and empirically grounded" (Rhodes, Fishbein, & Reis, 1997 p. 32). Often the inadequacies of these systems are related to incomplete or flawed designs that do not incorporate or reflect an awareness of the best science from all of the domains that are related to the problem (University of Wisconsin-Madison, 1998).

This chapter will feature a comprehensive review of the theoretical, methodological, and practical evidence that relates to the problem as well as the literature from fields where solutions might be found. The scope and depth of this review will be very broad in order to satisfy the diverse audience of readers who are interested in this topic. It will reflect the complexity and number of factors associated with the problem, the intricacies and sophistication of the technologies that are being looked to for solutions to address the problem, and the difficulties of designing a the model system that will encompass all of these factors.

The key issues, challenges, and problems will be highlighted through this discussion of the literature. The transdisciplinary review will include relevant findings from three domains: health promotion, informatics and the information sciences, and the behavioral sciences. Questions that are foremost in the minds of key constituencies and stakeholder groups such as developers, practitioners, researchers, providers, policy makers, and consumers will be explored. The research will be cited, reviewed, summarized, and critiqued in order to provide a clear picture of the evidence as it relates to the design, potential, and future for state-of-the-art health promoting technologies.

The review of the literature for this chapter is organized into five sections. The first section will focus on the basic health concepts and definitions, its context and the three major health models that were featured in Chapter I. An overview of some of the key behavioral change literature as it relates to health-promoting technologies is presented in the second section. Section three features a discussion of the fundamental principles and key elements of informatics, the information sciences, and modern telecommunication technology. The fourth section is a review of the literature that is related to design studies and mixed-methodology investigations. A summary of the literature is presented in the final section.

The Literature

The Basic Health Concepts and Definitions

The importance of health, well-being, and quality of life for Americans has been well documented in the literature. Health is unquestionably among the most important priorities for humankind (Koop, 1995). The value people assign to their health is indicated in two ways: first, people consistently rank health very highly when asked what is most important in their lives; second, individuals and institutions devote enormous amounts of time and money to the treatment or improvement and pursuit of good health. However, when scientists examine the literature and look at the actual behavior of people they often find discrepancies between what is needed to maintain good health and how a large portion of Americans live (Sobel, 1995; United States Department of Health and Human Services, 1995).

There is an enormous body of work in the literature covering all aspects of health and medicine. However, the literature is dominated by studies that are on the "downstream" or primarily disease management and treatment side of the medical continuum. The downstream side is associated with disease, morbidity, and mortality. The primary emphasis of those studies is devoted to downstream approaches for curing patients who already have medical conditions or to alleviating the suffering and pain that is associated with illnesses and disease. Some individuals refer to the preoccupation with the disease-related aspects of health as "sickcare" as opposed a more general view of "healthcare" (Health Enhancement Systems, 2000). This orientation is often referred to as the traditional medical or public health model (Herzlinger, 1997; Sobel, 1995).

In the sections below, most of the literature will reflect an alternative or "upstream" orientation toward health (Edington, 1997; Chapman, 1994). In this consumer or patient-centric approach, individuals assume a much greater responsibility for their health status by adopting habits and lifestyles that promote good health. This newer health model is commonly referred to as health promotion. Many health practitioners use health promotion in tandem with disease prevention (Downie, Fyfe, & Tannahill, 1994). The theories, themes, and issues from the literature that are related to and support this new upstream conceptualization of health and health promotion will be presented below.

A historical review of the literature reveals how much the concepts of health have changed over the last several centuries and how difficult it has been to arrive at a consensus on the way in which health should be defined and conceptualized today. In traditional curative medical models, health is often thought of as the absence of disease (O'Donnell, 1986a). However in the 20th century, several organizations have adopted newer models that are representative of a more comprehensive view of health. For example, in 1947 the World Health Organization (WHO) adopted the following definition that includes multiple dimensions of health: "health is a state of complete physical, mental, and social well-being and not merely the absence of disease or infirmity" (World Health Organization, 1951 p. 1).

Some of the health and medical models indicate that goals related to health, such as enhancing quality of life and attainment or advancement toward optimal health, are also important (Downie et al., 1994; Bowling, 1991). Increasingly, the medical, public health, and health education models are placing a greater emphasis on the role of the individual in their care. In theory, the relationship between practitioners and individuals is moving toward a partnership arrangement (O'Donnell, 1989).

In traditional curative medicine models, the manifestations of physical health were the primary criterion for outcome evaluations (Kulick & Kulick, 1991). Some mental aspects were treated, although not nearly as often as the physical manifestations of illness or disease. Today, expanded and alternative models include multiple dimensions of health such as physical, intellectual, emotional, social, environmental, and spiritual (Karch, 1987). These concepts are subsumed under the definitions and concepts of health promotion.

The Problem

There are volumes of references in the literature about the health status and qualify of life of Americans (Centers for Disease Control, 2000; Center for the Advancement of Health, 2000a; Chrvala & Bulger, 1999; United States Department of Health and Human Services, 1998). Because of the nature of this study, the health literature will be examined from three levels. The review of the literature will begin with the problems that are related to individual health status and quality of life that are determined by the behavior and lifestyle choices of individuals. Second, a brief review will cover the problems, impact, and implications of the health of individuals for groups and organizations. Third, the problems related to the achievement of the national health goals will be reviewed.

Individual Health Status and Lifestyle Choices

Many theories and models have been offered to explain why individuals develop negative habits and choose health-compromising lifestyles and behaviors instead of positive health behaviors. Excellent reviews and summaries of the historical development, current status, strengths, and critiques of the models are contained in texts by authorities such as Glanz, Downie, and O'Donnell (Glanz et al., 1996; Downie et al., 1994; O'Donnell, 1995). The health promotion models and the Transtheoretical model are among the most promising theories for helping individuals with behavior and lifestyle changes (Prochaska, Norcross, & DiClemente, 1995; Allen, 1997). Some of details and features of these two important models are reviewed in greater detail below.

For the last several centuries data on the health status and quality of life of Americans has been collected and reported in the literature. Today, the morbidity and mortality data can be found through a network of reliable and reputable sources including physicians, public health officials, and hospitals. The Centers for Disease Control (CDC), in conjunction with local and regional officials throughout the healthcare system, have developed an excellent surveillance system, an extensive national database, and a weekly reporting system (Centers for Disease Control, 2000). Accurate numbers for morbidity and mortality due to specific health and medical conditions as well as the statistical trends are available for the leading causes of death, disease, and infirmity. Although problems and errors in the data collecting and reporting systems still exist, these data have allowed researchers and practitioners to pinpoint the leading causes of death, disease, and illness and to implement programs and services to cure, prevent, or palliate the conditions and track trends and progress over time.

There are many staggering statistics in the literature that reflect the scope and magnitude of the problem. The five actual causes of death in 1997 were heart disease (726,974), malignant neuroplasms (539,571), cerebrovascular disease (159,791), chronic obstructive pulmonary diseases (109,029), and unintentional injuries (95,664) (Centers for Disease Control, 2000). However, as McGinnis pointed out, over 50% of the actual causes of death are related to health-compromising habits, behaviors, and lifestyle choices (McGinnis et al., 1993). For example, McGinnis estimated that the real causes of death that are directly attributable to lifestyle choices in 1990 were tobacco (400,000), diet/activity patterns (300,000), alcohol (100,000), microbial agents (90,000), and toxic agents (60,000) (McGinnis et al., 1995). When researchers and practitioners compare the difference between the real and actual cause of death, they can begin to understand how to best develop programs that will have the most impact on the health and quality of life of individuals in the United States (Strecher, 2000; Prochaska et al., 1995; Bouchard, Shepard, & Stephens, 1994; Dishman, 1994; Hahn et al., 1990).

In the 1980s the CDC, in order to align itself with the Healthy People 2000 initiative, established the Behavioral Risk Factor Surveillance System (BRFSS) to monitor the health risks of Americans (Centers for Disease Control, 2000). Annual data for the BRFSS is collected by most states on the incidence of the leading risk behaviors and key variables that were found to be closely related to health status, morbidity, and mortality. Tobacco use, lack of physical activity, poor nutrition, seat belt use, preventive screenings, and healthcare utilization are among the key health promotion data that are collected and analyzed. Fairly precise estimates of the rates of key health behaviors and trends are available through the BRFSS. Recently, a great deal of the data has become accessible on-line (Baker et al., 2000). The data from the BRFSS and other sources such the National Health and Nutrition Examination Survey (NHANES) are excellent repositories of information and research about the determinants and covariables of health behaviors, risk, and health status of Americans.

The economic cost related to the healthcare problem is also staggering. In 1998 the national healthcare expenditure was $1.1 trillion which was 13.5% of the gross domestic product (GDP). The total expenditure is expected to rise to $2.2 trillion by 20008 (Health Care Financing Agency, 2000 p. 1). These figures provide evidence about why all sectors of society should be concerned about healthcare. Moreover, with a 5.6% growth rate, and projections of double-digit increases, the economic side of the problem has been described as dire (Robert Wood Johnson Foundation, 1998 p. 11).

Groups and Organizations

Several studies in the literature have addressed the importance of the health status of individuals to groups and organizations (Center for the Advancement of Health, 2000b; United States Department of Health and Human Services, 1980). Groups and organizations range in size from small units such as families and neighborhoods, to larger entities such as businesses, schools, agencies, and communities. Factors such as productivity, healthcare costs, injury rates, lost work time, and quality of life, have been mentioned as reasons why groups and organizations are concerned with the health of their members (Chapman, 1997; Duhl, 1996; O'Donnell, 1989).

The government, universities, and foundations have sponsored several highly regarded longitudinal studies such as the Harvard Alumni, Institute for Aerobic Research, Stanford Five-Cities Project, Pawtucket Heart Health Program, and Minnesota Heart Health Program (Paffenbarger et al., 1994, Blair, 1994; Bouchard Shepard, & Stephens, 1993). These studies were designed gather baseline data and to improve the health status and quality of life of individuals in targeted communities through a variety of programming efforts and by creating environments that support healthy lifestyle choices. The studies that included interventions were based on prevention and health promotion models. The results have been equivocal or generally positive, but not overwhelming.

In the last decade many businesses have developed programs to improve the health and productivity of their workforce, to reduce the enormous burden caused by injured or sick workers, and to reduce the skyrocketing cost of healthcare. Today, employers are very extremely concerned about the safety and health problems of their workforce as evidenced by the following statistics. In 1994, 28% of all employees in the United States participated in employee-sponsored health promotion activities. However, by 1999 95% of the employers with 50 or more employees offered at least one health promotion activity (United States Department of Health and Human Services, 2000a).

Economists and researchers have made a strong case for linking the health-related lifestyle choices of individuals and cultures of organizations to economic reward packages and incentive schemes (United States Department of Health and Human Services, Centers for Disease Control and Prevention, 1999; Edington, 1997; Chapman, 1994). From an economic standpoint, there is ample justification for incentive systems that provide economic incentives and returns to individuals and organizations who try to influence and improve the lifestyle choices of individuals as well as develop healthier environments (Edington, Yen, & Ma, 1997; Chapman, 1997; Chenoweth, 1996).

School, church, institution, and community-based health promotion and prevention programs have been developed by organizations and entities to address the health problems of groups and constituencies. Local, regional, and state-wide networks, such as Health Cities, and the Interfaith Council, have targeted groups for general lifestyle improvement efforts as well as specific health campaigns (United States Department of Health and Human Services, 2000).

National Campaigns

In 1979, the Public Health Service published Healthy People 2000: The Surgeon General's Report on Health Promotion and Disease Prevention (Public Health Service, 1979). This landmark report set an agenda and outlined national goals and priorities for preventing unnecessary disease and disability and achieving a better quality of life for all Americans. The Healthy People 2000 project was initiated to provide a systematic coordinated national scheme for preventing disease in the United States. Moreover, the report stated that approaches based on health promotion principles have the greatest potential for achieving the national objectives. The success of the Healthy People campaign in achieving long-term population-wide lifestyle changes has been equivocal. Some of the goals such as seat belt use, worksite health promotion programs, and infrastructure and surveillance systems development have been reached, surpassed, or judged as successes (United States Department of Health and Human Services Public Health Service, 1995). However, progress in most of the areas has been disappointing and slow and many programs have been reevaluated (United States Department of Health and Human Services, 2000a; Department of Health and Human Services, 1997).

The Health Models

Three major health models that are relevant for this study were identified and discussed in Chapter I. Each of the three models has played a major role in the healthcare system in the United States. Excellent in-depth reviews, discussions, and comparisons of the models and their implications for the healthcare system are contained in articles and texts including those by Glanz, Prochaska, Herzlinger, Sobel, O'Donnell, and Downie. Additional points about some of the models and theories will be made below; however, the discussion has been kept superficial and only focused on a few main points since complete coverage is beyond the scope of this review. A more detailed discussion of the health promotion model is provided below.

Health Promotion Models and Concepts of Upstream Treatment

Health promotion concepts began to appear more frequently in the literature in the 1980s. Health promotion theory is based on the concept of pushing treatment upstream. The primary emphasis is not on treating disease. Upstream treatment emphasizes avoiding disease and infirmity by preempting its course and striving for high quality of life (Orleans et al., 1999).

O'Donnell provided one of the early working definitions of modern health promotion. His concept of wellness is based on the work of Travis who used a continuum to illustrate the range from death to optimal health. In 1986, O'Donnell offered the following definition: "health promotion is the science and art of helping people change their lifestyle toward a state of optimal health" (O'Donnell, 1986a p. 4).

Self-responsibility is a central theme in O'Donnell's conceptualization of health promotion. He stated that health promotion programs should be included at three levels awareness, lifestyle change, and environmental support. However, he indicated that not all people are ready for change and part of the awareness level is helping individuals get ready for change through a multi-step process (O'Donnell, 1986b).

In 1989, O'Donnell offered the following expanded definition,

Health promotion is the science and art of helping people change their lifestyle to move toward a state of optimal health. Optimal health is defined as a balance of physical, emotional, social, spiritual, and intellectual health. Lifestyle change can be facilitated through a combination of efforts to enhance awareness, change behavior, and create environments that support good health practices. Of the three, supportive environments will probably have the greatest impact in producing lasting change (O'Donnell, 1989 p. 5).

Some criticisms have been levied at O'Donnell's health promotion model in the literature. In 1986, O'Donnell agreed that his model is a conceptual model that has not been fully tested (O'Donnell, 1995). Others have suggested that it is too eclectic (Burton, Murphy, & Bennett, 1991).

Several other comprehensive multifaceted health promotion models that have incorporated the new approaches to behavioral change and healthcare are found in the literature. For example, the model by Downie, Fyfe, and Tannahill has received considerable notoriety internationally. Downie lists protection, prevention, and health education as the pillars of health promotion (Downie et al., 1994).

Maddux stated that health promotion interventions should be related to the goals of the program. He developed a typology for his model with three different approaches (Maddux, 1995). First, prevention is used to avoid, delay, or reduce the severity of diseases. Detection efforts such as screening and risk assessment are used to try to identify conditions early in the development cycle. Programs may also use a third approach - protection. The overall goal of each approach is to facilitate the behavioral change process.

Three important misconceptions or myths about the relationship between health, lifestyle, and how people view the process of treatment are found in the literature. The first misconception relates to a general misunderstanding about the relationship between health status and lifestyle. Several large population-wide studies have explored the relationship between cause of death, increased health risk, and lifestyle. In one of the most often cited studies on health, McGinnis concluded that 70% of chronic disease and illness were lifestyle related (McGinnis et al., 1995). Ainsworth stated "major contemporary chronic diseases and health problems appear to be associated with our modern habits of living, including low levels of physical activity" (Ainsworth, Montoye & Leon, 1994 p. 146). Therefore, by changing the health habits and lifestyle patterns of people, the cost in both human and economic terms due to this tragic state of affairs could be significantly reduced (Edington et al., 1997).

The second myth relates to a widely held misunderstanding about how much of an impact medicine and technology have on health-related conditions. Studies by the Centers for Disease Control (CDC) found that in our modern era of medicine, medical interventions only accounted for 11% of the reductions in the incidence of disease and illness or increased longevity in the United States (U.S. Department of Health and Human Services Public Health Service, 1995; Ratzan, 1994). Clearly, for much of the population there is great deal of over-reliance on medicine and medical technology for increasing longevity and improvements in quality of life (Strecher, 1997a).

The third area of research relates to the misconception of self-care. Sobel found that "80% of all conditions that are classified as health or medical conditions are first evaluated and treated at home" (Sobel, 1995 p. 238). The self-care research conducted by Sobel, Vickery, Kemper, and others provides strong support and a solid rationale for building and promoting systems by de-emphasizing the traditional provider-centric medical or health systems, replacing them with systems that are based on the principles of self-management (Goldstein et al., 1998; Kemper, Loring, & Mettler, 1993; Prochaska, 1992).

The implications of the three previously cited misconceptions reinforce the importance of rethinking how health and medical professions could and should be providing care. Clearly, the models found in the literature that are based on new approaches for changing lifestyle, health habits, and behavior must form the basis of modern methods of healthcare. Enormous benefits can be achieved and significant reductions in disease and illness can be realized through self-managing interventions that facilitate lifestyle changes.

In summary, there is strong support for the health promotion model and upstream treatment concepts in the literature. Many of the earlier misconceptions and myths attributed to the models have been addressed in previous studies. There is ample evidence to support the use of health promotion concepts in programs and services that are designed to help people make health-enhancing lifestyle changes. One of the most popular behavioral change models that emphasizes health promotion concepts is discussed below.

The Behavioral Change Literature

There is an abundance of research on all aspects of behavior change in the literature. Many of the theories for behavior change have been derived from the fields of psychology and sociology. A complete review of all of the major theories and constructs of these models is beyond the scope of this review. However, one model that has gained notoriety for its usefulness in explaining the behavior change process will be examined in greater detail below. In the last several years there have been numerous studies of the Transtheoretical model on populations of all sizes and demographic compositions for a variety of health-related problems. The Transtheoretical model and its constructs have been shown to be very compatible with the health promotion models.

The Transtheoretical Model

The Transtheoretical model (TM) is among the most popular, well-researched, and promising theories of behavior change (Samuelson, 1998; Marcus et al., 1992). The model grew out of Prochaska and DiClemente's research and understanding of the processes and fundamental concepts of self-directed change. Moreover, the TM is consistent with the principles of the health promotion theories.

A historical review of the literature reveals that the TM began as a descriptive theoretical model that was based on the work of Horn's earlier stage modeling (Horn, 1976). Prochaska and his colleagues used the model as a way to explain how patients changed in therapeutic interventions (McConnaughy et al., 1989). In Systems of Psychotherapy: A transtheoretical analysis, Prochaska identified the processes of change that were common among prominent therapeutic treatment theories (Prochaska, 1984). Prochaska and DiClemente tested the model and all of the components in a seminal series of studies on smoking cessation. Their work eventually expanded to include over a dozen other health-related areas (Prochaska, 1994; Prochaska et al., 1993).

All components of the model have been rigorously examined in the literature and they have exhibited strong psychometric properties (Samuelson, 1998). Recently, there has been a abundance of research that has documented the potential and applicability of the model for positive as well as negative health behaviors (Glanz et al., 1996; Prochaska et al., 1994).

Prochaska, like numbers of other health practitioners, concluded that interventions are often ineffective because too many health promotion programs are action-oriented, and, therefore, are not appropriate for 80% of the population (Prochaska, 1992 p. 1103). Moreover, he found that when interventions help people progress by even one stage, the long-term success rates increase dramatically and the chance of making changes in the future doubles (Messer, 1996).

Experts in health promotion acknowledge that most health promotion programs reach only the highly motivated and those who are already committed to healthy lifestyles (King, 1994). O'Donnell stated that the vast majority of the population, those who are not already overtly healthy, are not reached through programs that target the "low hanging fruit" (O'Donnell, 1986a). Prochaska believes that interventions will only achieve maximum effectiveness and reach when they are matched to the level of readiness and the unique blend of psychological and sociological characteristics and preferences for each individual (Prochaska, 1997).

Although the psychological processes are at the heart of the TM, from a practitioner's point of view, the most readily identifiable component of the model is the stage of change construct. Prochaska was able to identify which processes are most likely to be used during each stage. Several other components such as self-efficacy, decision balance, and temptations have been added to the original model. Together, the components form a comprehensive picture of the self-change process and they provide strong empirical support and predictive power for the model. Moreover, Prochaska found that the patterns and effect of the components of the model are remarkably consistent across 12 health and lifestyle behaviors (Prochaska et al., 1994).

Some criticisms of the TM are found in the literature. Davidson objected to the eclectic nature of the model. In fact, he called the model atheroetical (Davidson, 1991). Others such as Bandura and Heather have cited difficulties related to assigning a single discrete stage to a behavior that has many gradations. For example, Bandura maintains that "human functioning is simply too multifaceted and multidimensional to be categorized into a few discrete stages." Bandrua also stated, "On close inspection, the stages of change scheme violates every major requirement of a stage theory" (Bandura, 1997 p. 9). Heather said, "the model may have limited explanatory value, but high descriptive value." (Heather, 1991).

Prochaska concedes that the model can be considered descriptive, although he argues that it is robust, has strong psychometric properties, and that it meets all of the necessary theoretical model criteria (American Journal of Health Promotion, 1998). In addressing several of the challenges to the model, Prochaska states that many of the critiques are based on misconceptions and misrepresentations of the TM. For example, Prochaska points out that stage is not the model; it is merely a construct of the TM (Prochaska, 1997).

Tailoring

Although tailoring is not one of the core components of the TM, it is the method through which the model is operationalized. Psychologists, sociologists, and behavior scientists have developed theories and models and have conducted experiments in an attempt to predict, test, or determine the impact of certain traits or characteristics on behavior. The literature is full of current and popular theories or schools of thought such as behaviorism and social learning theory that attempt to explain the nuances of human behavior (Bandura, 1977; Rhodes et al., 1997; Skinner, 1972). Core constructs from these theories could be used to vary the content for the interventions instead of generating one type of content for all subjects. For example, some researchers suggest that the content of Webpages should be matched to the individual on the basis of whether they are primarily field dependent or field independent (Boyce, 1999).

Kreuter stated that there is an almost unlimited array of psychological or social characteristics and individual preferences that can be used as criterion for tailoring (Kreuter, 1996). The challenge for developers or designers of interventions and products is to make the right decisions about how sophisticated or granular the matching process will be. The tailoring process follows a series of steps in which the content or services are generated and matched to the unique set of preferences or characteristics for each individual. The basic assumption of tailoring is that, when content is matched to individuals, the chances of their remembering, reading, and acting on it are significantly enhanced (Strecher, 1997b). Many of the most promising applications of the model are focused on impacting the targeted behaviors rather than merely providing or trying to increase retention of information (Rhodes et al., 1997).

The concept of tailoring is a practical application and an extension of marketing research. Weiss popularized the application of market segmentation in the commercial sector (Forrester Research Group, 1998; Weiss, 1988). In 1994, Weiss added clustering concepts to his consumer profiling services for the entire population of the United States (Weiss, 1994). The Stanford Research Institute developed the SRI VALS as a process for identifying lifestyle patterns of individuals (Stanford Research Institute, 1998). The National Cancer Institute has been applying tailoring and market segmentation concepts in its health communications efforts (U.S. Department of Health and Human Services, National Cancer Institute/Office of Cancer Communications, 1998).

Several companies have been using segmentation and tailoring concepts on the Internet. Don Peppers and Martha Rogers have popularized concepts such as one-to-one marketing and customer relationship management for a variety of businesses (Peppers & Rogers, 1998). Recently, companies have been using sophisticated datamining techniques to predict the appeal of and then to deliver products based on population-wide sampling and collaborative techniques (Firefly, 1998; Studach, 1998).

Some health-related services use tailoring concepts. For example, Micromass has been tailoring personalized information for the Five-a-Day nutrition plan and the Committed Quitters program on the World Wide Web (WWW) for the past three years (Bulger, 1997). Strecher has developed a robust tailoring application that resides on networked interactive kiosks. Modules that are tailored for children are available for exercise, smoking, substance abuse, bicycle safety, and sunscreen use (Strecher, 1997b).

There is a great deal of confusion among many health practitioners about the application of matching and tailoring concepts (Kreuter, 1996). Kreuter uses a continuum to illustrate the differences between the approaches that manipulate some aspect of the content (Kreuter et al., 1999). At one end of the continuum is segmentation, or the dividing up of the target audience on the basis of some global characteristic such as geographical region, work place, or zip code. The second level is personalization, which varies the content on the basis of something more personally identifiable, such as name. A more sophisticated level uses matching on a single or a series of demographic or psychographic traits and characteristics. The most advanced systems use ipsitive techniques to produce dynamically tailored content during each interaction with the system (Bulger & Dukes, 2000; Strecher, 1999; Velicer, 1999).

In summary, Prochaska and his colleagues believe that the TM is the most effective way for individuals and health practitioners to achieve effective behavioral change. The full power of the TM becomes apparent at the application level when the concept of matching or tailoring interventions and content are implemented on the basis of factors such as the stage of readiness to change, psychographic characteristics, and preferences of the individual. Although the individual is still the primary agent of change, health practitioners and behavior change specialists can provide tailored programs and services to influence, accelerate, facilitate, or support the change process.

Informatics and Information Science

Today there are many pressing problems in our society and throughout the world. Individuals, communities, businesses, academic institutions, and governments are searching for creative and effective ways to address these problems. For several decades futurists and science fiction writers have suggested that the answer to most of these problems lie in the development and application of innovative technologies. However, only in the last decade of the 20th century have the computing and telecommunications industries converged, reached the level of critical mass, and become sufficiently mature to offer any realistic hope of addressing our most difficult problems.

The basic concepts and issues for the modern computing and telecommunications technologies are found throughout the information sciences literature. A review of some of the most important factors and characteristics that are germane to this study will be presented in this section.

Fundamental Principles of Informatics and Information and Telecommunication Technologies

Technology: Characteristics, Power, and Potential for Healthcare

The technology revolution has unquestionably been among the most profound developments for humankind since the Industrial Revolution (Negroponte, 1996; Toffler, 1990; Ofiesh, 1986; Bush, 1945). Collen stated that the "development of efficient communications between computers was as vital to the evolution of informatics as the computer itself" (Collen, 1999 p. 72).

The advancements and merger of the computing and telecommunications industries have revolutionized many aspects of our work and how we live (Gates, 1995; McDonald, 1995). Moreover, the pace of change as exemplified in Moore's, Metcalf's, Glider's, and Neilsen's laws is accelerating in every sector of the economy (Neilsen, 1998b; Ferguson, T., 1997; Kelly, 1997). In fact, the term "Internet years" was coined to represent the pace of change. New industries have capitalized on these advancements and now it is possible to look at the world and its problems in innovative and exciting new ways (Negroponte, 1996).

The potential and progress of the technology revolution have been well documented throughout the literature (Ernst & Young, 1997; Crawford, 1996). Many sectors of the economy have embraced computers and the communications-related technologies. For example, banking, commerce, retail, transportation, and many other areas have revolutionized or completely reengineered the way they do business as well as how they relate to their customers and consumers (Healthcare Information and Management Systems Society, 1998; Brown, 1997). However, the same type of enthusiasm or progress has not spread to the medical and health-related communities (Parr, 1996). Although there are pockets of innovation and demonstrations of amazing applications that will greatly benefit individuals and society, the healthcare sector as a whole has been among the latest and most reluctant of adopters of computer technology (Bergman, 1994). Raguhpathi estimates that "it is generally perceived that the health care industry's use of information technology is 10-15 years behind" other sectors of the economy (Raguhpathi, 1997 p. 81).

Defining technology is difficult for many people. Frequently practitioners think of technology only in terms of hardware and software. However, in a more general sense technology should also be conceptualized to include the knowledge, understanding, and awareness that is associated with the development and application of innovations in practical settings (Rogers, 1995). One useful way of thinking about technology is to view the physical part as the hardware and the knowledge components as the software. An understanding of both of these is necessary for a system to perform optimally. Moreover, the importance of the conceptual elements of technology should not be underestimated. Further, it is equally important to ensure that technology transfer is one of the goals of the development process and the diffusion of the interventions (Valente, 1995).

For this investigation health-related technologies are subsumed under the rubric of telehealth which Ratzan calls a new hybrid or "telecommunications for health" (Ratzan, 1998). Others favor a closely related but narrower concept of Interactive Health Communications (Scientific Panel on Interactive Communication and Health, 1999). The focus of the IT discussion will be primarily on computing and telecommunications that can benefit the general public. These programs and services can be dispensed in formal or traditional settings such as hospitals, medical offices, and clinics. However, since the informatic system that is envisioned for this study will more often be delivered in a non-clinical environment, the primary focus will be on the more informal or outpatient settings such as homes, worksites, personal offices, and libraries. The delivery appliances may include stand-alone or networked computers linked to the Internet, communication devises such as phones and pagers, or multimedia communication channels such as WebTV (Mossberg, 2000; Brennen & Strombom, 1998; Bulger, 1997; Dirkin, 1994). Artificial intelligence, expert systems, decision support systems, and speech recognition technology are featured in many of the more sophisticated systems (NII 2000 Steering Committee, 1996). These systems can supplement the services of health practitioners, act as surrogates of care, or provide powerful forms of social support (Friends of the National Library of Medicine, 1998; Boberg, et al., 1995; Orlandi, Dozier, & Marta, 1990).

Characteristics

Information scientists have identified many characteristics that make technology appealing to users in the new global information age. The ubiquitous, seamless, and powerful attributes of technology are particularly relevant to innovations and interventions in healthcare (Strecher, 1997b; Street et al., 1997). The degree of effectiveness of many of the most recently developed health-promoting technologies is dependent on how well these characteristics are incorporated into the systems and the capacity of the systems to match or adapt to the needs and preferences of the users (DeVries & Brug, 1999; Lefebvre et al., 1995).

Four of the most frequently mentioned, attractive, and important features of technology are its potential for empowering the user, its ability to erase the boundaries such as time and geography, its flexibility and transparency to the user, and the optimism that is ascribed to it by so many users (Gold, 1998; Gustafson et al., 1994). In Health Promotion and Interactive Technology, Rimal and Flora list multimodality, networkability, temporal flexibility, segmentation capability, interactivity, sensory vividness, modifiability, availability, cost, and ease of use as the most important components for health-promoting IT systems (Street et al., 1997). Several of these features, all of which are related to systems that allow for tailoring of content and information, are discussed in greater detail below.

For years many people have looked to technology as the latest form of the "magic bullet" (Petrosa & Gillespie, 1984). Although the overexuberance is not always warranted, the feeling of optimism that is attached to technology by individuals and organizations is a very important characteristic and it has a great deal to do with its progress and acceptance (Gold, 1997; Dede & Fontana, 1995). Many researchers have found the perceived value and receptivity of technology to be very high (Bock, Niaura, Fontes, & Bock, 1999; Boberg et al., 1997; Alemi, 1995). However, in Silicon Snake Oil, Stoll warned about the unrealistic expectations of technology (Stoll, 1995). Moreover, a strong case for using low-tech approaches has been made by experts such as Clark and Ferguson (Clark et al., 1997, Ferguson E, 1997).

The potential of technology seems limitless (Ball et al., 1990; Toffler, 1990). Every day new technology applications and advancements that will benefit mankind are featured in the media. Scientists and engineers have been able to connect several electronics domains such as computers and telecommunications. These symbiotic relationships have produced exponential benefits. Further, the merger of fields such as computing, telecommunication, and information science has significant implications for many areas of healthcare (American Medical Informatics Association, 1997).

One of the most profound attributes of technology is its enabling power (Kahn, 1997; Dillon & Morris, 1996). Programs, systems, and applications have been developed that allow the user to harness or exploit the power of the technology. The central concept of the enabling technologies is that it puts the user in control of these powerful technology tools.

Flexibility is s highly attractive attribute of technology (Street et al., 1997). The components of technology can be reprogrammed, reconfigured, or repurposed to respond to an amazing array of needs and in a variety of situations. For example, many businesses have benefited substantially from the ability of technology to integrate disparate parts of their operations. However, computer systems in healthcare could be described as "islands of information" (Crawford, 1996). Further, divisions, departments, and organizations along the supply chain have sought to resolve their feelings of isolation (Patrick & Koss, 1996).

Significant advantages that relate to the performance of computers over human beings have been often cited in the literature (Kelly & Reiss, 1998; Dillon et al., 1996). For example computers never get tired, don't take breaks or holidays, don't get sick, don't strike, don't have bad days, don't get distracted, and are easily replaced (Obradovich & Woods, 1996; Hettler, 1996). Computers can be programmed to be much more discriminating than humans in many areas, and they have miniscule error and mistake ratios. Many of these features make computers highly desirable throughout the healthcare arena.

There has been an ongoing debate about the characteristics and capacity of humans versus computers at the interface and intelligence levels. For expert systems, the "gold standard" for interface and intelligence is the Turing test, which states that the user should not be able to tell from the interface or the output whether they were interacting with a computer or a human (Turing, 1950). With the advent of sophisticated expert systems, artificial intelligence, smart systems, and neural networks, the "intellectual capacity" and "reasoning powers" of computers will be able to outperform humans in most categories (Knapik & Johnson, 1997; Girratano, 1998; Minsky, 1996; Bergman, 1994). Further, there is evidence in the literature documenting the advantages of the impersonal nature of a computer interface in some health-related areas including taking in sensitive and confidential information (DeVries, 1999; Yates, Wagner, & Suprenant, 1997; Skinner et al., 1993).

A final attribute that is important for individuals in highly developed and affluent countries is the ubiquitous nature of computers and technology (Pan American Health Organization, 1996). The 1997 US Census Bureau found that 47% of American households have access to a computer at home or at work while only 22% use the Internet. (United States Census Bureau, 1999 p. 40). However, in 1999, 60% of adults in the Washington, DC, area had internet access either at home or at work (Arbitron, 1999). Further, some entrepreneurs and companies have devised schemes that offer free computers and Internet access (Clark, 1999).

In a relatively short time, the Internet has become almost universally available through home, work or public access points (Aspden & Katz, 1998). Moreover, powerful economic and social drivers and trends in the developed countries point toward almost universal access in the 21st century (Brown, 1997; Cornish, 1981). WebTV, personal communication devices and appliances, and free computers will mean that anyone, anywhere, anytime can access information and services that will benefit his or her health at little or no cost (Corcoran, 1999; Ratzan, 1998; Street et al., 1997; Alemi et al., 1995; McDonald, 1995). In fact, according to the 2000 Pew Internet and American Life report fifty-two million American adults, or 55% of all Internet users have used the Web to access health or medical information (Fox & Rainie, 2000 p. 3).

This list of characteristics is not meant to be exhaustive. However, the fact that many of them are complementary and are imbedded in multiple technologies means that their synergistic effect is substantial. Toffler reminds us of "the neglected fact that big breakthroughs often come not from a single isolated technology but from imaginative juxtapositions or combinations of several of them" (Toffler, 1990, p. 126).

Issues

Several important issues, particularly those related to the slow adoption of technology by health professions, are worth highlighting. Many of these issues have implications at the individual and organizational level (Dewan & Lorenzi, 2000; Anderson, 1997; Street et al., 1997). Some of the salient issues that have been identified in the literature are mentioned below.

Information overload is an extremely important issue in the information age (MacDougall et al., 1994). For example, Clark noted that just as the amount of computing power is doubling every 18 months, so is the volume information in the world (Clark, 1999 p. 1). The Science Panel on Interactive Communication and Health mentions filtering and managing the plethora of data and information as a major issue for healthcare professionals as well as the general public (Eng et al., 1999).

A second set of concerns ranks among the top issues for practitioners as well as the public. These concerns include privacy, security, and confidentiality (Ziegler, 1999; Brown, 1997; Gustafson et al., 1994). Mishandling, unauthorized access, and control over electronic patient records are major concerns for health practitioners and the lay public (Fox et al., 2000; Buckovich, Rippen, & Rozen, 1999; IBM Global Services, 1999). For example, an expert panel found that 98% of those surveyed rated privacy, security, and access issues as essential policy issues (Health Summit Working Group, 1997).

The lack of adequate training and expertise in computers and informatics during medical school and in the health training curriculum is a major issue (Bergman, 1994; Randolfi, 1986). Training in the use of computers is a very low priority compared to other subject areas and it is often left up to the individual to learn or develop skills on his or her own (Ferguson, T., 1997; Randolfi, 1986). Moreover, the cost of training is a significant factor. For example, a recent Robert Wood Johnson report estimated that it would cost $50,000 to train each physician in the new clinical systems (Robert Wood Johnson Foundation, 2000 p. 2).

It is interesting to note that physicians were early adopters of telephones, they have high levels of disposable income, and are highly educated. However, they are among latest adopters of computer technology (Ferguson, 1998). In many ways this paradox is related to the doctors reluctance to give up their control as the sole or primary source of information for patient care (Detmer & Friedman, 1994). This factor, along with liability issues, is frequently mentioned as a major reason why physicians are unwilling to use e-mail or recommend resources on the Internet to their patients (Ferguson, T., 1997).

Rogers noted that there are relatively few champions of IT systems within the health and medical establishment. The shortage of zealots in these professions has severely hampered the diffusion of innovations in the health arena as well as diffusion among client and consumer population (Rogers, 1995). However, physicians and health practitioners are often besieged by multiple competing priorities. Time, training, and support is often not available for them to acquire skills or even experiment with the new technologies (Slack, 1999).

There are also a host of issues cited in the literature that relate to the products that have been developed for healthcare professionals. Many of the first generation designs lacked sufficient maturity. Several of the earlier designs were either bad, poorly conceptualized and designed, or created with minimal or inappropriate involvement of professionals who would use them (Dijkstra & DeVries, 1999; Gold, 1998; Anderson, 1997; Gustafson, Bosworth, Chewing, & Hawkins, 1987). More often than not, the products did not fit the style or the job requirements of the professionals who were designated to use them (Norico, 1989). Often systems were purchased and installed by managers or staff from the information systems departments with little or no input or enthusiasm on the part of the practitioners in the field (Anderson, 1997).

Fear is an important issue. Some individuals are technophobic (Anderson, 1992). Many individuals are slow to adopt technology because they fear that computers will make them redundant (Anderson, 1997). This fear extends to helping information scientists and developers with knowledge engineering and the next generation of computing devices (Covvey, Craven, & McAlister, 1985). However, a recent study on the attitudes and perceptions of information technology for mainstream workers found that workers were very favorable toward technology; they saw it as a big part of the future, and they didn't feel that technology was threatening their job security (Heldrich, 2000). Clearly, this is a complex issue.

In summary, many issues related to technology have become significant barriers and obstacles to the development, adoption, and the level of sustained use that is necessary to impact on health-related behaviors. Ideally, the elements mentioned above will be featured in the current best-of-the-breed systems and become incorporated or standard in the next generation of applications. Some of these elements will be presented in the next section. The discussion will focus on behavior change that can be promoted and facilitated by telehealth or health-promoting technology applications and systems.

Health-Promoting Technology Issues in Practical Applications

The discussion that follows will focus on a few of the major issues that are related to technologies that are based on health promotion concepts. Many of the factors to consider when developing or evaluating health-promoting technologies have been cited in the literature. For example, design and human factors principles including human-to-computer interaction and user-interface characteristics, diffusion of innovations, computer-facilitated social marketing, and sociodemographic variables are frequently mentioned as important factors in systems design (Chiasson, 1997; Gustafson, 1995; Andreasen, 1995; Chamberlain, 1994). However, because an in-depth critique of these factors is beyond the scope of this investigation, only a few have been included in this literature review.

Two prominent authorities in the field have explored access, use patterns, and threshold of use issues. Both Gustafson and Alemi found that when systems are designed properly, socioeconomic status, level of education, race, and gender were not significant predictors of use (Boberg et al., 1997; Alemi, 1996; Shackle & Richardson, 1991). Experience and expertise with technology was not as reliable predictor as were need and motivation, particularly when subjects were faced with health crises (Brennen et al., 1998; Sainfort et al., 1990).

Gustafson found a five-month threshold of use was necessary in order to achieve desired outcomes measures (Gustafson, Hawkins, et al., 1999). The total length of time, total number of sessions, and time between sessions were all found to be important variables. However, since their systems were often multifaceted, and the use and number of subjects who used the components varied greatly, direct correlation about use could not be established. Velicer found a dose-response relationship between use of an expert system and the amount of change (Velicer et al., 1999b).

Many interventions that are designed to change behavior rely heavily on health communications. The main principles of health communications are the same for campaigns aimed at mass audiences as well as individuals. The research in health communications is a very dynamic, eclectic, and comprehensive field. An extensive coverage of it is beyond the scope of this study. However, many of the principles for communication campaign and program design are similar and complementary to health promotion and the TM. Among the shared concepts and principles are matching the message and the preferred type of medium to the individual (National Cancer Institute, 1997; Maibach & Cotton, 1995).

Using another approach, others such as Norcross have looked at temporal elements. Norcross studied New Year's resolution pledges and the concept of "teachable moments" as motivation factors (Norcross, Ratzin, & Payne, 1989; Norcross & Vangarelli, 1989). Bouchard mentions seasonal changes as a key factor to consider when tailoring for exercise (Bouchard et al., 1994).

In summary, when designing health promoting technology systems it is important to consider factors from many different perspectives. A thorough understanding of the issues and how they interrelate is essential for people who have an interest in designing systems that are efficacious and that will have a maximum impact on a population-wide basis.

The Design Study Methodology and the Design Process

The goal of this study is to develop a design and conceptual framework for a state-of-the-art health promoting informatic system. Therefore, this portion of the discussion will focus primarily on the issues related to methodologies for design studies and the design process. Unfortunately there are relatively few citations for methodologies for design studies in the literature.

Several methodological and design options were found in the general research, information systems, design, and health informatics literature. Two important decision points about the design study methodology and the design process for this study emerged from the literature. First, the mixed-methodology approach that was featured in Advances in Mixed-Method Evaluation: The Challenges and Benefits of Integrating Diverse Paradigms is well suited for complex design studies (Greene & Caracelli, 1997). The second issue is related to the design processes and design development framework that is required for complex projects. After a review of the literature, it was clear that hybrid design processes are most suitable for complex projects. (Robertson & Robertson, 1999; Hocking, 1998; Alavi, 1984).

The Design Study Methodology

This discussion will begin with a definition of three words that will be at the heart of this study and the design process for the model health informatic system. First, Magrab defines design as "the process of converting information that characterizes the needs and requirements for a product into knowledge about that product and its implied processes" (Magrab, 1997 p. 1). In this study the model system will be conceptualized as the components, the characteristics of the system and the framework for the design of the system. Second, in The New World Dictionary, phrases such as "a standard of excellence, a pattern, a copy or imitation, a plan, a style or design, to serve as a model, a standard of excellence" are used to define the word model (Webster, 1970). Third, Webster defines a system as a "set or arrangement of things so related or connected as to form a unity or organic whole."

A thorough search of the literature found relatively few citations for methodologies that are appropriate for design studies. The majority of the studies follow the traditional research methodologies. Most of the design study references were from the fields of information systems and engineering. However, some authors have proposed innovative or hybrid approaches that are often needed or are most suitable for complex problems and new areas of study (Hocking, 1998; Friedman & Wyatt, 1997; Cooper & Press, 1995; Alavi, 1984). The most attractive feature of the hybrid designs is that they provide unique approaches for addressing problems that span several disciplines and do not fit neatly or cleanly into any single domain (Magrab, 1997).

This section will include a review of some of the issues and key elements of the design methodology. The most appropriate methodological roots for this type of investigation are found in the health or medical informatics literature (Collins, 1995). These methodologies generally evolved or were taken directly from fields of the information sciences (Sosa-Iudicissa et al., 1997).

The information systems design projects for the health and medical sectors have been confined to a relatively few areas. The field of health and medical informatics focuses almost exclusively on health and medically related problems. However, these fields are much less developed than the general informatics or information sciences (Collins, 1995).

Because of the complexity, breadth, and depth of the problems, systems, and solutions that are developed to address them, authorities in the informatics field often recommend mixed methodological approaches (Coiera, 1997; Alavi, 1984). In Evaluation Methods in Medical Informatics Friedman presents several traditional and hybrid methodologies that are appropriate for the design and evaluation of medical informatic systems (Friedman et al., 1997). The authors concluded that it is justifiable and often recommend that researchers include a variety of techniques in their research designs in order to gather qualitative data that will enhance the traditional quantitative techniques (Yin, 1994). However, currently there is no "gold standard" in medical informatics (Friedman et al., 1997). Alternative or supplemental designs that incorporate a mixture of methodologies such as case studies, correctional, comparative, planning, demonstration, and illuminative designs are useful for filling the gaps in this emerging field. Further, it has been noted that great care must be taken in the design and execution phases to avoid fragmented or poorly designed studies (Aday, 1996).

In Advances in Mixed-Method Evaluation Greene presents a strong case for studies that feature multiple levels of data gathering and analysis (Greene et al., 1997). The authors suggest that if the methods are complementary, appropriate for the problem, and can be meshed into a design, the integrity and validity of the study can be greatly enhanced. For example, by using multiple methods, researchers can enhance the integrity of their studies to achieve the type of "triangulation" that is a hallmark of case studies (Merram, 1988). The multiple forms of data collection allow for the representation and input from all of the relevant stakeholder groups. The inclusion of the worldview and perspectives from all of the key players, especially the prospective users of the systems, is a critical factor for the success of projects in the health and medical fields (Berners-Lee, 1999; Kolbe & Iverson, 1981).

Several issues and challenges that are related to mixed-methodology and hybrid designs have been raised in the literature. For example, methodologies and novel or non-traditional research designs that are outside the mainstream are often suspect or frequently challenged for their rigor and integrity (Gall et al., 1996). At times this is due to the newness of these designs which may also be a problem due to a lack of awareness. At other times it is due to the lack of attention to standards of experimental rigor that are ignored by researchers (Fowler, 1988). There is no universally accepted "gold standard" for the process overall (Center for the Advancement of Health, 2000a; Scientific Panel on Interactive Communication and Health, 1999). Another major issue within the research community is that some individuals are reluctant to accept the worth of studies from those who do not use traditional experimental methodologies (Yin, 1993).

A second major factor for mixed methodologies relates to achieving balance and the difficulties of pulling together and synthesizing the data from several experimental orientations. This issue is particularly important for studies that are more complex and those that lack well-defined boundaries (Greene, 1997).

In summary, there is strong support in the literature for research designs and methodologies that are dynamic, flexible, and appropriate for highly complex problems and systems. The task for the researcher is to formulate a design that matches the problem and the context in which it will be implemented (Merriman, 1998). The use of the best-of-the-breed concept is particularly appropriate for designing model systems (Dimancescu & Dwenger, 1996).

Principles of the Design Process

A variety of design principles, some of which are appropriate for this study, were found in the literature. Several of the principles are common among the information science, industrial design, and community health domains. Each of these three disciplines has important implications for the key aspects of a model health informatic system. A short list of four important design principles that will be featured in this study will be highlighted below. In some instances examples of how the principles are being used in health will be included.

The first design principle is related to the methodological approach and how the system is viewed in the context of addressing the problem. Often, systems fail because the designers have not performed a comprehensive and systematic analysis of the problem and the solution (Kendall et al., 1999). In fact, many systems designers do not perform the in-depth analysis of all of the internal and external factors, attributes, and drivers that impact on systems (Ball, 2000; Kaplan, 2000; Cooper, 1995). Further, they do not attempt to match problems and environments to the solutions that possess the characteristics necessary to ensure optimal success (Gustafson, 1997). A systems-thinking approach allows designers to more fully understand and resolve many of these issues from a macro or interdisciplinary perspective (Weinberg, 1975). The worth of the systems approach holds true for health entities at the organizational as well as the national and international level (Pan American Health Organization, 1997).

The second design principle, multi-level analysis with strategic planning, is closely related to the systems approach. Theorists have proposed many types of models that incorporate an analysis of the potential, cost, and impact of new or altered systems (Levin et al., 1992). Ideally, an analysis of the operational, managerial, and production levels should be conducted. Generally, the analysis includes an internal and external environmental scan and an assessment of key factors such as the strengths, weaknesses, opportunities, and threats (SWOT) of any change (Cooper, 1995; Englert, 1990; Karch, 1987). These techniques have been used by Gustafson to design multiple systems to address catastrophic health conditions (Gustfason et al., 1995).

A third principle that helps to ensure success for designing complex systems is supply-chain analysis. Systems designers look at each entity along the supply chain to assess the value and impact it has on the system. This analysis is essential for new systems as well as those that are being reengineered (Snodgrass et al., 1997). Many entities such as healthcare organizations and agencies such as the Koop Foundation are applying business process reengineering (BPR) concepts across the spectrum of healthcare in the United States (Koop Foundation, 1996; Hammer & Champy, 1993). Jones estimates that in the healthcare sectors 70% savings can be achieved by using BPR techniques (Jones, 2000; Tonnesen, 2000). Moynihan stated that the healthcare industry could save $125 million per week with standardized IT (Moynihan, 2000). Presidential candidate Bill Bradley stated that $250 billion could be saved every year by streamlining the system to avoid excess administrative costs and waste within the system (Bradley, 2000).

The fourth design principle deals with information technologies that span multiple domains or a "family of professions" (Cooper, 1995). Designing and modeling systems of various levels of complexity require skills and tacit knowledge from several domains. Systems engineers and software designers have become increasingly proficient in developing and prototyping information technology systems. However, the exceedingly high failure rate of 70% of projects systems from the conceptualization to implementation phase is evidence of the difficulties as well as the inexactness of the science in this field (Ball, 2000; Stair, 1995). Two problems, a lack of awareness or understanding of the organizational culture by the "outsiders" who are designing the systems and lack of proactive upper-echelon commitment and leadership, are the most prominent reasons for the failure of projects (Dewan & Lorenzi, 2000). The literature from projects in the healthcare field reveals similar trends, issues, and shortcomings (American Medical Informatics Association, 1998).

Although these design principles are drawn primarily from the information sciences, they are also found consistently across multiple domains. For example, many of the same systems thinking concepts are embedded in the Proceed/Preceed model for community health (Smedley, 2000; Kreuter, Farrell, Olevitch, & Brennan, 1999). In a collection of works from multiple design domains, Jacobson found that the principles were common across the industrial, engineering, and visual arts disciplines (Jacobson, 1999).

The Design Process

References to all aspects of the design process are found in the information sciences, industrial design, and engineering literature. The design process is fundamental to the information sciences and in this study. Important advances in the process and procedures for developing new systems and software or in reengineering ones that already exist have come about as a direct result of the proliferation of new technologies that have characterized the Information Age (Future of Health Technology Institute, 1999; Gamma et al., 1995). For complex systems, a key to this progress and a successful design process is being able to incorporate the design principles in ways that are reproducible, appropriate, and efficient for each design problem (Kendall et al., 1999; Alavi, 1984). Further, the design process must be able to incorporate all aspects of the modern computing, information, and telecommunications technologies (Berson, 1996). Several health technology visionaries are calling for the application of these key concepts in the healthcare arena (Bulger, 1997; Pan American Health Organization, 1997; Fitzmaurice, 1995; McDonald, 1995).

Three reasons that explain why the progress and efficiency of the science of systems design have improved were mentioned in the literature. First, the design processes have become more standardized, formalized, and mature (Stair, 1995). The standardized methodologies provide a structure and reliable step-by-step guidelines for designers and project engineers to follow throughout the design process. In fact, many designers use systems thinking concepts in the design process (Weinberg, 1975). Second, sophisticated and scalable yet affordable system and software design tools such as computer assisted software engineering (CASE) and computer-aided design (CAD) tools have been developed to support design teams in every stage of the design process (Kendall et al., 1999). Because of the complexity of information systems projects, it is often necessary to assemble teams of project and subject specialists who can apply their expertise to the problem or represent the stakeholders who will be using them. These teams are able to function efficiently because of the standardized methodologies, software tools, and distributed organizational and communications systems that have become synonymous with the Information Age (Quinn, 1997).

Since the 1960s several variations to the System Development Life Cycle model (SDLC) have been used for design projects throughout the information sciences (Kendall et al., 1999; Donaldson & Siegel, 1997). The different SDLC models have evolved, matured, and diffused throughout the industry. As the name implies, the SDLC is viewed as a cyclical process. There have been many derivatives of the first SDLC models. For example, Stair suggested a five-step model that includes the following steps: investigation, analysis, design, implementation, and maintenance and review (Stair, 1997). Some variations are modified for certain types of systems development projects, while other models such as the "waterfall" and spiral methods emphasize multiple iterations and feedback mechanisms throughout each of the stages (Kendall et al., 1999; Girratano et al., 1998). Several complementary design models and approaches are found in the industrial design and engineering literature (Cooper, 1995; Rosenau, 1990).

The phases of the seven-step SDLC model are listed below (Kendall et al., 1999).

Identifying the problems, opportunities, and objectives
Determining information the system requirements
Analyzing system needs
Designing the recommended system
Developing and documenting the system and processes
Testing, maintenance, and implementation
Evaluation and measurement

When appropriate, some types of projects will adapt the model and use only part of these steps or add others. For example, the SDLC would be modified to focus only on the first five steps in a design project.

A variety of models, frameworks, and techniques that have been used as alternatives or as supplements to the traditional design process models such as the SDLC are contained in the literature. For example, Robertson has developed a Volere requirements template that has been used to provide designers with greater detail at several key design stages (Robertson et al., 1999). Details about the Volere shell will be provided below.

Object-oriented (OO) modeling is one of the newer design methodologies that has received considerable attention in the literature (DeMarco, 2000; Gamma et al., 1995). It allows sophisticated systems to be built in parts that can be reused in other systems (Levin et al., 1992). Object-oriented modules and components are conceptualized as entities that may be created and then stored in libraries for later use by other systems. The attributes of the object are encapsulated and transferred with the object that is embedded in the new system. This modular approach is highly attractive to designers because it allows for a great deal of savings and flexibility in the systems design process. However, initially it adds a great deal of complexity to these systems (Stallings, 1998). The Koop Foundation has used the OO process in modeling the health informatics infrastructure (HII) (Ball, 2000; Koop Foundation, 1996).

Prototyping concepts that are featured in the systems development process for complex models are being mentioned more frequently in the design literature (Kendall et al., 1999; Alavi, 1984). Prototyping has several advantages over traditional lifecycle methods. For example, prototyping provides earlier feedback and promotes credibility among user groups (Schrage, 1999). It offers a tangible way for designers and users of systems to come to a common understanding of the feasibility and usability of a system by testing and using it before it becomes a final product or a fully developed system (Alavi, 1984). Prototyping is particularly useful for developing new and innovative systems such as information systems for healthcare (American Medical Informatics Association, 1998). Alavi noted that prototyping designs can be used effectively with the lifecycle models (Alavi, 1984).

The validity and worth of prototyping approaches has been well documented in the information sciences literature (Kendall et al., 1999; Schrage, 1999; Alavi, 1984). In order to reduce risk and speed up the development process for complex systems, design teams are often tasked with developing the systems as parts or components. These subsystems or modules are then tested for usability and performance standards. The feedback and measurements from these tests are used to improve the system design and to determine whether to go forward with or alter the project in some way.

The field of artificial intelligence (AI) has become an important part of the design process in several areas (Shortliffe, 1998; Barrett et al., 1988). It has added some remarkable theoretical and practical contributions to the field of systems design. Currently, AI techniques are being used in many ways including facilitating and improving the design process. The systems of the future will use AI processes and techniques and they will be embedded into systems that are self-reengineering, organizing, and learning (Epstein, 2000; Girratano et al., 1998). Experts in the field of health technology foresee a greatly expanded role for AI in a variety of systems (Intel, 2000; Bulger, 1997; Knapik et al., 1997; Dede et al., 1995).

The literature contains some important references to the art of the design process. Several authors such as Jones in Developments in Design Methodology point out that creative, intuitive, and interdisciplinary thinking are critical elements of the design process (Cross, 1984; Weinberg, 1975). Jones provides several examples of how important serendipity can be in the systems design process (Cross, 1984). Further, Quinn points out that over half of all innovations occur at the hands of users (Quinn, 1997). Leaders in the development of health technology systems such as Gustafson, who realize the importance of collaborative and creative thinking with the potential users of systems, have been able to develop systems that are in sync with their user populations (University of Wisconsin-Madison, 1998).

A variety of reasons were cited in the literature about why it is extremely difficult to forecast and therefore plan for development in the future of technology (Schwartz, Leyden, & Hyatt, 2000; Wake, 2000). It goes without saying that the accuracy of the forecasts in such a dynamic and volatile field is questionable. However, Alexander suggests that for model systems a master plan should project 30 years ahead (Cross, 1984). Several models such as the Fisher-Pry model offer ways to project the theoretical limits of technologies (Quinn, 1997). Chamberlain suggests that even though the lines between the technologies will continue to blur, and it is difficult to predict the rate of diffusion of technologies, it is important to project at least five years into the future for health-related systems designs (Chamberlain, 1994).

In summary, design methodologies such as the SDLC model provide a useful structure that designers can use as a starting point for technology-based projects. However, it is important that organizations assemble the right composition of members and talents into the design teams (Weinberg, 1986). Moreover the organization must provide the right culture and support that will allow the teams to accomplish their mission. The teams must customize the process to fit the problem and the needs of the users (Buchanan & Margolin, 1995; Rosenau, 1990). The modern software design tools and technologies can greatly enhance the efficiency and quality of the design process. Fortunately, some authors have pointed out that healthcare does not have to reinvent the wheel; it only needs to learn how adapt and use it to address its needs (Lee, 1997).

Selected Design Development Models and Frameworks

Several models, frameworks, and techniques were found in the information systems, industrial design, and engineering literature. These design elements may be used as stand-alone structures, as supplements to, or in conjunction with other methods. The Integrated Product Process and Design and Development (IP2D2) and the Volere Requirements Specification Template are two of the models that seem to be suitable for design studies (Robertson et al., 1999; Magrab, 1997).

Robertson offers the Volere framework as a structure for designers to use in the design development process (Robertson et al., 1999). The Volere shell and the requirements specification template are the two main elements of design development methodology. The product constraints, functional and non-functional requirements, and the project issues are the four elements of the template. The nine main elements of the Volere shell are requirements (type and event/use case), description, rationale, source, fit criterion, customer (satisfaction and dissatisfaction), dependencies, supporting materials, and history. This process has been used effectively in a variety of design projects (Robertson et al., 1999).

Summary

This chapter has included an extensive review of the health theories and technology and design concepts and issues from the literature. The review was performed in the context of designing a technology-based system for improving the health status and lifestyles choices of Americans. The problems, theories, and issues from the three domains of health promotion, information technology, and the social sciences were presented.

Kassirer, who is one of the advocates health informatics, reminds us that "ignoring the trends of technology makes us reactors to change instead of agents of change" (Kassirer, 1995 p. 6). Researchers must seek ways to develop and evaluate the complex concepts of behavioral change in simple ways through technology.

We are moving rapidly toward a world of "personal health valets" as envisioned by Szolovitz and his colleagues at MIT in 1994. Many development teams are "pushing the envelope." But it is equally important to validate the worth of these products in more controlled studies. Demonstration projects such as this one are needed for the development of ideal systems.

Link to Chapter 3.

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