Understand the development of trends leading to the evolution of the e-health paradigm shift
Recognize the emergence of mobile health care as a frontier of e-health systems and environments
Recognize the emergence of virtual reality as another frontier of e-health systems and environments
Articulate the concept of consumer-driven e-health systems
Specify the steps involved in generating performance-based, future-oriented e-health applications
Chart the future of e-health technologies and what humans can make of these technologies

Introduction

During the turn of this century, we have been and still are witnessing an electronic information and knowledge revolution that parallels and, in many respects, clearly surpasses the industrial revolution of the past millennium. Just as the industrial revolution and its social implications changed the way of life not only for workers but also for families, organizations, and communities, so will this knowledge diffusion affect workers, families, organizations, and communities. Where once railroads, motorways, and machinery contributed to building industrialized communities and brought great economic benefits to corporations situated on or linked to busy crossroads and prepared and willing to jump on the bandwagon, now growing electronic and wireless networks are providing similar competitive advantages to new forms of organizations, a new breed of knowledge workers, and a new generation of cross-disciplinary thinkers. All of these stakeholders are learning about the power of emerging e-technology and discovering new ways to harness the power of this awesome technology (see Chapter Fifteen).

Accordingly, the proliferation of electronic mail systems, the Internet, and the World Wide Web and the emergence of intranets and extranets, e-communities, e-medical and remote patient monitoring devices, and Web services, as well as the introduction of mobile technologies have generated new computing and network applications in health care. As discussed in Parts Two and Three of this text, e-health records and databases (Chapter Four), e-public health information systems (Chapter Five), e-networks (Chapter Six), e-rehabilitation (Chapter Seven), e-medicine (Chapter Eight), e-home care (Chapter Nine), e-diagnostic decision support (Chapter Ten) and e-health intelligent systems (Chapter Eleven) together have called for a significant expansion of knowledge and training among analysts, managers, practitioners, and researchers. Most critically, stakeholders need to understand the prospects of e-health care technologies for future growth and development amid emerging frontiers and applications and evolving health care systems and environments.

The traditional role of health management information systems is to provide administrators with automated solutions for routine transaction processing problems (Tan, 2001). Health management information systems were built to resolve generally isolated, well-structured departmental information processing needs. These systems diffused and proliferated in the late 1970s and the early 1980s. Their acceptance among health administrators and clinicians (for example, physicians and nurses) has now been widely and clearly documented in mainstream health informatics literature. In Tan with Sheps (1998), the focus shifted to health decision support systems as the next paradigm for computerized applications, with the concept of using computer models and knowledge-based systems to support managerial and clinical decision making. In this context, a health decision support system may be defined as “any computer-based intellectual mechanisms useful for supporting and augmenting organizational or system users' cognitive abilities and skills in making complex decisions via the application of a mix of data, models, and knowledge elements through interacting with a convenient (typically, graphical) interface” (Tan with Sheps, 1998, p. xvii).

The key feature that distinguishes health decision support systems from traditional health management information systems is the combined use of data, models, and knowledge elements to enhance and extend the perceptual and cognitive effectiveness of health administrators and clinical decision makers. This enhanced effectiveness is normally accomplished by extending the range and capability of managerial thinking and clinical problem-solving processes rather than merely providing a system for automating routine, programmable, and repetitive tasks or functions (Keen and Scott-Morton, 1978). Although this more advanced concept of automation was proposed as early as 1978 by Keen and Scott-Morton, its application to solving semistructured and higher-order health care decision problems was never fully appreciated until the late 1980s and the 1990s.

Today, as this text has emphasized, we are experiencing a further shift in the e-health care paradigm, in which information and communications technology is applied not only to assist individuals and organizations in solving routine and semistructured problems but also to network, educate, and even transform the health and well-being of individuals, groups, communities, and entire populations. Indeed, it now appears that transformation is now virtually the only constant in the evolving health care system.

This chapter focuses on the prospects and transformational role of e-health systems and how to go about designing and growing future-oriented applications of e-health technologies. I will first survey some emerging frontiers of e-health technologies and applications—namely, mobile health care and virtual reality. Both offer natural extensions of the concepts, domains, methodologies, and cases discussed throughout this text. These topics, along with areas such as nanotechnology in health care, are expected to be the subject of future textbooks in health computing.

To complete this chapter, I take a closer look at consumer-driven e-health systems from the perspective of generating future-oriented e-health applications. I discuss the analysis of end user information requirements to aid the reader in understanding traditional health care technology planning and design. I then argue that this traditional perspective is inadequate for prospecting and building consumer-driven, future-oriented e-health care information systems. Accordingly, I discuss a new accountability expectations framework in detail, to provide an understanding of the rationale and underlying process for evolving strategically relevant, performance-based, and consumer-oriented e-health systems. The goal is systems that will satisfy consumer requirements, both by developing successful interventions for change and by promoting the health and well-being of individuals, families, groups, organizations, communities, and populations.

Mobile Health Care

Mobile computing has been touted by many industries as the next frontier. Apparently, this trend will include health care, although the development of mobile health is expected take longer than developments in other fields because of familiar concerns about standards, security, privacy, and confidentiality of e-patient data (see Part Four, particularly Chapter Fourteen; Tan, Wen, and Gyires, 2003).

Nonetheless, the transition and transformation from traditional computing technology and methodology to a wireless platform is already happening in many of our routine work and leisure activities. Hence, it is only a matter of time before this transformation moves into the realm of health care. The benefits for mobile health will be significant, given that immediate data capture and retrieval will become convenient when specialists, physicians, dentists, pharmacists, nurses, nurses' aides, public health professionals, and home health care workers all begin using wireless-enabled personal data assistants (PDAs).

Many executives today have converted to a mobile platform, making schedules, writing memos, engaging in complex analysis, listening to music, creating alerts and alarms, and e-mailing via BlackBerries, Palm Pilots, iPods, advanced pagers, cell phones, and other handheld devices. These handhelds provide a very convenient platform for generating future-oriented applications in health care. For example, both Pocket PCs and Palm Pilots are currently being tested and used for e-prescribing, capturing charges (e-billing), on-line research, e-book resources and references, e-patient education, e-clinical tools, and real-time retrieval of daily scheduling information.

Mobile Health Clinical Applications

Not only is wireless computing changing the lives of e-health stakeholders, but its effects are also becoming evident on a global and extraterrestrial scale. News articles about medical breakthroughs describe how e-medicine can be transmitted to the North and South Poles and even to outer space, providing e-care services to astronauts on the space shuttle. When one begins to fathom the countless possibilities that mobile computing technology opens up, the result is a growing stream of future applications and opportunities for scientific advances in almost every imaginable occupation. With regard to future-oriented e-patient care, the following list of ideas is only a sampling of the ways in which handheld technology can transform patient-caregiver interactions and provide instantaneous improvements.

Automated alerts: using cell phones, pagers, and handheld devices to alert patients about doctor's appointments, or remind patients of scheduled medication, vitamins or supplements, self-administered blood sugar tests, walking and stretching exercises, or e-mail prompts for messages from e-providers or home health care personnel.
E-diagnosis: using e-diagnostic decision support software to input patient symptoms and verify diagnoses using a clinical protocol reference database; obtaining information to support the practice of evidence-based medicine.
E-patient safety and error reduction: using automated functions to calculate correct dosages and reduce the possibility of dosage errors; to graph and chart medication consumption for e-care monitoring; to flag errors in e-health records due to captured inputs that do not make sense, for example, spelling errors and missing information; and to ease the transmission of patient self-reports by beaming patient input on drug reactions from one device to another, thereby offering immediate alerts in case of errors.
E-patient monitoring and tracking: recording information such as vital signs, medical history, prescriptions, allergies, and patient laboratory data at the point of care and updating patient records as care is administered or as soon as possible; immediately after patient information has been updated, the information can be transmitted between devices and synchronized with network computers for review by caregivers and e-providers.
E-referencing: providing reference-based information to e-consumers on various aspects of health care and services and to e-providers, including evidence-based medicine and clinical care protocols as well as information resources such as e-directories of prescription drugs, referrals, and experts.
E-prescriptions: transmitting prescription orders directly to pharmacies and using specialized software programs to reduce error by automatically checking drug interactions and eliminating errors due to misreading of physical handwriting.

In order for a wireless personal computer (PC) or Palm to be used for medical purposes, a nurse or physician must register the handheld with some support services such as ePhysician, an e-information service model in support of physician's office daily workflow and problems founded by Dr. Stuart Weisman. Registration is accomplished on the first synchronization with ePhysician, which is compatible with over fifty practice management system (PMS) software. Following registration, data stored in the PMS database, which include items such as provider information, patient demographics, insurance information, and appointments, are imported on a scheduled basis into the ePhysician remote database by way of the Patient Data Exchange program.

One application of this kind of wireless technology is an e-prescription system. With the elimination of handwriting, a physician can send an e-prescription order directly to the pharmacy, where encryption programs allow fast and inexpensive verification of the credentials of the prescribing physician. A prescription software package such as ePad requires the provider to customize the drugs, pharmacies, and formulary information that appear on both the handheld and the communicating PC. The selected medications, pharmacies, and formulary information, in tandem with the patient identification information (name, appointment, and demographic information) are then transferred to the handheld unit each time the PC is synchronized with the handheld where data is also transferred from the handheld to the PC. The key benefit of an e-prescription system is therefore the elimination of potential medication errors due to human transcription and increased efficiency and accuracy in the dispensing of medication and refills.

Besides clinical applications, mobile health encompasses health administration applications.

Mobile Health Administration Applications

Wireless technology can also be used to lighten the load for health administration processes and procedures. Again, the following list is just a sample of the many possibilities:

E-billing and e-charge capture: a direct method of efficient, accurate, and concise billing, including automatic billing and electronic capture of charges. This increases the reliability and accuracy of data transfer from the point of care to the official records, speeding up business transactions.
E-messaging: giving doctors, nurses, aides, and other caregivers continual access to remotely located e-patients and e-provider colleagues through wireless technology.
E-credentialing: securely verifying the integrity of caregivers' credentials by means of encryption programs.
E-recording: capturing treatment records and other measurements electronically at the point of care, for automatic updating of network computers in a timely fashion, thus drastically reducing the possibility of error and increasing patient safety.
E-tasking: taking advantage of the portability of handhelds to monitor personal information such as appointments and prescheduled meetings. Reminders and other documentation can be dispatched automatically via e-mail.

Mobile Health Delivery Systems

EPocrates Rx Pro, a popular PDA program for e-prescription services, is an example of a mobile health delivery system. Information is available for each drug, including dosage recommendations, administration routes, cautions, typical patient reactions, drug interactions, metabolism information, retail costs, manufacturer, safety data, and recalls. EPocrates Rx Pro will also recommend alternative and substitute drugs, particularly when a patient's formulary does not cover the initial option; this is known as e-prescription referencing. Multicheck, another useful feature of the Rx module, evaluates two or more drugs and compiles a list of drug interactions.

The SUNY Upstate Medical University, located in Syracuse, New York, has been educating students to become qualified physicians for over 160 years. The university comprises the medical center with a teaching hospital, a Level 1 trauma center, a burn unit, the Center for Evidence-Based Practice, many specialty clinics, and an expanding biomedical research facility. Dr. R. Eugene Bailey of the SUNY Medical University, uses his PDA an average of two dozen times per day for a “variety of reasons…. [Uses include] teaching students, diagnosing illnesses, determining treatment, prescribing medication, determining drug interactions, calculating dosages, and performing all necessary steps that are involved with quality patient care without the concern restraints on physical location and proximity to the subjects.” Bailey goes on to point out that his PDA allows him to conveniently review various articles and current events in the medical field through publications such as Drug News Weekly and DrugLink, a monthly newsletter that provides abstracts of drug-related articles from a good selection of journals. Like Dr. Bailey, many physicians are shifting to wireless computing applications, a trend that is especially appealing to the younger generation of trained doctors and nurses.

In addition to the wireless devices of mobile health care, other new technologies are being applied in the medical sciences—for example, virtual reality, sound waves, voice recognition and other advanced interface technologies, gene therapy, and nanotechnology. Due to the newness of some of the other technologies, the focus in the next section will be on virtual reality, a future-oriented e-health application that is already making a difference in fear therapy, among other uses.

Virtual Reality in Health Care

Virtual reality (VR) has been employed for years, particularly in entertainment and design modeling, but it has only recently been applied to health care. According to Strickland, Hodges, North, and Weghorst (1997), VR uses one of several modeling languages to create imaginary environments, or virtual environments (VEs), which permit real-time, user-controlled actions. VEs are computer-presented visions that give the feeling of another place. The user is given a head-mounted device, which projects a VE and eliminates any background noise (interference from “real reality”), effectively fooling the mind into believing the images are real. The user's hands may be free to move around or may have a remote control that allows redirection of movements through the VE. The user's actions are tracked, so that the environment can constantly readjust in order to interact as the real world would. For example, in its bid for the 2008 Olympics, the city of Toronto, Canada, used VR software to create the sight and feel of a new city landscape. The judges could be ushered into a VE to see different parts of the city from the sky as if they were flying over the city.

Virtual reality technology offers new and promising opportunities in every field, not just health care. However, it is especially suitable for enhancing the teaching and delivery of health care because of its ability to realistically simulate real-life situations and environments. Users are able to perform or practice complex tasks and challenging procedures without taking a lot of risk. In the Toronto VR example, city redesigns can be tested before the city is actually rebuilt to welcome the Olympics. In health care, the stakes are even higher than they are in an Olympic bid, because care providers are dealing with human lives and well-being. In such a field, the riskfree practice available through VR technology is invaluable.

Many VR applications are in the early stages of experimentation. VR has been carving out niches in particular health care areas, especially those that have not been adequately addressed by traditional medical science, including medical education, surgery, mental health, and rehabilitation.

Virtual Reality in Medical Education and Surgical Intervention

Telerobotic and telepresence surgery are examples of VR applications. Whereas the former entails the virtual control and use of remote surgical instruments, someone else other than the surgeon, who is not physically present, may manipulate the surgical instruments locally in the latter. In any case, these surgical interventions are performed with the aid of satellite communications where surgeons in a remote location perform procedures on a virtual image of the patient. A telerobotic prostatic biopsy on a human patient has been accurately performed. Although past results have been satisfactory, it is believed that further improvement in the technological architecture can reduce overall time delays while improving the time consistency between and within scheduled surgeries, thus greatly enhancing the technique.

Surgical Simulator, a stylized replica of a human abdomen with several essential organs, allows surgeons and residents to practice surgeries in a VE and predicts outcomes far more accurately and with very reduced risk compared with real-life practice. For example, the use of the virtual scalpel, clamps, and staples on these visualized organs can be varied, and the short-term or long-term consequences for various surgical interventions can then be assessed. This is a particularly safe environment for training new surgeons.

Three-dimensional (3-D) visualization of anatomy is yet another VR application. With 3-D visualization, not only is the surgeon able to visualize the intended procedure more accurately, but the technology is able to scale, rotate, reposition, overlap, and reconstruct images that have been previously scanned and stored digitally into specialized equipment such as a Picture Archiving Communication System (PACS). Oyama and others (1997) report that 3-D visualization offers new breakthroughs for cancer research, diagnosis, and treatment. For example, VR software enables estimates of cancer invasion to surrounding organs based on virtual cancer images of individual patients. The software can be used to help explain procedures and findings to cancer patients in order to obtain their informed consent. 3-D visualization can also be combined with other VR techniques to simulate complicated surgeries. Satava (1995a) notes that in difficult brain tumor operations, for example, MRI scans of the patient's tumor can be fused with video images of the patient's actual brain, allowing a previously impossible level of precision in X-ray vision, especially when the tumor is implanted in the brain tissue. With 3-D visualization, the next generation of medical students will be able to learn anatomy, not from a textbook with overlapping transparencies, but by exploring organs inside and out through manipulation of 3-D images (Satava, 1995b). Use of 3-D visualization tools coupled with interactive modeling (which allow the users to participate actively) allows dentists to better understand jaw articulation, while simulation of jaw movements helps dentists to deal with complex contact points and observe the actual functioning of the human jaws, thereby learning how to better treat their patients.

VR offers special needs educators a novel means of interacting with some of their hardest-to-reach students—for example, those with Down's syndrome and autism. The Learning in Virtual Environments (LIVE) program is the product of a network of researchers working together to develop tools for severely learning-disabled people. In this instance, users are exposed to virtual activities that simulate real life scenarios such as riding on a plane or shopping at a market to give them a feel of what can happen in real life activities. LIVE has been used to teach Makaton symbols, a language system used by children with a wide range of learning disabilities. VR provides new hope for success in an area in which traditional educational strategies and tools have generally failed.

Finally, VR can be used in hazard simulations—for example, in a simulation of a terrorist attack. In the real world, we cannot summon hazardous events at will, yet there is a need to prepare and plan effective mitigating steps (Mitchell, 1997). VR software can be combined with geographical information systems to simulate rescue operations for terrorist attacks (see Chapter Five). A VE allows first responders to practice novel and creative mitigation steps that might otherwise remain untried. Imagine too how VR can be applied to prepare military personnel for warfare against terrorists and for rescue missions to recover injured soldiers. All of these can be performed safely in a VE, and the skills learned have been found to translate well into real life (Inman, Loge, and Leavens, 1997).

Virtual Reality in Phobia Therapy

Acrophobia (fear of heights) can be a debilitating phobia. People with acrophobia avoid heights whenever possible, and this can interfere with their daily activities and routines. Therapy often takes the form of exposing these victims to varying heights in order to decrease their level of anxiety. Traditional therapy entails placing the victims in increasingly threatening real-life situations (in vivo exposure), controlling the exposure periods. VR effectiveness studies conducted on acrophobia treatment show that besides being safer and less embarrassing, exposure therapy in a VR environment had better outcomes than the traditional approach (Strickland, Hodges, North, and Weghorst, 1997).

Similarly, VR treatment for fear of flying offers many advantages compared to the traditional approach. Virtual flights taken by patients can achieve the same clinical outcome as actual flights. In a virtual flight passenger simulation, the patient can look out the window and see the changing ground and sky scenes. Such VR therapy has been shown to be as effective as in vivo exposure, at a significantly reduced cost (Rothbaum and others, 1996). Whereas the cost of actual airline tickets for patients and therapists are quite prohibitive, initial investment in VR hardware and software can be spread over many patients for years, making VR therapy possible for many more people.

Treatment for fear of spiders and other insects has also been attempted via VR exposure. Victims can expose themselves to increasingly frightening situations in the VE until their anxiety gradually decreases. Realistic virtual exposure can be achieved not only with virtual spiders but also with the tactile enhancement of large fuzzy plastic spiders (Carlin, Hoffman, and Weghorst, 1997). Other phobias treatable with VR therapy include fear of driving, fear of public speaking, and agoraphobia, which is the fear of being helpless in an inescapable situation—such as being trapped inside a burning building or being caught in rising floods. Agoraphobia often causes a person to avoid spaces or situations associated with anxiety. Many studies in VR therapy for phobias such as fear of public speaking and agoraphobia have produced remarkable results. More studies are being done, but VR therapy for phobias will likely become a growth industry.

Body image disturbances, which are believed to lead to eating disorders, have also been very difficult to treat with traditional therapies. A virtual environment offers a novel way for users to receive therapy, because it requires the user to pass tests and to perform tasks. These tasks must be completed in order for the patient to advance to the next level or to get into the next room. For example, they may have to eat something, weigh themselves, or choose which body image among many simulated versions best represents their true body size. Other symptoms—such as pain, insomnia, fatigue syndrome, and feelings of hate and anger—can all be treated in innovative ways with VR applications that use VE scenarios. Imagine taking a virtual cable car up a virtual mountain to ski; such an experience might teach you how to ski, help overcome your fear of heights and skiing, or even relieve the stress of your daily work and activities. It may also provide opportunity to those who will never have the possibility of performing the same activities physically due to impairments or other reasons. This brings us to the next topic on virtual reality in rehabilitation.

Virtual Reality in Rehabilitation

Rehabilitation may be the area in which VR will have the most impact and bring about the greatest transformation in human living. Not only do VR technology promise to make the blind “see” and help the paraplegic “walk,” but we have yet to fathom the limits of this technology in related areas (Max and Burke, 1997). In a simulated VE, disabled people can safely engage in all kinds of activities and be relatively free of the limitations imposed by their disabilities. Moreover, there is evidence that skills learned in a VE are transferable to the real world. For example, disabled people can practice navigating their wheelchairs in dangerous situations. Owing to the limitations of current technologies, there is, of course, a trade-off between performance observed within the simulated system and in real life. Even so, research has shown that driving skills of those who may have impairments or are learners and are being trained increase as a function of time spent in VR (Inman, Loge, and Leavens, 1997). Moreover, VR therapy promotes compliance by making the entire rehabilitative process more enjoyable, motivational, and appealing (Bowman, 1997).

DataGlove and WristSystem technologies, which measure human movements, have been discussed and illustrated in Greenleaf (1997). These technologies are being used by occupational and rehabilitation medicine specialists, ergonomists, industrial safety managers, biomechanical researchers, and risk management consultants to study physical movements of patients undergoing rehabilitation. When worn during normal daily tasks, for example, these gloves (and wrist systems attached at the end of the gloves) measure how long the wrist, hand, and arm are positioned at specific angles; they also measure maximum, minimum, and mean wrist angles. Such information can then be usefully applied to study and help patient overcome poor ergonomics such as challenges faced with Carpal Tunnel Syndrome. VR-based rehabilitative workstations simulate occupational tasks as well as tasks of daily living. VR technologies can also help people with vocal impairments communicate. Computer mapping of hand movements in the GloveTalker, for example, can permit one who previously would have been locked inside oneself to convey more complex ideas.

Physical rehabilitation has obvious VR applications, but VR can also reach people with specific attention and movement disorders. Paradoxical walking or the diminished ability to walk voluntarily is a condition suffered by patients with Parkinson's disease. The difficulty of walking can be overcome if only stationary objects can be placed along the walk paths. VEs can be used in presenting the virtual images to the nondominant eye and scrolling the objects toward the subject along a virtual ground plane. Perception of the objects stabilizes appropriately as the subject walks over them. The VE can create images of such stationary objects with the use of special glasses and can superimpose these images onto the real environment, enabling people with paradoxical walking disorder to walk again (Weghorst, 1997). Attention deficit disorder and visual impairments are other domains in which VR rehabilitation is believed to be effective as the VR provides users with visual cues of objects in the surrounding space (Wann, Rushton, Smyth, and Jones, 1997).

Recovery from a stroke is often rapid during the first few weeks but normally plateaus before full functionality is reached. Traditional therapy often helps to prevent an early plateau, but it is hoped that VR therapy can help patients achieve a higher level of functionality as a result of gradual exposure and safe training experimental treatments. VR systems can either be used alone or as a complementary treatment modality alongside traditional treatment. The criteria, of course, should be whether value is added to the rehabilitation process, therefore justifying the required capital investment and technical expertise needed to set up VR therapy.

Trade-Offs in Virtual Reality Therapies

Although VR offers many opportunities in the treatment of otherwise difficult-to-treat conditions, some possible risks to patient health and safety must be considered. For example, people who suffer from migraines are believed to be susceptible to adverse physiological effects from VR. VR machines may be prone to errors such as creating visual distortions, which may induce hallucinations or exacerbate symptoms of existing mental illness. Such possible adverse effects need to be monitored and evaluated when applying VR therapies. Because patients are unaware of their real physical environment during VR therapy, attention should also be paid to physical environments so as to avoid possible trauma caused by accidents.

Owing to the effects of VR on the vestibular system or the body's sensors for movement, some patients experience motion sickness (“cybersickness”), while others suffer from a small epileptic event (“flicker vertigo”) following their VR exposure. Stanney and Kennedy (1997) suggest that cybersickness may be reduced by providing the user with an optimal level of user-initiated control over their movements in the virtual world. Results from their VR studies indicated that VEs tend to produce fewer oculomotor-related (O) disturbances, such as eyestrain and more disorientation (D) than neuronegative (N) symptoms, such as nausea (Stanney and Kennedy, 1997). Hence, in order to ensure safety, VR patients and users should allow for recovery time before engaging in risky psychomotor activities such as operating motor vehicles.

The exact causes of cybersickness and other VR aftereffects such as flicker vertigo are not fully understood. While there are standards for binocular image alignment, there are no tolerance standards for the amount of dynamic mismatch the visual system can tolerate in terms of either convergence or focus. Eyestrain caused by a poor quality head-mounted device (HMD) or ocular alignment is better understood. Design of the HMD may result in a dynamic mismatch with the user's visual system. Enforcing specific standards to limit the amount of dynamic mismatch may reduce the eyestrain. Viire (1997) suggests that the standards established for eyeglass prescriptions would be a practical place to begin specifying HMD design standards.

Light source and noise levels are other considerations in ensuring the safety of VR therapies. Because lighting from many VR systems shines directly at the user's eyes, the light levels must be safe. Moreover, some VR systems use potentially dangerous sources of light such as lasers, which can damage eyes. VEs can produce loud noises at close range, which can also pose risks to users. Fortunately, existing standards for safe sound levels can be applied, and the effects of sound exposure at various decibels can be controlled and managed properly.

The next section covers a critical topic that can pave the way for the future success of e-health systems—that is, what must happen to generate future-oriented, performance-based e-health systems that satisfy consumer and user requirements and expectations.

Consumer-Driven E-Health Systems

With active and increasing grassroots participation from consumers and community groups, e-health may soon become a household word. Whether health organizations like it or not, and regardless of what the major insurers may try in order to stop health care reform, consumers and payers such as employers and third parties (for example, the government) will continue to play major roles in determining the future of health care, particularly e-health care. Advocates of consumer-driven health care systems argue for a transformation in the current system that will ultimately allow consumers to decide for themselves how they are going to pay for health care. Employers, on the other hand, are also taking the initiative in order to get the most out of the money they spend on employee health care. Major manufacturing firms such as General Motors, Ford, and Chrysler need to ensure that health care costs are sufficiently contained in order to stay profitable. Similarly, the government is always trying to find the best formulas to help keep a lid on the escalating costs of health care.

With these trends, we will be seeing some drastic changes in the way health care will be financed in the future. Many consumers are already turning to alternative modalities such as integrative medicine, preventive medicine and therapies, and e-health. One financing suggestion is that the premiums paid for health care go into a savings account until health services are rendered. Other schemes include ensuring that the services meet the requirements and expectations of the consumers and the employers based on needs and priorities. Some employers are even demanding that cost-saving services such as e-prescriptions be instituted as the norm, regardless of employee preference. The U.S. government and government-funded research agencies have been studying the financing of health care costs, legislation on security and privacy of patient records, health care technology assessment issues, challenges to the quality and safety of health care services, and managed care schemes.

Hence, we are beginning to see some real changes emerging in health care and e-health care. Put simply, if insurers and other traditional health organizations continue to turn a blind eye to changing trends in health care and a deaf ear to the new generation of informed and Internet-savvy consumers, these organizations may soon be replaced by emerging competitors who are responsive to the demands and requirements of consumers and employers.

Analyzing User Information Requirements

In light of changing trends and paradigm shifts in our health care system, we close this chapter with a discussion of how to understand user information requirements (IRs), which is basic to any systems development. Information requirements affect how a system designer or developer elicits and specifies the relevant, useful information that is expected to be available from an information system (IS).

In health systems development, the problem of having data without useful or meaningful information is usually the result of having too much rather than too little information. This problem is especially pervasive in e-health applications because massive amounts of data are often collected, accumulated, and then presented to serve many different purposes. Moreover, the data are often gathered from a variety of sources without a good rationale or adequate planning. Instead, data gathering can be motivated by reporting needs or sometimes by fear of potential requests for more information from diverse e-stakeholders (for example, the government, e-health providers, e-payers, e-patient advocacy groups, and users, who include e-consumers, managers, directors, and referring clinicians).

Data collected for a particular use may not be transferable or even relevant for other uses. Informational needs vary in focus and volume according to the type and level of planning and decision making that is to be undertaken (Tan, 1995). For example, strategic planning typically requires the integration of external and internal data sources, whereas routine operations concentrate mainly on internal data sources. There often is a lack of clarity as to the relevance of the data collected to meet user IRs. Even so, it is obvious that when inadequate planning or attention is given to user IRs at the beginning of the system development cycle, the resulting information system will likely be irrelevant, leading rapidly to its disuse and obsolescence. This happens because users or decision makers who interface with the system will not benefit if the system cannot deliver the information they need or want.

Notwithstanding, the process of analyzing user IRs is complex and poorly understood or enforced in everyday practice. As a result, many systems provide poor or inadequate support to users. Conceptually, the traditional process for analyzing user IRs can be configured as a three-stage framework, as shown in Figure 16.1.

At the conceptualization stage, which is closest to the real-world representation, the context for modeling is the actual environment in which empirical problems and needs are observed and interpreted. Conceptualization is the point where empirical reality is gradually translated into mental models and concepts, which are then articulated as key system design ideas and elements. The representation of these elements (or entities) and their interrelationships is necessarily complex because these are often the byproducts of the interplay of many poorly defined variables, including legal, cultural, socioeconomic, political, environmental, technological, and epidemiological variables. These variables are frequently difficult, if not impossible, to define operationally. In fact, their meanings and interrelationships are often the subject of multiple interpretations that depend on a manager's or an analyst's view of the world. Yet in this beginning step of IR analysis, elements of real-world objects and their interrelations have to be reduced from highly dynamic environments in which economic, political, legal, social, and technological variables are constantly evolving to more concrete and tangible measures (see Chapter Thirteen for more on defining e-health care technology management and strategy).

FIGURE 16.1. TRADITIONAL PROCESS FOR ANALYSIS OF USERS' INFORMATION REQUIREMENTS

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Next, the process of specification involves moving from a mental representation of abstract ideas and concepts to a more logically defined and formalized model. This is the stage in which key stakeholders, particularly users, attempt to move toward an information processing model of the real-world situation. Typically, the chief analyst is responsible for providing the specification in a form that is readable for both the end users and the programmers. In this regard, concepts and variables of the conceptual phase now have to be operationally defined as constructs, and the complex but observable phenomena in question must now be reduced to a manageable model that depicts the information flow. In short, conceptual elements and their relationships are translated into corresponding data objects (entities) and linkages (relationships). Many transitional models are formed during this transformational stage, each of which may be relatively abstract compared with the physical models that will follow in the final stage. Specification is the part of the IR analysis process that brings about a consensus of perspectives and concerns among key stakeholders; the analyst and system developer notes these perspectives and concerns.

Finally, the validation stage is an attempt to determine whether a valid set of user IRs has actually been created. During this phase, the earlier specification is refined, to provide an accepted and measurable reflection of the perceived system performance gaps and accepted solutions, both of which are now limited to the information system context. Thus, the objective is to achieve a working prototype. This intermediate product is a computer-based prototype that adequately captures the specified design model. In fact, the design model produced during validation is analogous to an architectural blueprint of a building, waiting for construction. This blueprint is the method for communicating between users and analysts, and it spells out the details of the proposed structure and contents of the information flow system. It is also a document for the contractor (programmer) to use in verifying, evaluating and building the system.

The journey from conceptualization to validation involves a series of mental transformations. Different analysts will choose different routes of mental transformation, which explains, in part, why different e-health solutions may be proposed to achieve the same purpose. The possibility of multiple solutions implies that there can be as many e-health applications as there are conceptualizations and interpretations of real-world phenomena. This is also one of the reasons why effective communication between analysts and end users at all three stages determines whether the resulting information system solution will meet the ends of all stakeholders.

A key limitation of the user IR analysis process just described is the lack of emphasis on bridging the user's IRs with the overall system's information needs and values. In short, the traditional view limits the conceptualization of user IRs to mostly operational and tactical levels of thinking. Thus, the resulting information system design concepts or ideas depend greatly on somewhat biased and subjective communications of particular user needs to the analysts. Owing to the complexity and potential frustration for an analyst in interacting with a group of end users who may well be unable or unwilling to communicate what they need or want from a shared perspective, most analysts find it convenient to focus the conceptualization process toward the views of a particular user. Thus, to meet the needs of a multiplicity of users with different or even conflicting needs and wants, analysts develop a network of isolated and fragmented systems, each of which satisfies the needs of a different set of individual users. In other words, the traditional IR analysis process supports the development of individualized or compartmentalized systems, not integrated user-oriented networks or systems.

A related limitation of the traditional approach is users' lack of an agreed-on basis for defining constructs and validating user needs and requirements. In other words, the validation process in the traditional IR analysis approach assumes that the design concepts and elements can be verified through a series of structured analyst-user interactions. What is missing is the notion that the constructs and variables to be verified should be linked to accepted standards that are shared among key stakeholders. In short, there is no explicit sense of what the constructs or variables might be for different users. The problem is aggravated in e-health applications designed to support multiple-level users with conflicting needs and wants. Thus, a new perspective for understanding strategic e-health system planning and design is needed—that is, a perspective that will not only align users' IRs with the general system mandate and purpose but ensure that all e-health users share the same views about needs and priorities.

Finally, the traditional approach emphasizes formalization of information system solutions for well-defined, structured, and isolated systems rather than integrated, dynamic e-health decision problems. The traditional specification process requires that analysts map user IRs onto a formalized model, using the systems approach, defining outputs via a backward chain of reasoning to the inputs (and validating inputs to outputs via a forward chain of reasoning). Because this level of reasoning and formalization is possible only if the decision systems are somewhat well-structured, the potentially high benefits of developing e-health applications using more qualitative and consumer-oriented data for semistructured and complex decision systems cannot be easily accommodated.

Many key e-health problems occur at the high levels of intraorganizational and interorganizational problems—for example, difficulties with the integration of health care services or the sharing of information among strategic partners and users. Thus, there is a need to develop more integrated perspectives that would effectively guide and accommodate the development of mixed applications to support well-structured, semistructured and ill-structured decision problems. Therefore, an accountability expectations framework, developed on the basis of a consumer-driven problemsolving model, is proposed to guide future e-health system planning and design.

The Accountability Expectations Framework

The accountability expectations framework (Modrow and Mathias, 1998; Tan and Modrow, 1999, 2003) refers generally to identifying a set of expected performance measures or indicators through which management can be held accountable for particular decisions or actions vis-à-vis clearly defined requirements and expectations from the consumer's end. As presented in Figure 16.2, the accountability expectations framework begins with specifying the ideal e-health model, followed by the identification of specific problems evolving within dynamic mandates and environments for which adequate information to make decisions must be captured. In other words, the information available must be sufficient for users to make the decisions and judgments for which they will be held accountable. Various e-health alternative solutions must be evaluated in an attempt to bridge problem gaps—that is, when the difference between the desired and observed performance is deemed unacceptable, new efforts should be made to ensure that a wide variety of innovative e-health solutions are examined. Indeed, solutions generated in this manner are likely to be adaptive and dynamic.

For e-health systems to be strategically and dynamically relevant, then, these systems should link users throughout the network system and set desired performance criteria. This linkage provides the basis to ensure that users achieve their performance goals within the bounds of the e-health system mandate and purpose. One necessary condition for this linkage is the existence of consumer-driven, albeit explicit and clearly defined measures of performance or standards for benchmarking performance. In other words, consumers must be surveyed in order to generate the measures.

Since users' characteristics differ (for example, e-providers differ from e-consumers in their roles and needs), users' standards for benchmarking and monitoring performance will also differ. For instance, e-providers may have explicit performance standards for determining success, defined in terms of market share, return on investment, net profit, and other clearly articulated and measurable indicators. All user decisions in such an environment would be clearly linked to the performance measures, and the quality of decisions made could be judged in relation to these measures.

As another example, imagine that a physician or an employer wants a mobile system to reduce expensive and often extraneous physician consultation costs related to manual prescription services. On this basis, one requirement for an effective mobile e-prescription application would be the ability to provide relevant and precise e-prescription information directly to pharmacists without the need for further consultation with a physician. If the pharmacists still have questions after receiving the information or if patients have complaints about their prescriptions, these problems should be tracked to provide a basis for evaluating the effectiveness of the mobile e-prescription solutions. In this sense, the mobile e-prescription system will not only reduce opportunity costs and increase productivity but also add value by assessing the effectiveness of medication intervention for the patients.

FIGURE 16.2. ACCOUNTABILITY EXPECTATIONS FRAMEWORK FOR E-HEALTH INNOVATIONS

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The analysis of existing prescription solutions compared with mobile or other potential solutions can also yield insights for evolving future prescription systems (for example, virtual prescription applications). Closing-the-gap analysis and continual benchmarking via evidence based medical practices, therefore, require analysts and users (in our case, the employer, the physician, and the pharmacist) to focus on identifiable and measurable differences between expected and observed performance and between newly designed solutions and existing solutions. The ideal e-health model should focus on measurable performance standards and indicators at the competitive level and system performance measures at the user accountability level. Based on an understanding of ideal versus current solutions, we can then evolve an e-health application that will adequately support the user information and decision-making roles and responsibilities. Such a system will generate the information needed or wanted, not just provide massive databases that may overload users with irrelevant and unwanted data.

Strategic thinking in the e-health context moves toward understanding performance measures and adding value to the health care process. The critical questions are “How is performance to be determined?” and “What value has been added by the introduction of the e-health solution?” For instance, if overprescription or patient safety becomes a concern, it would be important to add a verification function in the system to set limits on prescriptions so as to make pharmacists aware of these concerns. Viewing clinical performance in terms of traditional process outcomes such as adequate supplies and scheduling of order fillings and refills versus our proposed performance outcomes such as quality assurance and resulting health outcomes is analogous to making products available without being concerned about their quality. Nonetheless, in the competitive e-market system, profitability is an important criterion. Hence, the strategic relevance of e-health solutions must be linked to both the system's environment and performance outcomes.

As discussed at the beginning of this text, five basic strategies govern the outcomes of e-health systems and guide the development of future e-health systems: (1) specifying e-health core value propositions; (2) understanding the characteristics of the e-health service model; (3) involving the community of e-stakeholders; (4) strengthening the potential for a critical mass of transactions, to ensure sustainability and eventual profitability; and (5) examining e-health potential to accommodate future features such as product or service expansion, population growth, and global development.

E-health applications that are strategically relevant, consumer-driven, and performance-based will include applications that track user satisfaction data, systems that perform accounting and budgeting analysis, solutions that capture information on quality assurance and on public perception, systems that track complaints and facilitate their resolution, and applications that monitor competitive funding sources and the success with which developers of innovative e-health solutions can compete for these funds. In the end, regardless of whether the e-health applications are intended for e-providers or e-consumers, effective e-health solutions are those planned and designed to determine what users want and need, and those that can be used to monitor particular interventions in an attempt to reduce performance gaps and evaluate the effectiveness of the interventions. Because change is an essential characteristic of e-health, these solutions will be evolutionary in nature.

Conclusion

The future of e-health relates to the expansion of perspectives, the continuing growth of the Internet and other e-networks (Parts One and Two), the emergence of new domains and applications (Part Three), and the implementation of new strategies, management approaches, and impacts (Part Four) as well as the application of new and emerging mobile health networks and technologies, virtual reality, and other advancing technologies (Part Five). All of these developments will ultimately amount to the blurring of corporate communities on one hand and the blurring of user communities on the other. The defined roles of e-suppliers, e-providers, and e-customers are becoming less distinct. Therefore, it is still critical to come back, as I have in the final part of this chapter, to ask, “What is it that the consumers or the customers want? How do we go about designing something that is precisely what the market wants? What performance measures determine success?”

Today, companies are reaching outside their walls to encourage growth and development that incorporate many collaborative partners. This is already happening in the U.S. e-health marketplace. Under this model, many stakeholders hope that the health care industry will become more globalized in a positive, inclusive sense and less centralized. Understanding how to nurture organizations through the transition from a command-and-control focus to a virtual model while keeping them integrated will be a challenge for the government, the health insurance companies, provider groups, and many e-health venture capitalists and entrepreneurs in this century.

The most important message to be relayed in this text is that e-health systems should focus not on creating profit but on providing a competitive advantage, encouraging further innovations and more significant change for the improvement of human health and well-being. This is what distinguishes e-health from e-business. While new business functions must be created and competitive advantages can be realized, the goal is to reach out to the underserved and to those who have limited access. The need for effective universal access to health services has changed how the health care industry values health care goods and services. In the past, making health care goods and services available to individuals was the primary goal. Later, the focus became the quality of health care goods and services that can be provided to all patients within a region. With the globalization of markets and the shift in emphasis to ubiquitous computing, the focus is now on what benefits can be derived from the provision of health care goods and services. In other words, can preventive care and preparedness for potential public health hazards be achieved with new ways of performing health care? The change in the industry is also a movement from structured to unstructured processes. Being able to capitalize on complex processes will enable e-stakeholders, including e-vendors, e-payers, e-providers, and, most important, e-consumers to use the latest e-health technologies in new ways.

As we have noted throughout this text, a new paradigm in health care, the e-health paradigm shift, has emerged. This has led to new expectations among e-consumers of health care. Virtual reality, with its great promise for medical training and education, is one example of how e-health technology can help to achieve these increasingly higher expectations. From information management to surgical simulations and 3-D anatomy, new generations of medical students will learn how to meet these raised expectations by embracing the new paradigm. With this learning will come substantial advances that will revolutionize the way we think about current practices and methods. Already, some experts believe that if we can use nanotechnology to cure cancer, cancer patients will no longer need to endure harmful treatments such as radiation or laser surgery. Instead, molecular-level healing elements (nanotechnology) might destroy only targeted cancer cells without affecting neighboring cells. How successfully we combine our knowledge of these new technologies with health care services will be the determining factor in our future health and well-being.

The next breakthroughs in strategic e-health care applications are expected in the areas of integrated e-systems, intelligent e-networks, and e-robotics (Raghupathi and Tan, 2002). Indeed, the ability to integrate e-clinical and e-administrative information about e-patients means that doctors can provide better care at lower cost. For example, integrated e-clinical support systems can provide e-health professionals in a distributed clinical setting with on-line, real-time history of e-patients accessed from a master patient database. These systems will also allow e-physicians and other e-providers to track and analyze e-patient care history, e-test results, and e-billing and cost information. Typically, such applications combine data warehouses, electronic data entry, messaging, networks, and graphical user interface tools. The most enlightened health care organizations are now discovering that higher-quality care can in fact lead to lower costs.

Future research in e-health strategic planning and design should focus on a basic understanding of the different competitive environments in which health care services can operate and the strategic role and relevance of e-health applications in the different environments. In this regard, an important area to investigate is the appropriate mix of e-health investments in order to maximize strategic expertise and competitive advantage for private nonprofit systems and public sector health organizations. For example, senior management and chief information officers in these environments could be surveyed to find out where or in what areas they perceive that investments in e-health solutions would yield the greatest strategic benefits, and why.

Similarly, a critical question to study is how the process of e-health strategic planning and design should be managed as it moves from isolated intraorganizational concerns to integrated intraorganizational and interorganizational systems and from single-user to multi-user applications. In this context, research on issues related to differences in the strategic thinking, planning, and management of e-health thinking in private sector versus public sector health environments is particularly warranted. I have also noted the importance of understanding how consumer-driven e-health will eventually affect the financing of e-health.

In summary, we stand at a crossroads. The technology we know today has the potential to be applied for the great good of millions of people, even entire populations. At the same time, the ongoing suffering in this world, fighting over limited resources, torturing of human beings, and killings not only of animals but also of large numbers of human beings must be reversed. Technology is only as good as its appropriate use to better the lives of others. Having that power in our hands, we must go about using it well. This, in essence, is the future of e-health care. The ideal and most significant paradigm shift will be the shift in human thinking—that is, applying new and emerging technologies not to destroy the human race but to create a peaceful and healthy world.

Chapter Questions

Provide a framework for understanding mobile health. How is mobile health different from and similar to e-health? What other domain or area might be the next frontier?
Give an example of a virtual reality application. Why might VR therapies be considered or expected to be superior to conventional therapies? What are the potential side effects of VR for phobia therapies?
Why is it important to understand the accountability expectations framework? What significance does this understanding have for our design of future-oriented e-health applications and solutions?
What is meant by an adaptive solution?
Imagine that you have the power to install an e-health application that would reverse the aging process. Describe the potential characteristics of such a solution, and indicate how it would actually be useful. How might such an innovation be evaluated?

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Virtual Reality Case

Joseph Tan, Pency Tsai

Originally conceived by the founder of VPL Research, Jaron Lanier, to refer to immersive virtual reality, in which users are thrown into an artificial computer-generated three-dimensional environment, the term virtual reality (VR) refers to a computergenerated interactive multimedia environment into which the user is assimilated, so that he or she becomes an active participant in a virtual world (Pantelidis, 1995; Passig and Eden, 2000). Other closely related terms include cyberspace, artificial reality, virtual worlds, and virtual environments.

Over the decades, the best-known VR applications have been in the entertainment industry. In fact, VR hype is now almost ubiquitous in that sector, in video games, movies, and more. VR simulations are found in many environments that range from education to military and pilot training and even practice for space shuttle missions. Architects, for example, use VR to envision a building before it is built, to minimize potentially costly mistakes. Molecular biologists use VR to explore the microscopic world of molecules and to “experience” intermolecular forces. The same immersive technology is used to assist people in exploring their phobias (Dunkley, 1994). VR applications are becoming progressively more compelling in many aspects of our lives.

Generally speaking, there are two types of VR technologies. Immersive virtual reality, the more advanced technology, fully surrounds users with a computer-generated environment. Users typically wear helmets, data gloves, and a body suit with visual display units and speakers. Thus, the system is able to track users' responses to the simulations. Non-immersive virtual reality, which is used primarily for academic purposes such as distance learning, permits users to interact primarily with a three-dimensional (3-D), computer-generated display. The following case focuses on immersive VR technology.

Entering Immersive Virtual Reality Environments

To enter immersive virtual environments (VEs), one must wear special equipment such as data gloves, goggles, and earphones, which receive inputs from the computer. A head-mounted display created by Evans and Sutherland in 1965 was the first device that provided immersive virtual experience. A head-mounted display (HMD) is a helmet that covers the user's full face and that contains an optical system and two miniature display screens that continually send images to the eyes. At all times, a motion tracker recognizes and measures the position and movement of the user's head. The HMD allows the image-generating computer to adjust the scene representation to the appropriate view. Thus, the viewer can “look around” and “walk through” the surrounding VE (Beier, 2004). Several types of HMDs (LCD-display HMD, projected HMD, small-CRT HMD, and single-column-LED HMD) may be used. However, with all HMDs, VR is often quite intrusive, uncomfortable enough to give rise to alternative types of VEs, such as BOOM and CAVE.

The BOOM (binocular omni-orientation monitor) is a device mounted on a mechanical arm that has tracking sensors located at the joints. Users must secure the monitor and hold their face up to it. The computer then generates appropriate scenes based on the positions and orientation of the joints on the mechanical arm (Aukstakalnis and Blatner, 1992). Through the use of projected stereo images on the floor and walls of a room-sized cube, the CAVE (cave automatic virtual environment) provides users with the illusion of immersion. Several persons wearing lightweight stereo glasses, for example, can enter and move freely inside the CAVE. Head tracking systems continuously adjust the stereo projection to the current position of the leading viewer.

A data glove is an input device equipped with a fiber-optic bend sensor, which helps users sense and generate their finger movements. The sensor also transmits the data to the VR computer. Some sophisticated data gloves can even record movements from wrists and elbows. In the virtual world, users can point to, grip, and push objects, so the use of the data gloves sensually enriches the immersive experience.

Virtual Reality Cases in Health Care

We now move to VR cases in Health Care, including training and education applications, psychology and psychiatry, and phobia therapies.

Training and Education. Computer graphics have been adapted in the Animated Dissection of Anatomy for Medicine (ADAM). With an extensive collection of twodimensional anatomy drawings, ADAM creates a 3-D effect by cutting away tissue layers and sections.

Another form of VR-like training simulation is electronic laparoscopic simulation. Dunkley (1994) notes that electronic laparoscopic simulations may act like VR. For instance, trainees (students) can insert simulated instruments into an electronic mock-up of a body and perform surgeries. Internal organs are displayed on monitors, and the surgeon's virtual movements can be sensed through the use of immersive VR technology. Thus, VR simulation can effectively increase the medical students' skills without risking patients' lives. Using advances in medical knowledge and the evolution of computerized training models, VR provides an alternative medium for medical students to practice medicine.

Many nursing schools continue to add more theoretical courses while shortening the length of practical training so that nurses can enter the workforce sooner. This practice results in deficiencies in clinical experience. With the aid of VR simulations, students can now practice their skills without adverse impacts on patients. Moreover, VR can also assist students in gaining critical thinking skills by giving them opportunities to take risks and make correct decisions. With VEs, students also have the opportunity to experience care settings similar to those they will face in real life. For example, VR allows nursing students to practice inserting an intravenous line. Students can also practice conducting patient assessments on the desktop, using virtual anatomical 3-D models, while tracking simulated electronic patient records.

Rehabilitation. Virtual reality has been proven effective as a treatment tool in rehabilitation. VR allows disabled individuals to practice tasks they wish to accomplish in real life without fear of pain or further injury. VR can be used in occupational therapy to improve balance and dynamic standing tolerance, especially in geriatric patients. It can also help patients with spinal cord injuries to overcome some of the physical limitations that affect their mobility and to increase their level of independence as well as the quality of their daily life.

It is often difficult to conduct accurate and controlled assessments of stroke patients' memories. There is scanty empirical evidence about how to address problems related to loss of prospective memory (Brooks, 2004). Prospective memory is the type of memory that is needed to complete future tasks, such as remembering to give a note to someone when you next see them, to pick up milk on the way home, or to keep an appointment. By testing prospective memory through simulations in VEs, a better assessment of the memory loss can be achieved. This will also help overcome some of the difficulties such as designing real world tasks for effective rehabilitation programs on stroke patients.

Surgical Applications. VR can provide 3-D anatomical views of internal organs as well as bones for simulations of surgical operations. This kind of practice enables surgeons to visualize the intended procedure more accurately, which improves their perception in the operative field. In addition to helping surgeons prepare for surgery through simulations, VR technology can circumvents many problems in actual surgery. For example, during a brain operation, VR technology can be used to fuse an MRI scan of the patient's tumor with a video image of the actual brain, which can obscure much of the X-ray image and result in loss of surgical precision if the tumor is deeply embedded in the brain tissues (Satava, 1995).

The most extreme use of VR in surgery is telepresence surgery, in which the surgeons in a remote location perform procedures on a virtual image of the patient. Their movements are electronically transmitted to a medical telerobot that performs the procedure on the actual patient (lovine, 1995).

Psychology and Psychiatry. The use of VR in medicine is not new; various VEs for health care have been developed for surgical procedures, preventive medicine and patient education, medical education and training, visualization of massive medical databases, and architectural design for health care facilities. However, there is a growing recognition that VR can play an important role in clinical psychology as well. VR applications can provide a range of services from diagnostic tests to therapeutic improvements. VR is an effective medium of treatment for a variety of disorders. One example is the use of VR in the treatment of phobias. Patients are helped to overcome their irrational fears and apprehensions through virtual exposure to phobogenic stimuli. A controlled study by Hodges and Rothbaum showed VR to be effective in remedying acrophobic subjects' anxiety and avoidance of heights (Kooper, 1995). Besides being time-efficient and cost-effective, VR defines a very controlled environment for phobia treatment. In other words, VR phobia treatment eliminates the variables that might prevent treatment receivers from successfully identifying and addressing the stimuli of interest. It is also worth mentioning that most people with phobias prefer to undergo virtual exposure rather than being exposed to a feared situation or object in vivo. We will now examine the use of VR for treatment of phobias in more detail.

Types of Phobias

Phobias can be divided into three categories: social phobias, specific phobias, and panic disorders. Social phobias, also known as social anxiety disorders, occur when individuals have excessive anxieties in social situations; such as, parties, meetings, interviews, restaurants, making complaints, writing in public, eating in restaurants, and interacting with the opposite sex, strangers, and aggressive individuals. Specific phobias, also known as simple phobia, is a persistent, irrational fear of, and compelling desire to avoid, specific objects or situations. Panic disorder is marked by recurrent, spontaneous fear and panic attacks. A panic attack is an intense period of fear or discomfort.

The National Institute of Mental Health estimates that at least 5.3 million Americans have a social phobia. Furthermore, the Surgeon General's Report on Mental Health, issued at the end of 1999, indicates that approximately 7 percent of Americans are disturbed to some extent by social phobias in their daily life (Smith, 2004a). Unfortunately, social phobias are only one type of fear. The NIMH further indicates that more than one out of ten Americans has had one or more specific phobias. A telephone study of one thousand adults done by Penn, Schoen, & Berland Associates, Inc., for Discovery Health shows that 7 percent of Americans report themselves as suffering from a phobia. Shockingly, about 40 percent admit that they have a great fear of a specific object or a specific situation. For example, Americans have fears of snakes (40 percent), rats (58 percent), and cockroaches (23 percent). Moreover, 24 percent of American women and 17 percent of men acknowledge the fear of being in crowded or open spaces. It is estimated that roughly a third of all Americans admit to having had panic attacks. Despite these high indices of fear, only about 11 percent of all people with phobias seek professional help.

According to Dr. Roger Burket, associate professor and director of residency training at the University of Florida's Division of Child and Adolescent Psychiatry, children often suffer from the same phobias and anxieties as their parents do (Smith, 2004a). His research indicates that many people learn phobias by hearing about their parent's fears or witnessing their parents' reaction when feared situations or objects are presented. According to Dr. Cary Savage, director of the Cognitive Neuroscience Group in the Department of Psychiatry at Massachusetts General Hospital and Harvard Medical School, it is not clear whether phobic reactions of children of parents with phobias are biologically inherited or attributable to early learning.

People with specific phobias are usually aware of their abnormal fears. Only when the fear interferes with their lives, however, do they seek professional help. Common phobias include fear of animals, insects, heights, elevators, flying, automobile driving, water, storms, and blood or injections.

Phobic disorders rarely develop after the age of twenty-five, according to the National Mental Health Association. Studies funded by the National Institute of Mental Health show that a specific phobia may be inherited or may result from damage to the amygdala, a small structure in the brain that may be responsible for fear responses (Smith, 2004c). However, serious social phobias may develop later in life or can be transformed into panic disorders, which are characterized by chest pains, heart palpitations, shortness of breath, dizziness, or abdominal distress. People who suffer from social phobias also have a 50 percent chance of simultaneously suffering from other psychiatric problems, such as depression, substance abuse, or panic disorder.

Traditional Versus Virtual Reality Therapy (VRT)

Medicine and other cognitive-behavioral therapies have traditionally provided remedies for phobias. The most effective and well-recognized phobia therapy is exposure therapy; that is, gradually exposing people with phobias to the stimuli that cause fear. For example, repeated exposure to footbridges, outdoor balconies, and glass elevators, virtual or otherwise, has been proven to successfully decrease patients' fear of heights and, furthermore, to change their previous outlook on heights as they become accustomed to heights (Hodges and others, 2001).

During VR exposure treatment, when patients are put into VR environments, their fears get activated; patients begin to experience physical reactions when in feared situations, such as sweating, “butterflies” in the stomach, and weak knees. Although the reactions are initially rather strong, with the help of the virtual reality therapy, most patients usually recover from their fears quite quickly. Progressively, they are also more able to face their fears in real life. Virtual reality exposure therapy places the client in a computer-generated world where they “experience” the various stimuli related to their phobia. The patient wears a head-mounted display with small TV monitors and stereo earphones to receive both visual and auditory cues. VR Therapy tends to cost less than vivo exposure. The “phobic” experience is in total control without leaving the therapist's office and the segments of any phobia can be repeated, allowing the patient to gradually reduce fear and anxiety. People once resistant to traditional treatment may find Virtual Reality Therapy acceptable.

A test of VR therapy's efficiency has been the treatment of combat-related post-traumatic stress disorders (PTSD) among Vietnam veterans (Hodges and others, 2001). Patients may develop PTSD after a traumatic change in their lives, such as a severe car accident or a sexual assault. High avoidance of retrieving past traumatic memories, sleep difficulties, nightmares, and flashbacks are some symptoms of PTSD. Combat-related PTSD affected approximately 830,000 Vietnam War veterans (Hodges and others, 2001). VR therapy can provide much needed help in facilitating retrieval of past traumatic memories. For patients suffering from PTSD, the virtual world is a place they could go to confront their fear or to confront a traumatic experience. Studies have shown that retrieval of past traumatic memories can help cure PTSD symptoms.

Conclusion

Virtual reality technology has many potential applications in medicine, including surgical training; tele-operated robotic surgery; assessment and rehabilitation of phobias and other social, behavioral, and neurological disorders; and diagnosis and rehabilitation of physical disabilities. Virtual reality today offers a new paradigm for human-computer interaction, in which users are no longer simply external observers of images on a computer screen, but active participants within a computer-generated three-dimensional world. Most of the psychological therapies carried out with the help of virtual reality rely on the principle of exposure. Possibilities offered by VR in the field of the cognitive-behavioral therapies are numerous. VRT has not replaced the role played by therapist. Indeed, his/her presence near to the patient remains essential. It seems that VR reinforces the therapeutic relation between patient and therapist on a collaborative mode.

Case Questions

Define virtual reality. Name the different types of virtual reality.
What are the major areas in which VR can be applied to health care?
What effective is VRT in treating phobic disorders?

References

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Smith, A. (2004a). Facts about phobia. Retrieved from http://health.discovery.com/centers/mental/phobias/facts.html

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Table of Contents for CHAPTER SIXTEEN: E-HEALTH PROSPECTS

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CHAPTER SIXTEEN

E-HEALTH PROSPECTS

Learning Objectives

Introduction

Mobile Health Care

Mobile Health Clinical Applications

Mobile Health Administration Applications

Mobile Health Delivery Systems

Virtual Reality in Health Care

Virtual Reality in Medical Education and Surgical Intervention

Virtual Reality in Phobia Therapy

Virtual Reality in Rehabilitation

Trade-Offs in Virtual Reality Therapies

Consumer-Driven E-Health Systems

Analyzing User Information Requirements

The Accountability Expectations Framework

Conclusion

Chapter Questions

References

Virtual Reality Case

Entering Immersive Virtual Reality Environments

Virtual Reality Cases in Health Care

Types of Phobias

Traditional Versus Virtual Reality Therapy (VRT)

Conclusion

Case Questions

References

Table of Contents for
CHAPTER SIXTEEN: E-HEALTH PROSPECTS