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 semi-structured 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 semi-structured 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.

Was this article helpful?

0 0

Post a comment