ELECTRONIC HEALTHCARE DATA SYSTEM DEVELOPMENT

Electronic Healthcare Data System Development

Abstract

This paper has considered the role of evaluation in the design of health care information systems.

It has been argued that evaluation must be considered throughout the entire systems development life cycle (SDLC) in creating health care applications. Modern design methodologies based on rapid development and iterative prototyping rely on formative evaluation in order to provide designers with the input needed to improve systems. Methods emerging from the field of usability engineering, in particular usability testing, are essential for conducting such evaluations. The paper concludes with a framework for considering evaluation methods ranging from controlled experimental approaches to naturalistic observational approaches. Suggestions for further research in advancing the state of evaluation in health informatics are discussed.

Electronic Healthcare Data System Development

Introduction

In the field of health informatics, summative evaluations have been conducted to evaluate the impact of a wide variety of systems in clinics and other health care environments. Numerous evaluations have assessed the effects of health information systems on dependent measures such as health outcomes, length of stay, cost -effectiveness, quality of care and other measures [1]. These studies typically apply randomized clinical control trials methodologies. Such evaluations are analogous to the testing of drugs and other discrete health care interventions where there is a clearly defined independent variable (e.g., presence or absence of a drug, or in the case of health informatics studies, presence or absence of an information system). Although these types of evaluations are necessary in order to ensure that systems that are developed are both safe and effective, greater emphasis is needed to ensure that the process of system design is effective. In addition, it can be argued that we will not understand the full meaning of outcomes we obtain from the use of information technology, unless we can understand outcomes in terms of the design decisions that lead to the outcomes.

A wide range of methodologies have been developed in the general software industry for providing frameworks for designing information systems. Life cycle models provide a foundation for guiding the development and evaluation of complex systems [2,3]. Traditional system development life cycles (SDLC) presuppose a set of fixed stages for system development, with evaluation of the system predominantly occurring in the final stages. Such approaches have proven difficult to successfully apply in health care where information needs may be hard to precisely determine. The possible reasons for this are that the health care environment is often complex and characterized by missing information, shifting goals and a great deal of uncertainty. Health care decision making processes are complex, poorly understood and consequently difficult to model effectively in the analysis of the SDLC. Health care decisions are subject to a level of uncertainty not found in traditional business environments and consequently health care technology and the knowledge on which it is based is often very volatile. In fact, even before decision making processes are understood, they may change within the time span of the traditional ...