Applying A Theoretical Framework To The Research And Design Of Medical Error Reporting Systems
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The following is an abstract for a paper presentation accepted for the International Conference for Healthcare Systems Ergonomics and Patient Safety (April 2005: Florence, Italy)
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R. J. Holden1,2 & B. Karsh1
1. Department of Industrial and Systems Engineering, University of Wisconsin-Madison
2. Department of Psychology, University of Wisconsin-MadisonPatient safety research is largely atheoretical. The failure to apply extant theory or generate new theoretical perspectives is especially evident in the literature on medical incident/error reporting, but this does not have to be so in the future. To encourage a more theoretical bearing of error reporting research, we demonstrate the effectiveness of a theoretical framework for interpreting and predicting research findings. We also propose a novel theoretical model for understanding and promoting the adoption and use of reporting systems and other healthcare technologies. Error reporting systems are widely promoted for improving patient safety, but current systems have had questionable success1, with underreporting rates estimated at 50 to 96%. This begs the question: what factors discourage error reporting (barriers) and what are the factors that will motivate reporting behavior (motivators)? This question has received some attention, yet there are currently more opinions than empirical findings. Moreover, the few empirical studies of the barriers to and motivators for reporting behavior have been largely atheoretical, despite a large corpus of relevant theory. For example, we and others have reported on practitioners' opinions of a "good" reporting system2, but these findings have not been organized into a theoretical framework nor has any theory been used to guide the exploration of barriers and motivators in a prospective manner. Employing a theoretical framework may provide more insightful evaluation and interpretation of findings and may guide the selection of factors to explore and hypotheses to test. Conversely, an atheoretical approach risks missing key factors, is weak for explaining how findings within and between studies interact, and makes it difficult to make generalizations about future findings or-importantly-about practical design decisions. To demonstrate how a theoretical framework can be applied to interpret research on error reporting, we drew on theories of motivation, decision making, and technology change/acceptance. Below we present only select examples due to space constraints (the complete paper will be far more comprehensive). We included two classes of motivation theories. Need classification theories focus on the importance assigned to different outcomes like safety and achievement. Expectancy theories describe motivation as a function of the belief that action/inaction will result in some aversive/rewarding outcome and the value placed on this outcome. Reporting can lead to positive performance outcomes (increased patient safety) or negative personal outcomes (legal ramifications). Because avoiding negative personal outcomes is a higher-classified need, practitioners avoid reporting if it is not protected from aversive (social/legal/professional) consequences. Decision-making theories are of two kinds. Attitude-based theories focus on attitudes toward actions/technologies. E.g., practitioners' attitudes differed on whether technology helps or gets in the way. Social cognitive theory implies that behavior is shaped by interactions between environmental and personal factors. E.g., practitioners' use of reporting systems depended on the interaction of environmental (complexity of system, amount of free time) and personal (training/knowledge) factors. Theories of technology change/acceptance are quite relevant to understanding the design and use of healthcare technology3. We used several theories, including the Technology Acceptance Model, Innovation Diffusion Theory, and Sociotechnical Systems Theory. Each has in common several factors that corresponded to error reporting research findings. System use is determined by its usefulness (does it improve patient safety?), ease of use (is it intuitive/time-efficient?), aversive outcomes (is there legal protection/anonymity?), and social norms for behavior (is reporting important/encouraged?). Finally, we present a hierarchical model of reporting system acceptance that includes four critical factors, described by the interaction between technology and (1) healthcare task characteristics like complexity and methodology, (2) practitioner characteristics like values and skills, (3) organizational characteristics like size and culture, and (4) environmental characteristics like legislation and external pressure to use technology for patient safety. We propose that our model can be useful for understanding the adoption and use of reporting systems and other healthcare technologies.
1. Barach, P. & Small, S.D. (2000). Reporting and preventing medical mishaps: Lesson from non-medical near miss reporting systems. British Medical Journal, 320, 759-763.
2. Escoto, K.H., Karsh, B., & Beasley, J.W. (2004). Multiple user considerations and their implications in medical error reporting system design. Human Factors. In press.
PLEASE CLICK HERE TO SEE THE PAPER SUBMITTED FOR THE CONFERENCE PROCEEDINGS.