Article

Health care research that delivers: introduction to the special issue on cognitive factors in health care.

Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, 405 N Mathews Ave, Urbana, Illinois, 61801, USA.
Journal of Experimental Psychology Applied (Impact Factor: 1.75). 09/2011; 17(3):191-4. DOI: 10.1037/a0025244
Source: PubMed

ABSTRACT Research that addresses human factors issues in health care has made good progress since the landmark 1999 Institute of Medicine report on medical error (Kohn, Corrigan, & Donaldson, 1999), yet patient safety remains a persistent challenge for the health care system. While this challenge reflects many factors, we focus on the need for research that is sufficiently comprehensive to identify threats to patient safety, yet specific enough to explain how provider and patient factors interact with task and health context to engender these threats. Such research should be theory-based, yet also problem-driven; exert experimental control over theoretically relevant variables, yet also involve participants, tasks, and contexts that represent the problems of interest. A tension exists between theory-based, experimentally controlled research on the one hand, and problem-driven research with representative situations on the other. The studies in this special issue are both informed by theory and guided by application, reflecting what Stokes (1997) referred to as "use-inspired basic research." Collectively, these studies represent progress toward improving patient safety and the quality of health care. However, important work remains to be done to significantly improve health care by more comprehensively managing tensions between theory and application and different research methodologies. We discuss barriers to accomplishing such research in general (the challenge of testing theory in situ in rich environments), and specifically in the health care domain. Significant progress will require research programs that thoughtfully manage mixed methods across a series of converging studies.

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