title: Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition.
abstract: Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.
authors.affiliation: Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
authors.forename: Don
authors.initials: D
authors.lastname: Roosan
authors.affiliation: COIN: Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS 2.0), Salt Lake City VA Medical Center, Salt Lake City, UT, USA.
authors.forename: Matthew
authors.initials: M
authors.lastname: Samore
authors.affiliation: COIN: Informatics, Decision-Enhancement and Analytic Sciences Center (IDEAS 2.0), Salt Lake City VA Medical Center, Salt Lake City, UT, USA.
authors.forename: Makoto
authors.initials: M
authors.lastname: Jones
authors.affiliation: Scientific Computing and Imaging Institute, School of Computing, University of Utah, Salt Lake City, UT, USA.
authors.forename: Yarden
authors.initials: Y
authors.lastname: Livnat
authors.affiliation: Department of Biomedical Informatics, School of Medicine University of Utah, Salt Lake City, UT, USA.
authors.forename: Justin
authors.initials: J
authors.lastname: Clutter
keywords: Big-Data; clinical reasoning; population decision support; population health data