title: Understanding complex clinical reasoning in infectious diseases for improving clinical decision support design.
abstract: BACKGROUND
  Clinical experts' cognitive mechanisms for managing complexity have implications for the design of future innovative healthcare systems. The purpose of the study is to examine the constituents of decision complexity and explore the cognitive strategies clinicians use to control and adapt to their information environment.
  
  
  METHODS
  We used Cognitive Task Analysis (CTA) methods to interview 10 Infectious Disease (ID) experts at the University of Utah and Salt Lake City Veterans Administration Medical Center. Participants were asked to recall a complex, critical and vivid antibiotic-prescribing incident using the Critical Decision Method (CDM), a type of Cognitive Task Analysis (CTA). Using the four iterations of the Critical Decision Method, questions were posed to fully explore the incident, focusing in depth on the clinical components underlying the complexity. Probes were included to assess cognitive and decision strategies used by participants.
  
  
  RESULTS
  The following three themes emerged as the constituents of decision complexity experienced by the Infectious Diseases experts: 1) the overall clinical picture does not match the pattern, 2) a lack of comprehension of the situation and 3) dealing with social and emotional pressures such as fear and anxiety. All these factors contribute to decision complexity. These factors almost always occurred together, creating unexpected events and uncertainty in clinical reasoning. Five themes emerged in the analyses of how experts deal with the complexity. Expert clinicians frequently used 1) watchful waiting instead of over- prescribing antibiotics, engaged in 2) theory of mind to project and simulate other practitioners' perspectives, reduced very complex cases into simple 3) heuristics, employed 4) anticipatory thinking to plan and re-plan events and consulted with peers to share knowledge, solicit opinions and 5) seek help on patient cases.
  
  
  CONCLUSIONS
  The cognitive strategies to deal with decision complexity found in this study have important implications for design future decision support systems for the management of complex patients.
authors.affiliation: Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT, 84108, USA. roosan.islam@utah.edu.|IDEAS Center for Innovation, VA Salt Lake City Health System, 500 Foothill Drive, Salt Lake City, UT, 84108, USA. roosan.islam@utah.edu.
authors.forename: Roosan
authors.initials: R
authors.lastname: Islam
authors.affiliation: Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT, 84108, USA.|IDEAS Center for Innovation, VA Salt Lake City Health System, 500 Foothill Drive, Salt Lake City, UT, 84108, USA.
authors.forename: Charlene R
authors.initials: CR
authors.lastname: Weir
authors.affiliation: IDEAS Center for Innovation, VA Salt Lake City Health System, 500 Foothill Drive, Salt Lake City, UT, 84108, USA.
authors.forename: Makoto
authors.initials: M
authors.lastname: Jones
authors.affiliation: Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT, 84108, USA.|IDEAS Center for Innovation, VA Salt Lake City Health System, 500 Foothill Drive, Salt Lake City, UT, 84108, USA.
authors.forename: Guilherme
authors.initials: G
authors.lastname: Del Fiol
authors.affiliation: Department of Biomedical Informatics, University of Utah, 421 Wakara Way, Ste 140, Salt Lake City, UT, 84108, USA.|IDEAS Center for Innovation, VA Salt Lake City Health System, 500 Foothill Drive, Salt Lake City, UT, 84108, USA.
authors.forename: Matthew H
authors.initials: MH
authors.lastname: Samore
mesh_terms: D000328:Adult; D003141:Communicable Diseases / Q000628:therapy*; D020000:Decision Support Systems, Clinical / Q000592:standards*; D006801:Humans; D010820:Physicians / Q000592:standards*; D036301:Qualitative Research; D013850:Thinking