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- Sarah A Teele, Patrice Tremoulet, Peter C Laussen, Nicole Danaher-Garcia, Joshua W Salvin, and WhiteBobbie Ann ABAAMassachusetts General Hospital Institute of Health Professions, Boston, Massachusetts, USA..
- Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
- J Eval Clin Pract. 2024 Mar 1; 30 (2): 337345337-345.
RationaleAdvancing our understanding of how decisions are made in cognitively, socially and technologically complex hospital environments may reveal opportunities to improve healthcare delivery, medical education and the experience of patients, families and clinicians.Aims And ObjectivesExplore factors impacting clinician decision making in the Boston Children's Hospital Cardiac Intensive Care Unit.MethodsA convergent mixed methods design was used. Quantitative and qualitative data sources consisted of a faculty survey, direct observations of clinical rounds in a specific patient population identified by a clinical decision support system (CDSS) and semistructured interviews (SSIs). Deductive and inductive coding was used for qualitative data. Qualitative data were translated into images using social network analysis which illustrate the frequency and connectivity of the codes in each data set.ResultsA total of 25 observations of eight faculty-led interprofessional teams were performed between 12 February and 31 March 2021. Individual patient characteristics were noted by faculty in SSIs to be the most important factor in their decision making, yet ethnographic observations suggested faculty cognitive traits, team expertise and value-based decisions were more heavily weighted. The development of expertise was impacted by role modeling. Decisions were perceived to be influenced by the system and environment.ConclusionsClinician perception of decision making was not congruent with the observed behaviours in a complicated and dynamic system. This study identifies important considerations in clinical curricula as well as the design and implementation of CDSS. Our method of using social network analysis to visualize components of decision making could be adopted to explore other complex environments.© 2023 John Wiley & Sons Ltd.
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