Modeling Task Scheduling Decisions of Emergency Department Physicians

Laura H. Barg-Walkow, Rickey P. Thomas, Christopher D. Wickens, Wendy A. Rogers

Research output: Contribution to journalArticle

Abstract

Objective: This study evaluated task-scheduling decisions in the context of emergency departments by comparing patterns of emergency physicians’ task-scheduling models across levels of experience. Background: Task attributes (priority, difficulty, salience, and engagement) influence task-scheduling decisions. However, it is unclear how attributes interact to affect decisions, especially in complex contexts. An existing model of task scheduling, strategic task overload management-no priority (STOM-NP), found that an equal weighting of attributes can predict task-scheduling behavior. Alternatively, mathematical modeling estimated that priority alone could make similar predictions as STOM-NP in a parsimonious manner. Experience level may also influence scheduling decisions. Method: An experimental design methodology shortened a judgment analysis approach to compare a priori task-scheduling decision strategies. Emergency physicians with two levels of experience rank-ordered 10 sets of 3 tasks varying on 4 task attributes in this complex environment. Results: Bayesian statistics were used to identify best-fit decision strategies. STOM-NP and priority-only provided the best model fits. STOM-NP fit the lower-experienced physicians best, whereas priority-only—using only one cue—fit the higher-experienced physicians best. Conclusion: Models of decision strategies for task-scheduling decisions were extended to complex environments. Experts’ level of experience influenced task-scheduling decisions, where the scheduling decisions of more-experienced experts was consistent with a more frugal decision process. Findings have implications for training and evaluation. Application: We assessed models of cues that influence task-scheduling decisions, including a parsimonious model for task priority only. We provided a sample approach for shortening methods for understanding decisions.

Original languageEnglish (US)
JournalHuman Factors
DOIs
StateAccepted/In press - 2019

Keywords

  • decision-making
  • emergency medicine and resuscitation
  • expert–novice differences
  • mathematical modeling
  • skilled performance

ASJC Scopus subject areas

  • Human Factors and Ergonomics
  • Applied Psychology
  • Behavioral Neuroscience

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