TY - JOUR
T1 - Modeling Task Scheduling Decisions of Emergency Department Physicians
AU - Barg-Walkow, Laura H.
AU - Thomas, Rickey P.
AU - Wickens, Christopher D.
AU - Rogers, Wendy A.
N1 - We thank Jeremy Ackerman, Sidhant Nagrani, and David Illingworth for their support on this research. Some data and analyses presented here were part of the first author’s dissertation (Barg-Walkow, 2017). This research was supported in part by an American Psychological Association Dissertation Research award to the first author.
PY - 2021/5
Y1 - 2021/5
N2 - 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.
AB - 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.
KW - decision-making
KW - emergency medicine and resuscitation
KW - expert–novice differences
KW - mathematical modeling
KW - skilled performance
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U2 - 10.1177/0018720819893427
DO - 10.1177/0018720819893427
M3 - Article
C2 - 31891518
AN - SCOPUS:85077378828
SN - 0018-7208
VL - 63
SP - 450
EP - 461
JO - Human Factors
JF - Human Factors
IS - 3
ER -