Collaboration, Interruptions, and Changeover Times: Workflow Model and Empirical Study of Hospitalist Charting

Itai Gurvich (), Kevin J. O’Leary (), Lu Wang () and Jan A. Van Mieghem ()
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Itai Gurvich: Cornell Tech, School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 10027
Kevin J. O’Leary: Feinberg School of Medicine, Northwestern University, Chicago, Illinois 60611
Lu Wang: Kellogg School of Management, Northwestern University, Evanston, Illinois 60208
Jan A. Van Mieghem: Kellogg School of Management, Northwestern University, Evanston, Illinois 60208

Manufacturing & Service Operations Management, 2020, vol. 22, issue 4, 754-774

Abstract: Problem definition: Collaboration is important in services but may lead to interruptions. Professionals exercise discretion on when to preempt individual tasks to switch to collaborative tasks. Academic/practical relevance: Discretionary task switching can introduce changeover times when resuming the preempted task and, thus, can increase total processing time. Methodology: We analyze and quantify how collaboration, through interruptions and discretionary changeovers, affects total processing time. We introduce an episodal workflow model that captures the interruption and discretionary changeover dynamics—each switch and the episode of work it preempts—present in settings in which collaboration and multitasking is paramount. A simulation study provides evidence that changeover times are properly identified and estimated without bias. We then deploy the model in a field study of hospital medicine physicians: “hospitalists.” The hospitalist workflow includes visiting patients, consulting with other caregivers to guide patient diagnosis and treatment, and documenting in the patient’s medical chart. The empirical analysis uses a data set assembled from direct observation of hospitalist activity and pager-log data. Results: We estimate that a hospitalist incurs a total changeover time during documentation of five minutes per patient per day. Managerial implications: This estimate represents a significant 20% of the total processing time per patient: caring for 14 patients per day, our model estimates that a hospitalist spends more than one hour each day on changeovers. This provides evidence that task switching can causally lead to longer documentation time.

Keywords: collaboration; coordination; multitasking; discretion; changeover time; empirical; interruptions (search for similar items in EconPapers)
Date: 2020
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