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

Manufacturing & Service Operations Management

43 Pages Posted: 12 Jun 2015 Last revised: 22 Nov 2018

Date Written: September 25, 2018

Abstract

Collaboration is important in services, but may lead to interruptions. Professionals exercise discretion on when to preempt individual tasks to switch to collaborative tasks. Discretionary task switching can introduce changeover times when resuming the preempted task and thus can increase total processing time.

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 changeovers dynamics---each switch and the episode of work it preempts---present in settings where 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 dataset assembled from direct observation of hospitalist activity and pager-log data. We estimate that a hospitalist incurs a total changeover time during documentation of 5min per patient per day. This represents a significant 20% of total processing time per patient: caring for 14 patients per day, a hospitalist spends more than one hour each day on changeovers. This provides evidence that task switching causally leads to longer documentation time.

Keywords: coordination, multitasking, professional labor, discretion, changeover time, empirical.

Suggested Citation

Gurvich, Itai and O'Leary, Kevin and Wang, Lu and Van Mieghem, Jan Albert, Collaboration, Interruptions and Changeover Times: Workflow Model and Empirical Study of Hospitalist Charting (September 25, 2018). Manufacturing & Service Operations Management. Available at SSRN: https://ssrn.com/abstract=2616926 or http://dx.doi.org/10.2139/ssrn.2616926

Itai Gurvich

Northwestern University ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Kevin O'Leary

Northwestern University - Feinberg School of Medicine ( email )

Chicago, IL 60611
United States

Lu Wang

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

Jan Albert Van Mieghem (Contact Author)

Northwestern University - Kellogg School of Management ( email )

2001 Sheridan Road
Evanston, IL 60208
United States

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