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A Markov chain model for analysis of physician workflow in primary care clinics

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

Abstract

This paper studies physician workflow management in primary care clinics using terminating Markov chain models. The physician workload is characterized by face-to-face encounters with patients and documentation of electronic health record (EHR) data. Three workflow management policies are considered: preemptive priority (stop ongoing documentation tasks if a new patient arrives); non-preemptive priority (finish ongoing documentation even if a new patient arrives); and batch documentation (start and finish documentation when the desired number of tasks is reached). Analytical formulas are derived to quantify the performance measures of three management policies, such as physician’s daily working time, patient’s waiting time, and documentation waiting time. A comparison of the results under three policies is carried out. Finally, a case study in a primary care clinic is carried out to illustrate model applicability. Such a work provides a quantitative tool for primary care physicians to design and manage their workflow to improve care quality. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Original languageEnglish
Pages (from-to)72-91
Number of pages20
JournalHealth Care Management Science
Volume24
Issue number1
Online published22 Sept 2020
DOIs
Publication statusPublished - Mar 2021
Externally publishedYes

Funding

This paper is supported in part by NSF Grant CMMI-1536987.

Research Keywords

  • Documentation
  • Face-to-face-encounter
  • Markov chain
  • Operations research
  • Physician workflow
  • Primary care

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