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

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.

[1]  Jie Song,et al.  Design and analysis of gastroenterology (GI) clinic in Digestive Health Center of University of Wisconsin Health , 2016 .

[2]  Jingshan Li,et al.  The impact of e-visits on patient access to primary care , 2018, Health care management science.

[3]  Oguzhan Alagoz,et al.  Medical decision making: open research challenges , 2011 .

[4]  S. Burge,et al.  A Time-Motion Study of Primary Care Physicians' Work in the Electronic Health Record Era. , 2018, Family medicine.

[5]  Ben-Tzion Karsh,et al.  Development of a primary care physician task list to evaluate clinic visit workflow , 2011, BMJ quality & safety.

[6]  Jingshan Li,et al.  A System-Theoretic Approach to Modeling and Analysis of Mammography Testing Process , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Richard W. Grant,et al.  Association of Medical Scribes in Primary Care With Physician Workflow and Patient Experience , 2018, JAMA internal medicine.

[8]  David S. Matteson,et al.  Temporal and Spatiotemporal Models for Ambulance Demand , 2016 .

[9]  Jeffrey W. Herrmann,et al.  A Survey of Queuing Theory Applications in Healthcare , 2007 .

[10]  Nan Liu,et al.  The productivity and cost-efficiency of models for involving nurse practitioners in primary care: a perspective from queueing analysis. , 2012, Health services research.

[11]  Yuehwern Yih,et al.  Handbook of Healthcare Delivery Systems , 2011 .

[12]  Stacey R. Finkelstein,et al.  A new model for nurse practitioner utilization in primary care: increased efficiency and implications. , 2014, Health care management review.

[13]  Jingshan Li,et al.  Modeling and analysis of work flow and staffing level in a computed tomography division of University of Wisconsin Medical Foundation , 2012, Health care management science.

[14]  L. Dyrbye,et al.  Physician burnout: a potential threat to successful health care reform. , 2011, JAMA.

[15]  Ronald E Giachetti,et al.  A queueing network model to analyze the impact of parallelization of care on patient cycle time , 2008, Health care management science.

[16]  Christine A. Sinsky,et al.  Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties , 2016, Annals of Internal Medicine.

[17]  Jingshan Li,et al.  Joint visit in primary care clinics: Modeling, analysis, and an application study , 2018 .

[18]  William E. Stein,et al.  A stochastic model for a visit to the doctor's office , 2007, Math. Comput. Model..

[19]  Brian G. Arndt,et al.  Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations , 2017, The Annals of Family Medicine.

[20]  Ben-Tzion Karsh,et al.  The myth of standardized workflow in primary care , 2016, J. Am. Medical Informatics Assoc..

[21]  T. Bodenheimer Primary care--will it survive? , 2006, The New England journal of medicine.

[22]  M. Brandeau,et al.  Operations research and health care : a handbook of methods and applications , 2004 .

[23]  R. Hall Patient flow : reducing delay in healthcare delivery , 2006 .

[24]  Eva K. Lee,et al.  Healthcare Analytics: From Data to Knowledge to Healthcare Improvement: From Data to Knowledge to Healthcare Improvement , 2016 .

[25]  Mark Lawley,et al.  The impact of overbooking on primary care patient no-show , 2013 .

[26]  Philip A. Bain,et al.  Electronic Visits in Primary Care: Modeling, Analysis, and Scheduling Policies , 2017, IEEE Transactions on Automation Science and Engineering.

[27]  L. Green,et al.  Reducing Delays for Medical Appointments: A Queueing Approach , 2008, Oper. Res..

[28]  Christopher A. Longhurst,et al.  Rapid implementation of inpatient electronic physician documentation at an academic hospital. , 2012, Applied clinical informatics.

[29]  Thomas Bodenheimer,et al.  In Search of Joy in Practice: A Report of 23 High-Functioning Primary Care Practices , 2013, The Annals of Family Medicine.

[30]  Nan Chen,et al.  An Analytical Framework for Modeling, Analysis, and Improvement of Team Communication and Collaboration Process in Primary Care Clinics , 2019, IEEE Transactions on Automation Science and Engineering.

[31]  Diwakar Gupta,et al.  Appointment scheduling in health care: Challenges and opportunities , 2008 .

[32]  David W. Bates,et al.  Primary care physician time utilization before and after implementation of an electronic health record: A time-motion study , 2005, J. Biomed. Informatics.

[33]  Jingshan Li,et al.  On the coefficients of variation of uptime and downtime in manufacturing equipment , 2005 .

[34]  Peter H. Millard,et al.  A continuous time Markov model for the length of stay of elderly people in institutional long‐term care , 2005 .

[35]  Xiang Zhong,et al.  Workload balancing: staffing ratio analysis for primary care redesign , 2018 .

[36]  Ben-Tzion Karsh,et al.  Information Chaos in Primary Care: Implications for Physician Performance and Patient Safety , 2011, The Journal of the American Board of Family Medicine.

[37]  W. Encinosa,et al.  National estimates of the impact of electronic health records on the workload of primary care physicians , 2016, BMC Health Services Research.