Literature DB >> 31258965

Burnout and EHR use among academic primary care physicians with varied clinical workloads.

Brian Tran1, Abigail Lenhart1, Rachel Ross1, David A Dorr1.   

Abstract

Burnout is becoming increasingly prevalent among primary care physicians. Recent studies have attributed electronic health record (EHR) related tasks as a potential source of physician burnout. In this cross-sectional study, EHR use was compared to self-reported burnout for 107 faculty physicians at 10 university-affiliated primary care clinics. Physicians who self-reported burnout spent more time managing their inbox and in the EHR after hours. Burnout was associated with lower rates of same day chart closure, longer completion time for inbox messages, and more incomplete messages. Burnout, while related to overall workload, had a complex relationship with EHR use, which was influenced by but could not wholly explained by clinical workload. Our results suggest that burnout is less prevalent with less allocated clinical time, however, more research is necessary to identify the optimal balance between clinical duties and academic pursuits. Segmenting providers based on relative workload to determine variation within similar groups may help optimize EHR use.

Year:  2019        PMID: 31258965      PMCID: PMC6568076     

Source DB:  PubMed          Journal:  AMIA Jt Summits Transl Sci Proc


  21 in total

1.  Learning Tasks of Pediatric Providers from Electronic Health Record Audit Logs.

Authors:  Barrett Jones; Xinmeng Zhang; Bradley A Malin; You Chen
Journal:  AMIA Annu Symp Proc       Date:  2021-01-25

2.  Predicting physician burnout using clinical activity logs: Model performance and lessons learned.

Authors:  Sunny S Lou; Hanyang Liu; Benjamin C Warner; Derek Harford; Chenyang Lu; Thomas Kannampallil
Journal:  J Biomed Inform       Date:  2022-02-05       Impact factor: 6.317

3.  Primary care physicians' electronic health record proficiency and efficiency behaviors and time interacting with electronic health records: a quantile regression analysis.

Authors:  Oliver T Nguyen; Kea Turner; Nate C Apathy; Tanja Magoc; Karim Hanna; Lisa J Merlo; Christopher A Harle; Lindsay A Thompson; Eta S Berner; Sue S Feldman
Journal:  J Am Med Inform Assoc       Date:  2022-01-29       Impact factor: 4.497

4.  Characterizing styles of clinical note production and relationship to clinical work hours among first-year residents.

Authors:  Jen J Gong; Hossein Soleimani; Sara G Murray; Julia Adler-Milstein
Journal:  J Am Med Inform Assoc       Date:  2021-12-28       Impact factor: 4.497

5.  Nephrology Fellows' and Program Directors' Perceptions of Hospital Rounds in the United States.

Authors:  Suzanne M Boyle; Keshab Subedi; Kurtis A Pivert; Meera Nair Harhay; Jaime Baynes-Fields; Jesse Goldman; Karen M Warburton
Journal:  Clin J Am Soc Nephrol       Date:  2020-03-17       Impact factor: 8.237

6.  Exploring the relationship between electronic health records and provider burnout: A systematic review.

Authors:  Qi Yan; Zheng Jiang; Zachary Harbin; Preston H Tolbert; Mark G Davies
Journal:  J Am Med Inform Assoc       Date:  2021-04-23       Impact factor: 4.497

7.  What Oncologists Want: Identifying Challenges and Preferences on Diagnosis Data Entry to Reduce EHR-Induced Burden and Improve Clinical Data Quality.

Authors:  Franck Diaz-Garelli; Roy Strowd; Tamjeed Ahmed; Thomas W Lycan; Sean Daley; Brian J Wells; Umit Topaloglu
Journal:  JCO Clin Cancer Inform       Date:  2021-05

8.  The impact of time spent on the electronic health record after work and of clerical work on burnout among clinical faculty.

Authors:  Lauren A Peccoralo; Carly A Kaplan; Robert H Pietrzak; Dennis S Charney; Jonathan A Ripp
Journal:  J Am Med Inform Assoc       Date:  2021-04-23       Impact factor: 4.497

9.  Electronic Health Record Use among Ophthalmology Residents while on Call.

Authors:  Christopher P Long; Ming Tai-Seale; Robert El-Kareh; Jeffrey E Lee; Sally L Baxter
Journal:  J Acad Ophthalmol       Date:  2020-07

10.  Mining tasks and task characteristics from electronic health record audit logs with unsupervised machine learning.

Authors:  Bob Chen; Wael Alrifai; Cheng Gao; Barrett Jones; Laurie Novak; Nancy Lorenzi; Daniel France; Bradley Malin; You Chen
Journal:  J Am Med Inform Assoc       Date:  2021-06-12       Impact factor: 4.497

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