Literature DB >> 32016375

Electronic health records and burnout: Time spent on the electronic health record after hours and message volume associated with exhaustion but not with cynicism among primary care clinicians.

Julia Adler-Milstein1, Wendi Zhao1, Rachel Willard-Grace2, Margae Knox2, Kevin Grumbach2.   

Abstract

OBJECTIVES: The study sought to determine whether objective measures of electronic health record (EHR) use-related to time, volume of work, and proficiency-are associated with either or both components of clinician burnout: exhaustion and cynicism.
MATERIALS AND METHODS: We combined Maslach Burnout Inventory survey measures (94% response rate; 122 of 130 clinicians) with objective, vendor-defined EHR use measures from log files (time after hours on clinic days; time on nonclinic days; message volume; composite measures of efficiency and proficiency). Data were collected in early 2018 from all primary care clinics of a large, urban, academic medical center. Multivariate regression models measured the association between each burnout component and each EHR use measure.
RESULTS: One-third (34%) of clinicians had high cynicism and 51% had high emotional exhaustion. Clinicians in the top 2 quartiles of EHR time after hours on scheduled clinic days (those above the sample median of 68 minutes per clinical full-time equivalent per week) had 4.78 (95% confidence interval [CI], 1.1-20.1; P = .04) and 12.52 (95% CI, 2.6-61; P = .002) greater odds of high exhaustion. Clinicians in the top quartile of message volume (>307 messages per clinical full-time equivalent per week) had 6.17 greater odds of high exhaustion (95% CI, 1.1-41; P = .04). No measures were associated with high cynicism. DISCUSSION: EHRs have been cited as a contributor to clinician burnout, and self-reported data suggest a relationship between EHR use and burnout. As organizations increasingly rely on objective, vendor-defined EHR measures to design and evaluate interventions to reduce burnout, our findings point to the measures that should be targeted.
CONCLUSIONS: Two specific EHR use measures were associated with exhaustion.
© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Keywords:  EHR optimization; EHR use; clinician burnout

Year:  2020        PMID: 32016375      PMCID: PMC7647261          DOI: 10.1093/jamia/ocz220

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  17 in total

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Journal:  Mayo Clin Proc       Date:  2015-12       Impact factor: 7.616

2.  Changes in Burnout and Satisfaction With Work-Life Integration in Physicians and the General US Working Population Between 2011 and 2017.

Authors:  Tait D Shanafelt; Colin P West; Christine Sinsky; Mickey Trockel; Michael Tutty; Daniel V Satele; Lindsey E Carlasare; Lotte N Dyrbye
Journal:  Mayo Clin Proc       Date:  2019-02-22       Impact factor: 7.616

3.  Optimization Sprints: Improving Clinician Satisfaction and Teamwork by Rapidly Reducing Electronic Health Record Burden.

Authors:  Amber Sieja; Katie Markley; Jonathan Pell; Christine Gonzalez; Brian Redig; Patrick Kneeland; Chen-Tan Lin
Journal:  Mayo Clin Proc       Date:  2019-02-26       Impact factor: 7.616

4.  Estimating the Attributable Cost of Physician Burnout in the United States.

Authors:  Shasha Han; Tait D Shanafelt; Christine A Sinsky; Karim M Awad; Liselotte N Dyrbye; Lynne C Fiscus; Mickey Trockel; Joel Goh
Journal:  Ann Intern Med       Date:  2019-05-28       Impact factor: 25.391

5.  Physician stress and burnout: the impact of health information technology.

Authors:  Rebekah L Gardner; Emily Cooper; Jacqueline Haskell; Daniel A Harris; Sara Poplau; Philip J Kroth; Mark Linzer
Journal:  J Am Med Inform Assoc       Date:  2019-02-01       Impact factor: 4.497

6.  Physician Burnout in the Electronic Health Record Era: Are We Ignoring the Real Cause?

Authors:  N Lance Downing; David W Bates; Christopher A Longhurst
Journal:  Ann Intern Med       Date:  2018-05-08       Impact factor: 25.391

7.  Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations.

Authors:  Brian G Arndt; John W Beasley; Michelle D Watkinson; Jonathan L Temte; Wen-Jan Tuan; Christine A Sinsky; Valerie J Gilchrist
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8.  Impact of Scribes on Physician Satisfaction, Patient Satisfaction, and Charting Efficiency: A Randomized Controlled Trial.

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9.  Electronic health record (EHR) training program identifies a new tool to quantify the EHR time burden and improves providers' perceived control over their workload in the EHR.

Authors:  Yumi T DiAngi; Lindsay A Stevens; Bonnie Halpern-Felsher; Natalie M Pageler; Tzielan C Lee
Journal:  JAMIA Open       Date:  2019-03-21

10.  Allocation of Physician Time in Ambulatory Practice: A Time and Motion Study in 4 Specialties.

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Journal:  Ann Intern Med       Date:  2016-09-06       Impact factor: 25.391

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  48 in total

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Authors:  Rebecca L Curran; Polina V Kukhareva; Teresa Taft; Charlene R Weir; Thomas J Reese; Claude Nanjo; Salvador Rodriguez-Loya; Douglas K Martin; Phillip B Warner; David E Shields; Michael C Flynn; Jonathan P Boltax; Kensaku Kawamoto
Journal:  J Am Med Inform Assoc       Date:  2020-08-01       Impact factor: 4.497

2.  Lower Likelihood of Burnout Among Family Physicians From Underrepresented Racial-Ethnic Groups.

Authors:  Montgomery Douglas; Emil Coman; Aimee R Eden; Suleiman Abiola; Kevin Grumbach
Journal:  Ann Fam Med       Date:  2021 Jul-Aug       Impact factor: 5.166

3.  Optimizing the electronic health record: An inpatient sprint addresses provider burnout and improves electronic health record satisfaction.

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Journal:  J Am Med Inform Assoc       Date:  2021-03-01       Impact factor: 4.497

4.  Reduced Cognitive Burden and Increased Focus: A Mixed-methods Study Exploring How Implementing Scribes Impacted Physicians.

Authors:  Elizabeth R Pfoh; Sandra Hong; Laura Baranek; Michael B Rothberg; Sarah Beinkampen; Anita D Misra-Hebert; Susan J Rehm; Andrea L Sikon
Journal:  Med Care       Date:  2022-04-01       Impact factor: 2.983

5.  Measuring time clinicians spend using EHRs in the inpatient setting: a national, mixed-methods study.

Authors:  Genna R Cohen; Jessica Boi; Christian Johnson; Llew Brown; Vaishali Patel
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

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.  The association between perceived electronic health record usability and professional burnout among US nurses.

Authors:  Edward R Melnick; Colin P West; Bidisha Nath; Pamela F Cipriano; Cheryl Peterson; Daniel V Satele; Tait Shanafelt; Liselotte N Dyrbye
Journal:  J Am Med Inform Assoc       Date:  2021-07-30       Impact factor: 4.497

8.  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

9.  Conceptual considerations for using EHR-based activity logs to measure clinician burnout and its effects.

Authors:  Thomas Kannampallil; Joanna Abraham; Sunny S Lou; Philip R O Payne
Journal:  J Am Med Inform Assoc       Date:  2021-04-23       Impact factor: 4.497

10.  Principles for Designing and Developing a Workflow Monitoring Tool to Enable and Enhance Clinical Workflow Automation.

Authors:  Danny T Y Wu; Lindsey Barrick; Mustafa Ozkaynak; Katherine Blondon; Kai Zheng
Journal:  Appl Clin Inform       Date:  2022-01-19       Impact factor: 2.342

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