Electronic Health Record Alert-Related Workload as a Predictor of Burnout in Primary Care Providers

Megan E. Gregory; Elise Russo; Hardeep Singh

doi:10.4338/ACI-2017-01-RA-0003

Applied Clinical Informatics, Table of Contents

Appl Clin Inform 2017; 08(03): 686-697
DOI: 10.4338/ACI-2017-01-RA-0003

Research Article

Schattauer GmbH

Electronic Health Record Alert-Related Workload as a Predictor of Burnout in Primary Care Providers

Authors

Megan E. Gregory

¹Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX

²Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX
Elise Russo

¹Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX

²Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX
Hardeep Singh

¹Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX

²Section of Health Services Research, Department of Medicine, Baylor College of Medicine, Houston, TX

Abstract

Summary

Background: Electronic health records (EHRs) have been shown to increase physician workload. One EHR feature that contributes to increased workload is asynchronous alerts (also known as inbox notifications) related to test results, referral responses, medication refill requests, and messages from physicians and other health care professionals. This alert-related workload results in negative cognitive outcomes, but its effect on affective outcomes, such as burnout, has been under-studied.

Objectives: To examine EHR alert-related workload (both objective and subjective) as a predictor of burnout in primary care providers (PCPs), in order to ultimately inform interventions aimed at reducing burnout due to alert workload.

Methods: A cross-sectional questionnaire and focus group of 16 PCPs at a large medical center in the southern United States.

Results: Subjective, but not objective, alert workload was related to two of the three dimensions of burnout, including physical fatigue (p = 0.02) and cognitive weariness (p = 0.04), when controlling for organizational tenure. To reduce alert workload and subsequent burnout, participants indicated a desire to have protected time for alert management, fewer unnecessary alerts, and improvements to the EHR system.

Conclusions: Burnout associated with alert workload may be in part due to subjective differences at an individual level, and not solely a function of the objective work environment. This suggests the need for both individual and organizational-level interventions to improve alert workload and subsequent burnout. Additional research should confirm these findings in larger, more representative samples.

Citation: Gregory ME, Russo E, Singh H. Electronic health record alert-related workload as a predictor of burnout in primary care providers. Appl Clin Inform 2017; 8: 686–697 https://doi.org/10.4338/ACI-2017-01-RA-0003

Keywords

Electronic health records - workload - burnout - health information technology - safety

Full Text

References

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