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Electronic Health Record Alert-Related Workload as a Predictor of Burnout in Primary Care Providers.
- Megan E Gregory, Elise Russo, and Hardeep Singh.
- Megan E. Gregory, Ph.D., Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Baylor College of Medicine, 2450 Holcombe Blvd, Suite 01Y, Houston, Texas 77021, Email: megan.gregory@bcm.edu, Phone: (713) 794-8601 ext. 10232.
- Appl Clin Inform. 2017 Jul 5; 8 (3): 686-697.
BackgroundElectronic 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 understudied.ObjectivesTo 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.MethodsA cross-sectional questionnaire and focus group of 16 PCPs at a large medical center in the southern United States.ResultsSubjective, 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.ConclusionsBurnout 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.
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