Dataset Information

More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

ABSTRACT:

Purpose

The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload.

Methods

This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments.

Results

From the pre-COVID-19 pandemic year (May 2019 to February 2020) to the most recent study year (April 2022 to March 2023), the average time PCPs spent in the EHR per 8 hours of scheduled clinic appointments increased (+28.4 minutes, 7.8%), as did time in orders (+23.1 minutes, 58.9%), inbox (+14.0 minutes, 24.4%), chart review (+7.2 minutes, 13.0%), notes (+2.9 minutes, 2.3%), outside scheduled hours on days with scheduled appointments (+6.4 minutes, 8.2%), and on unscheduled days (+13.6 minutes, 19.9%). Primary care physicians received more patient medical advice requests (+5.4 messages, 55.5%) and prescription messages (+2.3, 19.5%) per 8 hours of scheduled clinic appointments, but fewer patient calls (-2.8, -10.5%) and results messages (-0.3, -2.7%). While total time in the EHR continued to increase in the final study year (+7.7 minutes, 2.0%), inbox time decreased slightly from the year prior (-2.2 minutes, -3.0%). Primary care physicians' average aFTE decreased 5.2% from 0.66 to 0.63 over 4 years.

Conclusions

Primary care physicians' time in the EHR continues to grow. While PCPs' inbox time may be stabilizing, it is still substantially higher than pre-pandemic levels. It is imperative health systems develop strategies to change the EHR workload trajectory to minimize PCPs' occupational stress and mitigate unnecessary reductions in effective physician workforce resulting from the increased EHR burden.

SUBMITTER: Arndt BG

PROVIDER: S-EPMC11233089 | biostudies-literature | 2024 Jan-Feb

REPOSITORIES: biostudies-literature

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Publications

More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

Arndt Brian G BG Micek Mark A MA Rule Adam A Shafer Christina M CM Baltus Jeffrey J JJ Sinsky Christine A CA

Annals of family medicine 20240101 1

<h4>Purpose</h4>The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload.<h4>Methods</h4>This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments.<h4>Results</h4>From the pre-COVID-1 ...[more]

PMID: 38253499

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Project description:BackgroundThe temporal progression and workload-related causal contributors to physician burnout are not well-understood.ObjectiveTo characterize burnout's time course and evaluate the effect of time-varying workload on burnout and medical errors.DesignSix-month longitudinal cohort study with measurements of burnout, workload, and wrong-patient orders every 4 weeks.ParticipantsSeventy-five intern physicians in internal medicine, pediatrics, and anesthesiology at a large academic medical center.Main measuresBurnout was measured using the Professional Fulfillment Index survey. Workload was collected from electronic health record (EHR) audit logs and summarized as follows: total time spent on the EHR, after-hours EHR time, patient load, inbox time, chart review time, note-writing time, and number of orders. Wrong-patient orders were assessed using retract-and-reorder events.Key resultsSeventy-five of 104 interns enrolled (72.1%) in the study. A total of 337 surveys and 8,863,318 EHR-based actions were analyzed. Median burnout score across the cohort across all time points was 1.2 (IQR 0.7-1.7). Individual-level burnout was variable (median monthly change 0.3, IQR 0.1-0.6). In multivariable analysis, increased total EHR time (β=0.121 for an increase from 54.5 h per month (25th percentile) to 123.0 h per month (75th percentile), 95%CI=0.016-0.226), increased patient load (β=0.130 for an increase from 4.9 (25th percentile) to 7.1 (75th percentile) patients per day, 95%CI=0.053-0.207), and increased chart review time (β=0.096 for an increase from 0.39 (25th percentile) to 0.59 (75th percentile) hours per patient per day, 95%CI=0.015-0.177) were associated with an increased burnout score. After adjusting for the total number of ordering sessions, burnout was not statistically associated with an increased rate of wrong-patient orders (rate ratio=1.20, 95%CI=0.76-1.89).ConclusionsBurnout and recovery were associated with recent clinical workload for a cohort of physician trainees, highlighting the elastic nature of burnout. Wellness interventions should focus on strategies to mitigate sustained elevations of work responsibilities.

Project description:ObjectiveTo understand if providers who had additional electronic health record (EHR) training improved their satisfaction, decreased personal EHR-use time, and decreased turnaround time on tasks.Materials and methodsThis pre-post study with no controls evaluated the impact of a supplemental EHR training program on a group of academic and community practice clinicians that previously had go-live group EHR training and 20 months experience using this EHR on self-reported data, calculated EHR time, and vendor-reported metrics.ResultsProviders self-reported significant improvements in their knowledge of efficiency tools in the EHR after training and doubled (significant) their preference list entries (mean pre = 38.1 [65.88], post = 63.5 [90.47], P < .01). Of the 7 EHR satisfaction variables, only 1 self-reported variable significantly improved after training: Control over my workload in the EHR (mean pre = 2.7 [0.96], post = 3.0 [1.04], P < .01). There was no significant decrease in their calculated EHR usage outside of clinic (mean pre = 0.39 [0.77] to post = 0.37 [0.48], P = .73). No significant difference was seen in turnaround time for patient calls (mean pre = 2.3 [2.06] days, post = 1.9 [1.76] days, P = .08) and results (mean before = 4.0 [2.79] days, after = 3.2 [2.33] days, P = .03).DiscussionMultiple sources of data provide a holistic view of the provider experience in the EHR. This study suggests that individualized EHR training can improve the knowledge of EHR tools and satisfaction with their perceived control of EHR workload, however this did not translate into less Clinician Logged-In Outside Clinic (CLOC) time, a calculated metric, nor quicker turnaround on in box tasks. CLOC time emerged as a potential less-costly surrogate metric for provider satisfaction in EHR work than surveying clinicians. Further study is required to understand the cost-benefit of various interventions to decrease CLOC time.ConclusionsThis supplemental EHR training session, 20 months post go-live, where most participants elected to receive 2 or fewer sessions did significantly improve provider satisfaction with perceived control over their workload in the EHR, but it was not effective in decreasing EHR-use time outside of clinic. CLOC time, a calculated metric, could be a practical trackable surrogate for provider satisfaction (inverse correlation) with after-hours time spent in the EHR. Further study into interventions that decrease CLOC time and improve turnaround time to respond to inbox tasks are suggested next steps.

Dataset Information

More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

Purpose

Methods

Results

Conclusions

Publications

More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

Similar Datasets

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