ArticleCureus2026
Electronic Health Record-Related Burnout: Implementing a Data-Driven Quality Improvement Intervention for Ambulatory Providers After an Electronic Health Record Transition.
Article in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Electronic health records (EHRs) have improved healthcare delivery but have also introduced workflow inefficiencies that contribute to clinician burnout. After-hours EHR use has been identified as a key contributor, particularly among ambulatory providers. Objectives To evaluate the impact of a targeted EHR optimization intervention on self-reported EHR-related burnout and perceived efficiency among ambulatory providers following EHR implementation. Methods We conducted a quality improvement interventional study among ambulatory providers after transition to a new EHR. Self-reported EHR-related burnout and user experience outcomes were assessed using pre- and post-optimization surveys. Objective EHR event log data were used to evaluate after-hours EHR activity and efficiency metrics. Descriptive comparisons were performed to evaluate changes in perceived efficiency and after-hours EHR use. Results A total of 60/67 (90%) providers participated, with 57/60 (95%) completing the optimization training, and approximately 37% (22/60) were primary care providers (PCPs). Baseline self-reported EHR-related burnout was common. Following the intervention, most providers who initially reported burnout noted improvement, and nearly all participants reported increased efficiency in EHR use. Providers with higher after-hours EHR use were more likely to report burnout, with PCPs reporting greater after-hours EHR burden compared to non-PCPs. Conclusion EHR-related burnout remains prevalent among ambulatory providers, particularly those with substantial after-hours EHR use. Targeted EHR optimization interventions may improve perceived efficiency and reduce burnout. Further studies with more robust methodologies are needed to better quantify these effects.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.