Evidence map›Paper›PMID 40656379›Full record

ArticleCureus2025

Reducing Physician Burnout Through Workflow Redesign: A Quality-Improvement Initiative.

Jennifer Goebel, Jessica Sidle, Alma Aspiras, Leah Fow, Molly McCann-Pineo, Timmy Li

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jennifer GoebelEmergency Department, Northwell Health, New Hyde Park, USA.
Jessica SidleEmergency Department, Northwell Health, New Hyde Park, USA.
Alma AspirasCase Management, Northwell Health, New Hyde Park, USA.
Leah FowInternal Medicine, Northwell Health, New Hyde Park, USA.
Molly McCann-PineoStatistics, Northwell Health, New Hyde Park, USA.
Timmy LiStatistics, Northwell Health, New Hyde Park, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction Staff well-being is a critical element in any healthcare organization's framework. Improving provider and staff well-being is increasingly recognized as essential to high-quality care. Burnout among healthcare workers is often driven by excessive administrative demands, inefficient workflows, and time-consuming clerical tasks. These burdens take time away from meaningful patient interactions and clinical decision-making. At Huntington Hospital, clerical workload, especially tasks related to electronic health records (EHRs) and manual documentation, was identified as a key source of stress. To better understand the contributors to burnout, the hospital administered the Maslach Burnout Inventory (MBI) to all hospitalists. The MBI evaluates emotional exhaustion, depersonalization, and reduced personal accomplishment, offering a comprehensive assessment of professional well-being. Method To address this issue, a multi-disciplinary wellness learning community was formed to identify and implement evidence-based strategies to support staff well-being. The hospitalist group unanimously chose to focus on improving the workflow for the 3122 form, a handwritten discharge document required for patients transitioning to assisted living facilities. This form included evaluations of Activities of Daily Living (ADLs), therapy needs, home care requirements, and a medication list-all of which had to be completed manually by physicians. After multiple discussions with social work, case management, and peer institutions, it was decided that social workers would complete the sections of the form within their scope, such as ADLs and support needs. Medication lists were printed directly from the electronic medical record (EMR) and attached to the form to improve accuracy and efficiency. Hospitalists reviewed the completed form before it was submitted. This new workflow was piloted on one unit, with interest quickly spreading to other teams. Results With an 83% response rate to the MBI among hospitalists (33 out of 40 hospitalists), results revealed that workload was the primary driver of burnout. Following the workflow redesign, a two-question survey was conducted with hospitalists to assess the impact of the intervention. The survey asked physicians whether removing the 3122 form as a physician task had decreased their workload and whether they supported further collaborations with the Wellness Learning Community. 76% of respondents (n=21) agreed or strongly agreed that the change reduced their workload. An equal percentage supported ongoing efforts with the Wellness Learning Community to develop future process improvements and well-being initiatives. Conclusion This project highlights how small, targeted workflow changes can have a meaningful impact on clinician well-being. By reducing administrative burden and aligning task responsibility with appropriate team members, physicians were able to redirect time and energy toward patient care. The shift from handwritten documentation to EMR-generated materials also improved efficiency and reduced the risk of transcription errors. Interdisciplinary collaboration played a key role in the project's success. By engaging social work, case management, and frontline providers in the process, the hospital was able to design a more sustainable and effective solution. Focusing on staff well-being through operational redesign promotes a more resilient, satisfied, and safer healthcare workforce.

Indexed as

administrative burdeninterdisciplinary collaborationpatient safetyphysician well-beingquality improvementworkflow optimizationwork-related burnout

Identifiers

PMID40656379
PMCPMC12253977

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.