Evidence map›Paper›PMID 41229582›Full record

ArticlePlastic and reconstructive surgery. Global open2025

Implementation of Dragon Ambient Experience by Plastic Surgery Residents Improves Wellness and Decreases Burnout: A Pilot Study.

Anam J Furrukh, Rachel C Lister, Janice F Lalikos

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

3 authors.

Anam J FurrukhFrom the Department of Surgery, Division of Plastic Surgery, UMass Chan Medical School, Worcester, MA.
Rachel C ListerFrom the Department of Surgery, Division of Plastic Surgery, UMass Chan Medical School, Worcester, MA.
Janice F LalikosFrom the Department of Surgery, Division of Plastic Surgery, UMass Chan Medical School, Worcester, MA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Burnout is a significant issue for plastic surgery residents, often worsened by administrative burdens such as clinical documentation. This study examined whether the Dragon Ambient Experience (DAX), a Microsoft artificial intelligence-powered tool integrated with Epic, can reduce documentation-related burdens and enhance resident wellness by increasing efficiency in completing clinic notes. Methods: In this pilot study, 6 plastic surgery residents received a 6-month DAX license. Participants completed presurveys assessing wellness, burnout, and job satisfaction using validated tools, including the National Aeronautics and Space Administration Task Load Index (NASA-TLX) and Mini-Z scales. They also recorded weekly hours spent on documentation outside clinic hours. Postsurveys were collected after 6 months to measure changes in these metrics. Results: At baseline, 2 out of 6 participants reported understanding care plans, and 3 out of 6 were able to give patients undivided attention. The mean Mini-Z score was 2.5 (moderate burnout), and the NASA-TLX workload score was 74.64 (high mental workload). Participants spent an average of 3.6 hours per week on documentation outside clinic hours. After DAX implementation, the NASA-TLX score decreased significantly to 51.94 ( Conclusions: Our data highlighted documentation burdens on plastic surgery residents that significantly improved with the implementation of DAX, making it an important means of improving ambulatory workflow and resident wellness in plastic surgery.

Identifiers

PMID41229582
PMCPMC12604654

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Registered trials

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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.