Evidence map›Paper›PMID 39719798›Full record

ArticleEBioMedicine2025

Reducing unnecessary preoperative testing through a comprehensive EMR based digital algorithm.

Stephen A Esper, Jennifer Holder-Murray, Katie Meister, Hsing-Hua Sylvia Lin, Alison K Bauer, Jamie Artman, Michael Garver, Amy Lukanski, Brian Scott Zuckerbraun, Oscar Marroquin and 1 more

Abstract read
In one paragraph

Article in EBioMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Stephen A EsperDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh Medical Center (UPMC).
Jennifer Holder-MurrayDepartment of Surgery, University of Pittsburgh Medical Center (UPMC).
Katie MeisterDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh Medical Center (UPMC).
Hsing-Hua Sylvia LinDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh School of Medicine.
Alison K BauerHeart and Vascular Institute, University of Pittsburgh Medical Center (UPMC).
Jamie ArtmanDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh Medical Center (UPMC).
Michael GarverUniversity of Pittsburgh Medical Center (UPMC).
Amy LukanskiWolff Center, University of Pittsburgh Medical Center (UPMC).
Brian Scott ZuckerbraunDepartment of Surgery, University of Pittsburgh Medical Center (UPMC).
Oscar MarroquinHeart and Vascular Institute, University of Pittsburgh Medical Center (UPMC).
Aman MahajanDepartment of Anesthesiology and Perioperative Medicine, University of Pittsburgh Medical Center (UPMC). Electronic address: mahajana@upmc.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe hypothesised that the implementation of an electronic medical record (EMR) embedded perioperative clinical decision support (CDS) application, Anesthesia Testing Guidelines (ATG), would result in at least a 10% reduction of unnecessary perioperative testing in patients undergoing elective surgeries.

methodsThe development and implementation of ATG occurred in several phases: 1) team development, 2) development of an embedded EMR application, 3) creation of ATG training and education toolkit, and 4) implementation involving promoting ATG through training and education, addressing challenges, and monitoring compliance. The proportions of patients with any overutilisation across 19 perioperative tests were compared between the baseline cohort and the ATG implementation cohort.

findingsThe overutilisation of perioperative tests was observed in 77.6% of the baseline cohort (n = 59,799) and 68.1% in the ATG cohort (n = 132,131), with a significant 12.2% reduction over two years of implementation (p < 0.0001). The two tests with the greatest amount of associated cost were reduced by 46% for chest X-rays and 39% for complete metabolic panels. The health system was able to reduce overall costs by 22% from baseline. Interrupted time series analysis estimated an immediate 7.5% decrease in monthly overutilisation when ATG initially launched, and it continued to decrease by 0.24% per month.

interpretationOur findings suggest CDS ATG is a successful tactic to reduce unnecessary preoperative testing while maintaining quality of care and improving cost avoidance. This type of CDS implementation approach transforms organisational behaviour and medical practices to follow defined guidelines, thereby improving the value of care.

fundingCDS ATG was supported by UPMC Department of Anesthesiology and Perioperative Medicine and UPMC Department of Finance.

Indexed as

AlgorithmsElectronic Health RecordsPreoperative CareUnnecessary ProceduresAgedDecision Support Systems, ClinicalFemaleHumansMaleMiddle AgedAnesthesiologyCost avoidancePreoperative testing guidelinesSurgery

Identifiers

PMID39719798
PMCPMC11731619

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.