Evidence map›Paper›PMID 41051774›Full record

ArticleJAMA network open2025

Right-Sizing Testing Before Elective Surgery for Patients With Low Risk.

Nicole M Mott, Dana Greene, Erin Kim, Valerie Mefford, Anthony Cuttitta, Faelan Jacobson-Davies, Shawna N Smith, Eve A Kerr, Anthony L Edelman, Michael Mathis and 3 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Nicole M MottNational Clinician Scholars Program, University of Michigan, Ann Arbor.
Dana GreeneMichigan Program for Value Enhancement, Ann Arbor.
Erin KimCenter for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor.
Valerie MeffordMichigan Program for Value Enhancement, Ann Arbor.
Anthony CuttittaMichigan Program for Value Enhancement, Ann Arbor.
Faelan Jacobson-DaviesCenter for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor.
Shawna N SmithUniversity of Michigan Medical School, Ann Arbor.
Eve A KerrVeterans Affairs Center for Clinical Management Research, Ann Arbor, Michigan.
Anthony L EdelmanDepartment of Anesthesiology, University of Michigan, Ann Arbor.
Michael MathisDepartment of Anesthesiology, University of Michigan, Ann Arbor.
Michael EnglesbeCenter for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor.
Hari NathanCenter for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor.
Lesly A DossettCenter for Healthcare Outcomes and Policy, University of Michigan, Ann Arbor.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Guidelines recommend against testing before low-risk surgery in healthy patients because it offers no benefit and may cause harm. However, testing remains prevalent, highlighting the need for a deimplementation strategy that can be broadly applied across health care settings. Objective: To assess the feasibility of a multifaceted, multicomponent deimplementation strategy entitled Right-Sizing Testing Before Elective Surgery (RITE-Size), hypothesizing it would be feasible to execute with 80% of milestones met on time. Design, Setting, and Participants: This quality improvement study was conducted from March 1 to August 31, 2024, at 3 hospitals of varying characteristics in Michigan. The intervention was structured into 3 phases (baseline, preparation, and active deimplementation) and further divided into 6 milestones (ie, key steps in the deimplementation process). Eligible preoperative tests included bloodwork and cardiopulmonary evaluations (eg, blood cell counts, metabolic panels, chest radiography, and electrocardiography) performed within 30 days of elective laparoscopic cholecystectomy, inguinal hernia repair, or breast lumpectomy in healthy adults. Interventions: The intervention included site visits, coaching sessions, data review, initiation of consensus processes for deimplementation, and distribution of strategy components (eg, decision support tools). Main Outcomes and Measures: The primary outcome was milestone completion. Secondary outcomes included acceptability and appropriateness, as assessed by the Acceptability of Intervention Measure (AIM) and the Intervention Appropriateness Measure (IAM). Additionally, barriers and facilitators to implementation were evaluated through semistructured interviews, along with testing rates derived from claims data. Results: A total of 203 patients (mean [SD] age, 57 [17] years; 117 [57.6%] female) who underwent procedures of interest were identified. All milestones were achieved on time. The intervention had high acceptability and appropriateness among stakeholders (median [IQR], 20 of 20 [18-20] for AIM and 20 of 20 [16-20] for IAM). Key facilitators included small, cohesive, perioperative teams and the incorporation of the intervention into policy, supported by auditing and feedback systems. Barriers included the need for ongoing education and coordination across large health care systems. Testing rates significantly decreased across all sites from 68.0% (51 of 75) to 40.3% (25 of 62) (P = .001). Conclusions and Relevance: This quality improvement study of a multifaceted, multicomponent deimplementation strategy to reduce unnecessary preoperative testing at diverse hospital sites demonstrated feasibility of expanding this work in a stepped-wedge cluster randomized trial. These results suggest that hospital systems can use this deimplementation strategy in the future to reduce unnecessary preoperative testing.

Indexed as

Elective Surgical ProceduresPreoperative CareAdultFeasibility StudiesFemaleHumansMaleMichiganMiddle AgedQuality Improvement

Identifiers

PMID41051774
PMCPMC12501813

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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.