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Record W4412846463 · doi:10.1111/jgs.70027

Anesthesiologists' and Surgeons' Perceptions of the Impact of the American College of Surgeons Geriatric Verification Program on Co‐Management of Older Surgical Patients: A Qualitative Mixed Methods Analysis

2025· article· en· W4412846463 on OpenAlexaff
Ahmed Yousef, Maria Moustaqim‐Barrette, Matthew B. Allen, Angela M. Bader, Rachelle Bernacki, Zara Cooper, Houman Javedan, David L. Hepner

Bibliographic record

VenueJournal of the American Geriatrics Society · 2025
Typearticle
Languageen
FieldMedicine
TopicFrailty in Older Adults
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsMedicineAmerican society of anesthesiologistsGeriatricsFamily medicineGerontologyMedical educationSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: The American College of Surgeons (ACS) published the Geriatric Surgery Vlerification (GSV) program in 2019, establishing standards to improve geriatric care perioperatively. A multidisciplinary approach to the management of these patients aims to optimize preoperative health, mitigate perioperative complications, and provide valuable insights in terms of postoperative expectations for recovery. At Brigham and Women's Hospital (BWH), the first major academic hospital to be verified by the ACS, implementation of GSV standards has included a collaborative effort by a team including anesthesiologists, geriatricians, nurses, and surgical clinicians. Our novel study investigating clinician perceptions on the impact of this co-management program at BWH will serve to inform other hospitals that are in the process of or considering implementation of GSV. PARTICIPANTS AND SETTING: Participants included 20 anesthesiologists who completed surveys and 22 clinicians (anesthesiologists, geriatricians, and surgeons) who participated in interviews at BWH. METHODS: We used a convergent mixed-methods design. Quantitative surveys assessed exposure to geriatric co-management and perceived practice changes. Semi-structured interviews explored clinician experiences. Survey items covered demographics, perioperative decision making, and barriers to implementation. Interviews were transcribed and analyzed using inductive content analysis. RESULTS: Ninety-five percent of surveyed anesthesiologists reported modifying care based on geriatric recommendations. Changes included anesthesia technique, medication choices, monitoring strategies, and attention to goals-of-care discussions. Ninety percent said geriatric input influenced their preoperative communication, and 85% indicated documentation of goals of care informed anesthesia planning. Interview themes included enhanced advance care planning, detection of vulnerability, alignment with patient goals, reinforcement of best practices, and improved interdisciplinary communication. Limited access to geriatric consultation was the primary barrier to broader implementation. CONCLUSION: Clinicians reported favorable perceptions of GSV implementation. These findings support broader GSV dissemination and highlight opportunities to optimize interdisciplinary collaboration. Future studies should evaluate clinical outcomes, scalability, and the role of non-geriatrician providers in geriatric co-management.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.035
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0050.004
Scholarly communication0.0040.003
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.402
Teacher spread0.385 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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