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Record W2781203652 · doi:10.1213/ane.0000000000002758

American Society for Enhanced Recovery and Perioperative Quality Initiative Joint Consensus Statement on Patient-Reported Outcomes in an Enhanced Recovery Pathway

2017· review· en· W2781203652 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnesthesia & Analgesia · 2017
Typereview
Languageen
FieldMedicine
TopicEnhanced Recovery After Surgery
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsWorkgroupMedicinePerioperativeContext (archaeology)Delphi methodPatient-reported outcomeMEDLINEHealth careQuality managementQuality (philosophy)Best practicePatient satisfactionNursingQuality of life (healthcare)Operations managementSurgeryManagement

Abstract

fetched live from OpenAlex

Patient-reported outcomes (PROs) are measures of health status that come directly from the patient. PROs are an underutilized tool in the perioperative setting. Enhanced recovery pathways (ERPs) have primarily focused on traditional measures of health care quality such as complications and hospital length of stay. These measures do not capture postdischarge outcomes that are meaningful to patients such as function or freedom from disability. PROs can be used to facilitate shared decisions between patients and providers before surgery and establish benchmark recovery goals after surgery. PROs can also be utilized in quality improvement initiatives and clinical research studies. An expert panel, the Perioperative Quality Initiative (POQI) workgroup, conducted an extensive literature review to determine best practices for the incorporation of PROs in an ERP. This international group of experienced clinicians from North America and Europe met at Stony Brook, NY, on December 2-3, 2016, to review the evidence supporting the use of PROs in the context of surgical recovery. A modified Delphi method was used to capture the collective expertise of a diverse group to answer clinical questions. During 3 plenary sessions, the POQI PRO subgroup presented clinical questions based on a literature review, presented evidenced-based answers to those questions, and developed recommendations which represented a consensus opinion regarding the use of PROs in the context of an ERP. The POQI workgroup identified key criteria to evaluate patient-reported outcome measures (PROMs) for their incorporation in an ERP. The POQI workgroup agreed on the following recommendations: (1) PROMs in the perioperative setting should be collected in the framework of physical, mental, and social domains. (2) These data should be collected preoperatively at baseline, during the immediate postoperative time period, and after hospital discharge. (3) In the immediate postoperative setting, we recommend using the Quality of Recovery-15 score. After discharge at 30 and 90 days, we recommend the use of the World Health Organization Disability Assessment Scale 2.0, or a tailored use of the Patient-Reported Outcomes Measurement Information System. (4) Future study that consistently applies PROMs in an ERP will define the role these measures will have evaluating quality and guiding clinical care. Consensus guidelines regarding the incorporation of PRO measures in an ERP were created by the POQI workgroup. The inclusion of PROMs with traditional measures of health care quality after surgery provides an opportunity to improve clinical care.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.131
GPT teacher head0.394
Teacher spread0.264 · 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