American Society for Enhanced Recovery and Perioperative Quality Initiative Joint Consensus Statement on Patient-Reported Outcomes in an Enhanced Recovery Pathway
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.195 | 0.199 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.007 | 0.013 |
| Research integrity | 0.009 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".