Feasibility of a multidisciplinary Transitional Pain Service in spine surgery patients to minimise opioid use and improve perioperative outcomes: a quality improvement study
Bibliographic record
Abstract
INTRODUCTION: Spine surgery patients have high rates of perioperative opioid consumption, with a chronic opioid use prevalence of 20%. A proposed solution is the implementation of a Transitional Pain Service (TPS), which provides patient-tailored multidisciplinary care. Its feasibility has not been demonstrated in spine surgery. The main objective of this study was to evaluate the feasibility of a TPS programme in patients undergoing spine surgery. METHODS: Patients were recruited between July 2020 and November 2021 at a single, tertiary care academic centre. Success of our study was defined as: (1) enrolment: ability to enrol ≥80% of eligible patients, (2) data collection: ability to collect data for ≥80% of participants, including effectiveness measures (oral morphine equivalent (OME) and Visual Analogue Scale (VAS)-perceived analgesic management and overall health) and programme resource requirements measures (appointment attendance, 60-day return to emergency and length of stay), and (3) efficacy: estimate potential programme effectiveness defined as ≥80% of patients weaned back to their intake OME requirements at programme discharge. RESULTS: Thirty out of 36 (83.3%) eligible patients were enrolled and 26 completed the TPS programme. The main programme outcomes and resource measures were successfully tracked for >80% of patients. All 26 patients had the same or lower OME at programme discharge than at intake (intake 38.75 mg vs discharge 12.50 mg; p<0.001). At TPS discharge, patients reported similar overall health VAS (pre 60.0 vs post 70.0; p=0.14), improved scores for VAS-perceived analgesic management (pre 47.6 vs post 75.6; p<0.001) and improved Brief Pain Inventory pain intensity (pre 39.1 vs post 25.0; p=0.02). CONCLUSION: Our feasibility study successfully met or exceeded our three main objectives. Based on this success and the defined clinical need for a TPS programme, we plan to expand our TPS care model to include other surgical procedures at our centre.
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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 | 0.013 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".