Spine surgery referrals redirected through a multidisciplinary care pathway: effects of nonsurgeon triage including MRI utilization
Bibliographic record
Abstract
OBJECT: The Saskatchewan Spine Pathway (SSP) was introduced to improve quality and access to care for patients with low-back and leg pain in the province. There is very limited data regarding the efficacy of nonsurgeon triage of surgical referrals. The objective of this early implementation study was to determine how the SSP affects utilization of MRI and spine surgery. METHODS: The authors performed a retrospective analysis of 87 consecutive patients with low-back and leg pain who were initially referred to a spine surgeon but were instead redirected to the SSP clinic between May 1, 2011, and November 30, 2011. The SSP clinic triaged patients into 2 groups: Group A (nonsurgical management) and Group B (referred back to the spine surgeon). The SSP classification was modified from the classification proposed by Hall et al. Pain and disability were scored by pain-related visual analog scale, modified Oswestry Disability Index, and EuroQol-5D. RESULTS: Sixty-two patients (Group A, 71.3%) were discharged after patient education, self-care advice, and/or referral for additional mechanical therapies. Although only 25 patients (Group B, 28.7%) were directed back to the surgeon, the final percentage (12.6%) offered surgery was similar to that of historic controls (15%). Total MRI utilization was significantly lower in Group A (25.8%) than Group B (92.0%) (p < 0.0001). Nonsurgeon triage captured all red flags detected by the surgeon. Patients in Group B were much more likely to have a leg-dominant pain (p = 0.0088) and had significantly higher Oswestry Disability Index (p = 0.0121) and EuroQol-5D mobility (p = 0.0484) scores. CONCLUSIONS: The SSP significantly reduced MRI utilization and referrals seen by the surgeon for nonoperative care. Although this early implementation study suggests potential for cost savings, a more rigorous analysis of outcomes, costs, and patient satisfaction is required.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".