Whoʼs in the Driverʼs Seat? The Influence of Patient and Physician Enthusiasm on Regional Variation in Degenerative Lumbar Spinal Surgery
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional population-based study using administrative databases, census data, and surveys of orthopedic/neurosurgeons, family physicians (FPs) and patients in Ontario, Canada. OBJECTIVE: To determine the influence of the enthusiasm of patients, FPs, and surgeons for surgery on the regional variation in surgical rates for degenerative diseases of the lumbar spine (DDLS), such as spinal stenosis and degenerative spondylolisthesis. SUMMARY OF BACKGROUND DATA: Rates of surgery and healthcare costs for treating DDLS have been increasing. Regional variation in spinal surgical rates has been observed and it is thought that the enthusiasm of patients and physicians for surgery contributes to this variation. METHODS: Using population-based administrative databases, we included all patients aged 50 years and older who underwent DDLS surgery (i.e., decompression/laminectomy, fusion) from 2002 to 2006 and calculated standardized utilization rates across counties. We measured regional "enthusiasm for surgery" for surgeons, FPs, and patients, using responses from a province-wide survey. Small-area variation analysis and multivariate Poisson regression models were performed calculating incidence rate ratios (IRRs) controlling for county demographics, socioeconomic measures, prevalence of disease, and community resources. RESULTS: We identified 10,318 DDLS surgeries (mean age 65 years, 50.6% female). Significant regional variation was observed (extremal quotient 5.0, coefficient of variation 28.0). Counties with higher rates of surgery had higher surgeon enthusiasm for surgery (IRR: 1.26, P < 0.013), older (IRR: 2.17, P < 0.0001) male patients (IRR: 1.19, P < 0.0001), lower income (IRR: 0.89, P < 0.0015), more knowledge of official languages (IRR: 1.12, P < 0.0003), and the presence of magnetic resonance imaging scanners (IRR: 1.30, P < 0.004). FP and patient enthusiasm for surgery, physician supply, and prevalence of disease were not statistically associated with higher surgical rates. CONCLUSION: Prior studies have not addressed the role of patient enthusiasm for surgery. Although patients and FPs had variable enthusiasm for surgery, surgeon enthusiasm was the dominant potentially modifiable factor influencing surgical rates. Prevalence of disease and community resources were not related to surgical rates. Strategies targeting surgeon practices may reduce regional variation in care and improve access disparities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".