Geographical variation in the provision of elective primary hip and knee replacement: the role of socio-demographic, hospital and distance variables
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.
Bibliographic record
Abstract
BACKGROUND: To explore inequalities in the provision of hip/knee replacement surgery and produce small-area estimates of provision to inform local health planning. METHODS: Hospital Episode Statistics were used to explore inequalities in the provision of primary hip/knee operations in English NHS hospitals in 2002. Multilevel Poisson regression modelling was used to estimate rates of surgical provision by socio-demographic, hospital and distance variables. GIS software was used to estimate road travel times and create hospital catchment areas. RESULTS: Rates of joint replacement increased with age before falling in those aged 80+. Women received more operations than men. People living in the most deprived areas obtained fewer hip, but more knee operations. Those in urban areas received less hip surgery, but there was no association for knee replacement. Controlling for hospital and distance measures did not attenuate the effects. Geographical variation across districts was observed with some districts showing inequality in socio-demographic factors, whereas others showed none at all. CONCLUSIONS: This study found evidence of inequalities in the provision of joint replacement surgery. However, before we can conclude that there is inequity in receipts of healthcare, future research must consider whether these patterns are explained by variations in need across socio-demographic groups.
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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 | 0.004 | 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 it