Geographic variation in health services use in Nova Scotia.
Bibliographic record
Abstract
To further our understanding of factors underlying geographic variation in health and the potential role of availability of and access to health services, we sought to quantify the geographic variation in health services use in the province of Nova Scotia. For the period 1996 to 1999 we examined the variation in the use of health services across 64 geographic areas in conjunction with health and socio-economic factors, using multilevel methods and empirical Bayesian estimates based on provincial physician billings and hospital separation records. We revealed moderate geographic variation in the use of family physician services and large variation in specialist and hospital services. In the two urban centres, Metropolitan Halifax and the Cape Breton Regional Municipality, use of specialist services was respectively 26.24% and 15.59% higher than the provincial average, and use of hospital services was respectively 21.55% and 37.67% higher. Geographic areas in which residents had better health were characterized by more use of family physician services and reduced use of specialist and hospital services. These associations seem to support policy strategies that aim to improve health and to reduce health care costs by investing in prevention and primary health care, and they highlight the potential implications of the shortage of family physicians across Canada.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".