Determinants of hospitalisation rates: does primary health care play a role?
Bibliographic record
Abstract
OBJECTIVE: To analyse the influence of rates of general practitioner visits on rates of hospitalisations. DESIGN: Ecological cross-sectional study of factors influencing hospitalisation rates. Aggregated data on primary care centre area level. SETTING: The county of Ostergötland, Sweden, with 3 hospital districts and 41 primary health care centres, and the hospital district of Jönköping in the county of Jönköping, Sweden, with 11 primary health care centres. OUTCOME MEASURE: Hospitalisation rates. RESULTS: Age and rates of outpatient hospital visits were the most important factors explaining the variation in rates of hospitalisations between the primary health care centre areas. Hospital districts, socioeconomic factors and rates of GP visits also influenced the rates of hospitalisations. CONCLUSION: When evaluating the influence of primary health care on the rates of hospitalisations, both socioeconomic factors and health care structure must be taken into consideration. Doing this, the rates of GP visits correlated negatively with the rates of hospitalisations.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".