The Impact of Rural Hospital Closures and Health Service Restructuring on Provincial- and Community-Level Patterns of Hospital Admissions in New Brunswick
Bibliographic record
Abstract
In the early 2000s, the Province of New Brunswick, Canada, undertook health system restructuring, including closing some rural hospitals. We examined whether changes in geographic access to hospitals and primary care were associated with changes in patterns of hospital use. We described three measures of hospital use for ambulatory care sensitive conditions (ACSCs) among adults 75 years and younger annually during the period 2004-2013 overall, and at the community scale. We described spatial and temporal patterns in: age-standardized hospitalization rates, age-standardized incidence of hospital admissions, and rates of admissions via ambulance. Overall, rates and incidence of hospitalizations for ACSCs declined while admissions via ambulance remained largely unchanged. We observed considerable regional variation in rates between communities in 2004. This regional variation decreased over time, with rural areas demonstrating the sharpest declines. Changes in hospital service provision within individual communities had little impact on rates of ACSC admissions. Results were consistent across urban and rural communities and were robust to analyses that included older patients and those admitted for reasons other than ACSCs. Our results suggest that the restructuring and hospital closures did not result in substantial changes to regional patterns or rates of service use.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".