Seasonality of service provision in hip and knee surgery: A possible contributor to waiting times? A time series analysis
Bibliographic record
Abstract
BACKGROUND: The question of how best to reduce waiting times for health care, particularly surgical procedures such as hip and knee replacements is among the most pressing concern of the Canadian health care system. The objective of this study was to test the hypothesis that significant seasonal variation exists in the performance of hip and knee replacement surgery in the province of Ontario. METHODS: We performed a retrospective, cross-sectional time series analysis examining all hip and knee replacement surgeries in people over the age of 65 in the province of Ontario, Canada between 1992 and 2002. The main outcome measure was monthly hospitalization rates per 100,000 population for all hip and knee replacements. RESULTS: There was a marked increase in the rate of hip and knee replacement surgery over the 10-year period as well as an increasing seasonal variation in surgeries. Highly significant (Fisher Kappa = 16.05, p < 0.01; Bartlett-Kolmogorov-Smirnov Test = 0.31, p < 0.01) and strong (R2Autoreg = 0.85) seasonality was identified in the data. CONCLUSION: Holidays and utilization caps appear to exert a significant influence on the rate of service provision. It is expected that waiting times for hip and knee replacement could be reduced by reducing seasonal fluctuations in service provision and benchmarking services to peak delivery. The results highlight the importance of system behaviour in seasonal fluctuation of service delivery.
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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 | 0.012 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".