Priority setting in a Canadian surgical department: a case study using program budgeting and marginal analysis.
Bibliographic record
Abstract
INTRODUCTION: A key mandate of Canadian regional health authorities is to set priorities and allocate resources within a limited finding envelope. The objective in this study was to determine how resources within a surgical program in a Canadian rural hospital might be reallocated to better meet the needs of the local community. METHODS: Early in 2001, at the Canmore General Hospital, Canmore, Alta., an expert-panel working group, consisting of a community health service leader, operating-room nurse clinician, acute care head nurse and a general surgeon, assisted by a research assistant and 2 health economists carried out a program budgeting and marginal analysis project to assess multiple data inputs into the decision-making process and to develop recommendations for service expansion and resource release. They considered the cost and benefits of altering the mix of resources used, based on Headwaters Health Authority activity and financial data, and local expert opinion. RESULTS: The primary recommendation was to implement an additional surgery day per week (38 days of major surgery and 12 days of minor surgery over a 50-week year). However, the total dollars to fund such an expansion could not be released from within the Canmore budget, and additional dollars were not forthcoming from the health region. A secondary objective of implementing an additional minor surgery day every 3 weeks was pursued and the required resources were obtained. CONCLUSIONS: Due to resource constraints in health care, efforts by both clinicians and administrators should be made to better spend available resources. The marginal analysis process used in this study served as a useful framework for priority setting, which is generalizable to other surgical and nonsurgical programs in Canada.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".