Evaluation of the impact of program budgeting and marginal analysis in Vancouver Island Health Authority
Bibliographic record
Abstract
OBJECTIVE: The objective of this research was to provide further insights into the ability of Program Budgeting and Marginal Analysis (PBMA) to help health care decision-makers in deciding where to allocate scarce resources so as to best meet their organizational objectives. METHODS: We report on a case study of PBMA implementation. The main source of information was two sets of semi-structured evaluation interviews conducted with senior decision-makers after each of the first two years of PBMA implementation in Vancouver Island Health Authority (VIHA), Canada. These interviews were analysed thematically, with initial coding based upon themes that had been identified in the previous stage of the research. RESULTS: Many of the initial problems with PBMA implementation resolved themselves over time as participants became more familiar with the process. However, some problems needed to be addressed explicitly through changes in procedures. Establishing procedures for handling 'must-dos' (i.e. spending priorities, that are externally mandated) did not replace the need to define explicitly the extent of the organization's discretionary spending authority. CONCLUSION: Faced with claims that typically outstrip available resources, health care decision-makers need a process to guide allocation decisions. PBMA has demonstrated at VIHA an ability to handle some of the key issues associated with this challenge. Our analysis has produced lessons that should facilitate future implementation but has also shown that resource allocation criteria selection and the extent of executive discretion are likely to be ongoing challenges.
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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 | 0.152 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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".