A data envelopment analysis approach for measuring the efficiency of Canadian acute care hospitals
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Data envelopment analysis is a methodology particularly well-suited to measuring the efficiency of hospitals because it is able to accommodate multiple heterogeneous inputs and outputs in order to model the complex relationships that exist within them. This research uses data envelopment analysis to develop a model of Canadian hospital production efficiency in collaboration with the Canadian Institute for Health Information. The model is intended to illustrate the utility of data envelopment analysis as a hospital performance measurement tool for Canadian Institute for Health Information and to augment their current hospital performance indicators. The model measures the overall production efficiency of acute care hospitals using labour and capital inputs together with outputs measuring inpatient and outpatient activity. The model also includes non-discretionary variables adjusting for case-mix variations among the hospitals. The model is extensively validated and identifies a set of highly referenced, efficient hospitals ideal for the establishment of best practices.
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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 | 0.044 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.008 | 0.002 |
| 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 it