An Economic Evaluation of the National Surgical Quality Improvement Program (NSQIP) in Alberta, Canada
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to analyze the health care costs and savings associated with quality improvement (QI) interventions initiated and implemented utilizing NSQIP. BACKGROUND: Five acute care facilities of Alberta Health Services (AHS) adopted NSQIP in 2015 for a pilot project. METHODS: The cost-savings of NSQIP were estimated from the start of NSQIP to the end of 2017 under an AHS perspective using this formula: Gross cost-savings = N * (p1 - p2) * unit cost, where N was the number of surgical patients after the intervention, p1 was the probability of event occurrence (within 30 days of surgery) before the intervention, p2 was the probability of event occurrence after the intervention, and unit cost is health care cost per event. To calculate the net cost-savings, we deducted the costs of NSQIP and its interventions from the gross cost-savings. RESULTS: The QI initiatives initiated by NSQIP to reduce surgical events had significant impacts clinically and economically. The gross cost-savings of NSQIP were estimated at $11.4 million. Subtracting the costs of NSQIP and its interventions ($2.6 million) from the gross cost-savings, the net cost-savings were $8.8 million. The return on investment ratio was 4.3, meaning that every $1.00 invested in NSQIP would bring $4.30 in returns. The sensitivity analysis showed the probability for NSQIP to be cost-saving was 95%. CONCLUSION: QI interventions initiated and implemented utilizing NSQIP appear to be effective and cost-saving for AHS. These cost-savings would be even larger if NSQIP was prolonged in the pilot sites and/or expanded to other sites across the province.
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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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".