Reduced Mortality with Hospital Pay for Performance in England
Bibliographic record
Abstract
BACKGROUND: Pay-for-performance programs are being adopted internationally despite little evidence that they improve patient outcomes. In 2008, a program called Advancing Quality, based on the Hospital Quality Incentive Demonstration in the United States, was introduced in all National Health Service (NHS) hospitals in the northwest region of England (population, 6.8 million). METHODS: We analyzed 30-day in-hospital mortality among 134,435 patients admitted for pneumonia, heart failure, or acute myocardial infarction to 24 hospitals covered by the pay-for-performance program. We used difference-in-differences regression analysis to compare mortality 18 months before and 18 months after the introduction of the program with mortality in two comparators: 722,139 patients admitted for the same three conditions to the 132 other hospitals in England and 241,009 patients admitted for six other conditions to both groups of hospitals. RESULTS: Risk-adjusted, absolute mortality for the conditions included in the pay-for-performance program decreased significantly, with an absolute reduction of 1.3 percentage points (95% confidence interval [CI], 0.4 to 2.1; P=0.006) and a relative reduction of 6%, equivalent to 890 fewer deaths (95% CI, 260 to 1500) during the 18-month period. The largest reduction, for pneumonia, was significant (1.9 percentage points; 95% CI, 0.9 to 3.0; P<0.001), with nonsignificant reductions for acute myocardial infarction (0.6 percentage points; 95% CI, -0.4 to 1.7; P=0.23) and heart failure (0.6 percentage points; 95% CI, -0.6 to 1.8; P=0.30). CONCLUSIONS: The introduction of pay for performance in all NHS hospitals in one region of England was associated with a clinically significant reduction in mortality. As compared with a similar U.S. program, the U.K. program had larger bonuses and a greater investment by hospitals in quality-improvement activities. Further research is needed on how implementation of pay-for-performance programs influences their effects. (Funded by the NHS National Institute for Health Research.).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".