Effect of pay for performance on the management and outcomes of hypertension in the United Kingdom: interrupted time series study
Bibliographic record
Abstract
OBJECTIVE: To assess the impact of a pay for performance incentive on quality of care and outcomes among UK patients with hypertension in primary care. DESIGN: Interrupted time series. SETTING: The Health Improvement Network (THIN) database, United Kingdom. PARTICIPANTS: 470 725 patients with hypertension diagnosed between January 2000 and August 2007. INTERVENTION: The UK pay for performance incentive (the Quality and Outcomes Framework), which was implemented in April 2004 and included specific targets for general practitioners to show high quality care for patients with hypertension (and other diseases). MAIN OUTCOME MEASURES: Centiles of systolic and diastolic blood pressures over time, rates of blood pressure monitoring, blood pressure control, and treatment intensity at monthly intervals for baseline (48 months) and 36 months after the implementation of pay for performance. Cumulative incidence of major hypertension related outcomes and all cause mortality for subgroups of newly treated (treatment started six months before pay for performance) and treatment experienced (started treatment in year before January 2001) patients to examine different stages of illness. RESULTS: After accounting for secular trends, no changes in blood pressure monitoring (level change 0.85, 95% confidence interval -3.04 to 4.74, P=0.669 and trend change -0.01, -0.24 to 0.21, P=0.615), control (-1.19, -2.06 to 1.09, P=0.109 and -0.01, -0.06 to 0.03, P=0.569), or treatment intensity (0.67, -1.27 to 2.81, P=0.412 and 0.02, -0.23 to 0.19, P=0.706) were attributable to pay for performance. Pay for performance had no effect on the cumulative incidence of stroke, myocardial infarction, renal failure, heart failure, or all cause mortality in both treatment experienced and newly treated subgroups. CONCLUSIONS: Good quality of care for hypertension was stable or improving before pay for performance was introduced. Pay for performance had no discernible effects on processes of care or on hypertension related clinical outcomes. Generous financial incentives, as designed in the UK pay for performance policy, may not be sufficient to improve quality of care and outcomes for hypertension and other common chronic conditions.
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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 | 0.012 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".