Does pay-for-performance improve patient outcomes in acute exacerbation of COPD admissions?
Bibliographic record
Abstract
BACKGROUND: The COPD Best Practice Tariff (BPT) is a pay-for-performance scheme in England that incentivises review by a respiratory specialist within 24 hours of admission and completion of a list of key care components prior to discharge, known as a discharge bundle, for patients admitted with acute exacerbation of COPD (AECOPD). We investigated whether the two components of the COPD BPT were associated with lower 30-day mortality and readmission in people discharged following AECOPD. METHODS: Longitudinal study of national audit data containing details of AECOPD admissions in England and Wales between 01 February 2017 and 13 September 2017. Data were linked with national admissions and mortality data. Mixed-effects logistic regression, using a random intercept for hospital to adjust for clustering of patients, was used to determine the relationship between the COPD BPT criteria (combined and separately) and 30-day mortality and readmission. Models were adjusted for age, sex, socioeconomic status, length of stay, smoking status, Charlson comorbidity index, mental illness and requirement for oxygen or noninvasive ventilation during admission. RESULTS: 28 345 patients discharged from hospital following AECOPD were included. 37% of admissions conformed to the two COPD BPT criteria. No relationship was observed between BPT conforming admissions and 30-day mortality (OR: 1.09 (95% CI 0.92 to 1.29)) or readmissions (OR: 0.96 (95% CI 0.90 to 1.02)). No relationship was observed between either of the individual COPD BPT components and 30-day mortality or readmissions. However, a specialist review at any time during admission was associated with lower inpatient mortality (OR: 0.69 (95% CI 0.58 to 0.81)). CONCLUSION: Completion of the combined COPD BPT criteria does not appear associated with a reduction in 30-day mortality or readmission. However, specialist review was associated with reduced inpatient mortality. While it is difficult to argue that discharge bundles do not improve care, this analysis questions whether the pay-for-performance model improves mortality or readmissions.
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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 | 0.016 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".