Provider-Initiated Pay-for-Performance in a Clinically Integrated Hospital Network
Bibliographic record
Abstract
Long Island Health Network developed a provider-initiated pay-for-performance (PI-PFP) program beginning in 2004 and operated by 10 clinically integrated hospitals. The PI-PFP administrative processes, length of stay, patient satisfaction, and Hospital Quality Alliance measures are elaborated. PI-PFP has evolved over time and supports best practice sharing. We document how the risk amount is determined and then allocated to the Network and the individual hospitals based on performance, and we quantify the success of the program in achieving the goal of improved performance. A PI-PFP can prepare physicians and management for pay-for-performance or value-based purchasing programs operated by payers. Being self-administered, such a program can go beyond payer-run programs to focus attention on issues that are considered important by the hospitals and medical staffs, and that may not be feasible to measure or to include in a mandatory payer-run program.
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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 | 0.012 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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 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".