Pay-for-performance incentives for preventive care: views of family physicians before and after participation in a reminder and recall project (P-PROMPT).
Bibliographic record
Abstract
OBJECTIVE: The Provider and Patient Reminders in Ontario: Multi-Strategy Prevention Tools (P-PROMPT) project was designed to increase the rates of delivery of 4 targeted preventive care services to eligible patients in primary care network and family health network practices eligible for pay-for-performance incentives. DESIGN: Self-administered fax-back surveys completed before and after participation in the P-PROMPT project. SETTING: Southwestern Ontario. PARTICIPANTS: A total of 246 physicians from 24 primary care network or family health network practices across 110 different sites. INTERVENTIONS: The P-PROMPT project provided several tools and services, including physician and patient reminders, office management tools, and administrative database integration. MAIN OUTCOME MEASURES: Physicians' views about the delivery of preventive health services and pay-for-performance incentives before and after participation in the P-PROMPT project. RESULTS: The preintervention survey was completed by 86.2% (212 of 246) of physicians and the postintervention survey was completed by 53.3% (131 of 246) of physicians; 46.7% (114 of 246) of the physicians completed both surveys. Overall, 80.5% of physicians indicated that the P-PROMPT project was useful (scores of 5 or higher on a 7-point Likert scale). Patient reminder letters (89.1%), physician approval lists of eligible patients (75.6%), administrative assistance with management fees (79.8%), and annual bonus calculations (75.2%) were rated as the most useful features of the program. Compared with the preintervention survey, there were statistically significant increases in the mean agreement scores that the established target levels and bonuses provided appropriate financial incentive to substantially increase the uptake of mammography (P=.012) and Papanicolaou tests (P=.003) but not to increase uptake of annual influenza vaccination or childhood immunizations. There were statistically significant changes in the mean ratings of relying on an opportunistic approach (P<.001), increased agreement about the effectiveness of the current approach to delivery of preventive care (P<.001), and increased use of preventive management fees to recall patients (P<.001). CONCLUSION: The preventive care management program and P-PROMPT were viewed favourably by most respondents and were perceived to be useful in improving delivery of preventive health care services.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".