Longitudinal evaluation of physician payment reform and team-based care for chronic disease management and prevention
Bibliographic record
Abstract
BACKGROUND: We evaluated a large-scale transition of primary care physicians to blended capitation models and team-based care in Ontario, Canada, to understand the effect of each type of reform on the management and prevention of chronic disease. METHODS: We used population-based administrative data to assess monitoring of diabetes mellitus and screening for cervical, breast and colorectal cancer among patients belonging to team-based capitation, non-team-based capitation or enhanced fee-for-service medical homes as of Mar. 31, 2011 (n = 10 675 480). We used Poisson regression models to examine these associations for 2011. We then used a fitted nonlinear model to compare changes in outcomes between 2001 and 2011 by type of medical home. RESULTS: In 2011, patients in a team-based capitation setting were more likely than those in an enhanced fee-for-service setting to receive diabetes monitoring (39.7% v. 31.6%, adjusted relative risk [RR] 1.22, 95% confidence interval [CI] 1.18 to 1.25), mammography (76.6% v. 71.5%, adjusted RR 1.06, 95% CI 1.06 to 1.07) and colorectal cancer screening (63.0% v. 60.9%, adjusted RR 1.03, 95% CI 1.02 to 1.04). Over time, patients in medical homes with team-based capitation experienced the greatest improvement in diabetes monitoring (absolute difference in improvement 10.6% [95% CI 7.9% to 13.2%] compared with enhanced fee for service; 6.4% [95% CI 3.8% to 9.1%] compared with non-team-based capitation) and cervical cancer screening (absolute difference in improvement 7.0% [95% CI 5.5% to 8.5%] compared with enhanced fee for service; 5.3% [95% CI 3.8% to 6.8%] compared with non-team-based capitation). For breast and colorectal cancer screening, there were no significant differences in change over time between different types of medical homes. INTERPRETATION: The shift to capitation payment and the addition of team-based care in Ontario were associated with moderate improvements in processes related to diabetes care, but the effects on cancer screening were less clear.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".