Did changing primary care delivery models change performance? A population based study using health administrative data
Bibliographic record
Abstract
BACKGROUND: Primary care reform in Ontario, Canada started with the introduction of new enrollment models, the two largest of which are Family Health Networks (FHNs), a capitation-based model, and Family Health Groups (FHGs), a blended fee-for-service model. The purpose of this study was to evaluate differences in performance between FHNs and FHGs and to compare performance before and after physicians joined these new primary care groups. METHODS: This study used Ontario administrative claims data to compare performance measures in FHGs and FHNs. The study population included physicians who belonged to a FHN or FHG for at least two years. Patients were included in the analyses if they enrolled with a physician in the two years after the physician joined a FHN or FHG, and also if they saw the physician in a two year period prior to the physician joining a FHN or FHG. Performance was derived from the administrative data, and included measures of preventive screening for cancer (breast, cervical, colorectal) and chronic disease management (diabetes, heart failure, asthma). RESULTS: Performance measures did not vary consistently between models. In some cases, performance approached current benchmarks (Pap smears, mammograms). In other cases it was improving in relation to previous measures (colorectal cancer screening). There were no changes in screening for cervical cancer or breast cancer after joining either a FHN or FHG. Colorectal cancer screening increased in both FHNs and FHGs. After enrolling in either a FHG or a FHN, prescribing performance measures for diabetes care improved. However, annual eye examinations decreased for younger people with diabetes after joining a FHG or FHN. There were no changes in performance measures for heart failure management or asthma care after enrolling in either a FHG or FHN. CONCLUSIONS: Some improvements in preventive screening and diabetes management which were seen amongst people after they enrolled may be attributed to incentive payments offered to physicians within FHGs and FHNs. However, these primary care delivery models need to be compared with other delivery models and fee for service practices in order to describe more specifically what aspects of model delivery and incentives affect care.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".