The association between payment model and specialist physicians’ selection of patients with diabetes: a descriptive study
Bibliographic record
Abstract
BACKGROUND: As the number of people with chronic diseases increases, understanding the impact of payment model on the types of patients seen by specialists has implications for improving the quality and value of care. We sought to determine if there is an association between specialist physician payment model and the types of patients seen. METHODS: In this descriptive study, we used administrative data to compare demographic characteristics, illness severity and visit indication of patients with diabetes seen by fee-for-service and salary-based internal medicine and diabetes specialists in Calgary and Edmonton between April 2011 and September 2014. The study cohort included all newly referred adults with diabetes (no appointment with a specialist in prior 4 yr). Diabetes was identified using a validated algorithm that excludes gestational diabetes. RESULTS: = 5553]; risk ratio 1.17, 95% confidence interval 1.09-1.27). INTERPRETATION: Salary-based specialists were more likely to see patients with a clear indication for a specialist visit, while fee-for-service specialists were more likely to see healthier patients. Future research is needed to determine if the differences in types of patients are attributable to payment model or other provider- or system-level factors.
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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 | 0.001 | 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 | 0.001 | 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".