Production of physician services under fee‐for‐service and blended fee‐for‐service: Evidence from Ontario, Canada
Bibliographic record
Abstract
We examine family physicians' responses to financial incentives for medical services in Ontario, Canada. We use administrative data covering 2003-2008, a period during which family physicians could choose between the traditional fee for service (FFS) and blended FFS known as the Family Health Group (FHG) model. Under FHG, FFS physicians are incentivized to provide comprehensive care and after-hours services. A two-stage estimation strategy teases out the impact of switching from FFS to FHG on service production. We account for the selection into FHG using a propensity score matching model, and then we use panel-data regression models to account for observed and unobserved heterogeneity. Our results reveal that switching from FFS to FHG increases comprehensive care, after-hours, and nonincentivized services by 3%, 15%, and 4% per annum. We also find that blended FFS physicians provide more services by working additional total days as well as the number of days during holidays and weekends. Our results are robust to a variety of specifications and alternative matching methods. We conclude that switching from FFS to blended FFS improves patients' access to after-hours care, but the incentive to nudge service production at the intensive margin is somewhat limited.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".