Physician Payment Mechanisms, Hospital Length of Stay and Risk of Readmission: Evidence from a Natural Experiment
Bibliographic record
Abstract
We provide an analysis of the effect of physician payment methods on their hospital patients’ length of stay and risk of readmission. To do so, we exploit a major reform implemented in Quebec (Canada) in 1999. The Quebec Government introduced an optional mixed compensation (MC) scheme for specialist physicians working in hospital. This scheme combines a fixed per diem with a reduced fee for services provided, as an alternative to the traditional fee-for-service system. We develop a model of a physician's decision to choose the MC scheme. We show that a physician who adopts this system will have incentives to increase his time per clinical service provided. We demonstrate that as long as this effect does not improve his patients’ health by more than a critical level, they will stay more days in hospital over the period. At the empirical level, we estimate a model of transition between spells in and out of hospital analog to a difference-in-differences approach. We find that the hospital length of stay of patients treated in departments that opted for the MC system increased on average by 4.2% (0.28 days). However, the risk of readmission to the same department with the same diagnosis does not appear to be overall affected by the reform.
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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 | 0.023 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".