Physician Practice Style and Healthcare Costs: Evidence from Emergency Departments
Bibliographic record
Abstract
We examine the variation across emergency department (ED) physicians in their resource use and health outcomes, and the relationship between ED resource use and future healthcare costs and outcomes.Our data record the initial treating hospital, ED physician, ED billed expenditures, and all interactions with the provincial health system within the subsequent 90 days for EDs in Montreal, Canada.Physicians in Montreal rotate across shifts between simple and difficult cases, implying a quasi-random assignment of patients to physicians conditional on the choice of ED.We consider three medical conditions that present frequently in the ED and for which mistreatment can result in dramatic consequences: angina, appendicitis, and transient ischemic attacks.To control for variation across physicians in their diagnostic acumen, for each condition, our sample consists of patients with a broader set of symptoms and signs that could be indicative of the condition.We regress measures of healthcare costs on indicators for the hospital and ED physician separately by condition.We then evaluate the correlations between different measures of skill and resource use.We find strong positive correlations of physician resource use and skills across the three conditions.However, physicians with costly practice styles are often associated with worse outcomes, in terms of more ED revisits and more hospitalizations.One exception is that for patients in the angina sample, ED physicians with more spending have fewer hospitalizations.Comparisons of physician effects for the base and broader sets of conditions show that both diagnosis and disposition skills are important.
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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 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".