Impact of Provider Payment Structure on Obstetric Interventions and Outcomes: A Difference-in-Differences Analysis
Bibliographic record
Abstract
OBJECTIVE: Traditionally, Canadian physicians provide care on a fee-for-service (FFS) basis; however, this model has been criticized as it incentivizes quantity of care over quality of care. Consequently, all Canadian provinces and territories have implemented some form of alternative payment plan. Evaluation of the impact of these policy changes, however, has typically focused on family physicians as opposed to specialists. METHODS: On January 1, 2004, obstetricians at the Medicine Hat Regional Hospital (MHRH) transitioned from FFS to salary. A difference-in-differences analysis was used to examine the impact of changes in obstetrician payment structure on the use of obstetric interventions and neonatal outcomes controlling for temporal trends at MHRH (intervention group) and the Chinook Regional Hospital (CRH; comparison group) from 2002 to 2005. RESULTS: Between the pre-intervention period (2002-2003) and the post-intervention period (2004-2005), the rate of cesarean delivery increased significantly at both sites. Following adjustment for time of day, day of week, and antepartum risk score, the difference-in-difference estimator demonstrated a 5.8% (95% CI 1.5-10.0) increase in cesarean deliveries performed by obstetricians at MHRH compared with cesarean deliveries done at CRH after accounting for baseline differences and temporal trends. No significant differences were observed for family physicians. No significant differences were observed for other obstetric interventions or neonatal outcomes. CONCLUSION: Under an FFS model, obstetricians are incentivized to cesarean delivery due to the increased reimbursement rate; however, the increase in cesarean deliveries at MHRH following the transition to a salary model was unexpected. This finding suggests that, in Canada, financial incentives are not a factor that explains the increasing rate of cesarean delivery.
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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 | 0.038 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.008 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".