Caesarean sections and private insurance: systematic review and meta-analysis
Bibliographic record
Abstract
Objective Financial incentives associated with private insurance may encourage healthcare providers to perform more caesarean sections. We therefore sought to determine the association of private insurance and odds of caesarean section. Design Systematic review and meta-analysis. Data sources MEDLINE, Embase and The Cochrane Library from the first year of records through August 2016. Eligibility criteria We included studies that reported data to allow the calculation of OR of caesarean section of privately insured as compared with publicly insured women. Outcomes The prespecified primary outcome was the adjusted OR of births delivered by caesarean section of women covered with private insurance as compared with women covered with public insurance. The prespecified secondary outcome was the crude OR of births delivered by caesarean section of women covered with private insurance as compared with women covered with public insurance. Results Eighteen articles describing 21 separate studies in 12.9 million women were included in this study. In a meta-analysis of 13 studies, the adjusted odds of delivery by caesarean section was 1.13 higher among privately insured women as compared with women with public insurance coverage (95% CI 1.07 to 1.18) with no relevant heterogeneity between studies (τ 2 =0.006). The meta-analysis of crude estimates from 12 studies revealed a somewhat more pronounced association (pooled OR 1.35, 95% CI 1.27 to 1.44) with no relevant heterogeneity between studies (τ 2 =0.011). Conclusions Caesarean sections are more likely to be performed in privately insured women as compared with women using public health insurance coverage. Although this effect is small on average and variable in its magnitude, it is present in all analyses we performed.
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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) | 0.008 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".