An Economic Model of Professional Doula Support in Labor in British Columbia, Canada
Bibliographic record
Abstract
INTRODUCTION: Spending on care in childbirth represents a sizable portion of health care budgets. This has engendered a growing interest in potential clinical tools that could be used to improve patient experience and population health at a lower cost. A possible such tool is continuous support in labor from a trained doula, as doula care can decrease the likelihood of cesarean birth, epidural analgesia, and assisted vaginal birth. In addition, there is some emerging evidence suggesting that involving doulas in prenatal care can reduce rates of preterm birth. METHODS: We used data on the associations between doula care and these outcomes derived from a Cochrane review of continuous labor support to create an economic model of universal doula support in the Canadian province of British Columbia. These relative risks were used to estimate procedure reductions and the resulting cost savings using data on the number of relevant procedures performed from Perinatal Services BC coupled with cost information from the Canadian Institutes for Health Information. RESULTS: For the calendar year 2013, we estimated savings in Canadian dollars (CaD) of CaD $10,428,171 (95% confidence interval [CI], $5,430,650-$14,434,740) if every low-risk birth were attended by a professional doula, not including the cost of the doula's services. Including reduction in preterm birth increases total savings to CaD $17,847,370 (95% CI, $6,772,341-$27,054,610). A professional doula providing labor support would yield an estimated savings of CaD $269.55 (95% CI, $141.70-$374.14) per low-risk birth or CaD $418.67 (95% CI, $158.87-$634.65) if including reductions in preterm birth. Any cost savings disappear at a doula reimbursement rate above CaD $418.67 per birth. DISCUSSION: There is potential to reduce health care costs while improving patient experience and population health by providing universal doula coverage. However, our results suggest that reimbursement rates for doulas would have to be lower than the current range (CaD $300-$1500).
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".