Does supplementary prenatal nursing and home visitation reduce healthcare costs in the year after childbirth?
Bibliographic record
Abstract
AIM: This paper reports the costs of a programme of supplementary prenatal care, including healthcare costs, in the year following childbirth. BACKGROUND: Publicly funded healthcare systems have provided pregnant women with adequate medical care, but access to resources to address their non-medical needs is still an issue. To improve women's access to pregnancy-related resources, a community-based, prenatal programme involving consultations with a specialist nurse, or nurse plus a home visitor was evaluated. METHOD: A sample of 284 women who had participated in a randomized controlled trial of the prenatal care programme participated in this partial economic analysis. Women had been randomized to one of three trial arms: (1) standard care, (2) standard care plus consultations with a specialist prenatal care nurse, or (3) standard care plus nurse consultations and a home visitor. For the economic study, each woman was asked about her and her baby's use of healthcare services in the 12 months after the baby's birth. Health service utilization was multiplied by the unit cost of each service and summed to arrive at the total cost of services used. The study was undertaken in 2004. RESULTS: Supplementary prenatal care neither increased the use of health services nor resulted in savings in health spending. Compared with standard care, women in the two intervention groups made more use of family physicians and less use of paediatricians, but no significant differences in the overall costs of health care were noted. CONCLUSION: While supplementary prenatal care had no impact on costs, some benefits occurred for those at greatest risk of not accessing services. However, it would be premature to draw widespread recommendations for policy from the results of a single study. Further investment in prenatal care should continue to be accompanied by rigorous evaluation of its costs and the value that women place on the service provided.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.000 | 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".