A scoping review of costing methodologies used to assess interventions for underserved pregnant people and new parents
Bibliographic record
Abstract
BACKGROUND: Lack of evidence about the long-term economic benefits of interventions targeting underserved perinatal populations can hamper decision making regarding funding. To optimize the quality of future research, we examined what methods and costs have been used to assess the value of interventions targeting pregnant people and/or new parents who have poor access to healthcare. METHODS: We conducted a scoping review using methods described by Arksey and O'Malley. We conducted systematic searches in eight databases and web-searches for grey literature. Two researchers independently screened results to determine eligibility for inclusion. We included economic evaluations and cost analyses of interventions targeting pregnant people and/or new parents from underserved populations in twenty high income countries. We extracted and tabulated data from included publications regarding the study setting, population, intervention, study methods, types of costs included, and data sources for costs. RESULTS: Final searches were completed in May 2024. We identified 103 eligible publications describing a range of interventions, most commonly home visiting programs (n = 19), smoking cessation interventions (n = 19), prenatal care (n = 11), perinatal mental health interventions (n = 11), and substance use treatment (n = 10), serving 36 distinct underserved populations. A quarter of the publications (n = 25) reported cost analyses only, while 77 were economic evaluations. Most publications (n = 82) considered health care costs, 45 considered other societal costs, and 14 considered only program costs. Only a third (n = 36) of the 103 included studies considered long-term costs that occurred more than one year after the birth (for interventions occurring only in pregnancy) or after the end of the intervention. CONCLUSIONS: A broad range of interventions targeting pregnant people and/or new parents from underserved populations have the potential to reduce health inequities in their offspring. Economic evaluations of such interventions are often at risk of underestimating the long-term benefits of these interventions because they do not consider downstream societal costs. Our consolidated list of downstream and long-term costs from existing research can inform future economic analyses of interventions targeting poorly served pregnant people and new parents. Comprehensively quantifying the downstream and long-term benefits of such interventions is needed to inform decision making that will improve health equity.
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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 | 0.085 | 0.332 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.011 | 0.013 |
| Bibliometrics | 0.046 | 0.042 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".