Challenges in economic evaluations in obstetric care: a scoping review and expert opinion
Bibliographic record
Abstract
OBJECTIVE: The aim of this study is to identify items of economic evaluation guidelines that are frequently not complied within obstetric economic evaluations and to search for reasons for non-adherence. DESIGN: Scoping review and qualitative study. SETTING: Literature on economic evaluations in obstetric care and interviews with experts. POPULATION OR SAMPLE: The sample included 229 scientific articles and five experts. METHODS: A systematic literature search was performed. All types of literature about economic evaluations in obstetric care were included. The adherence to guidelines was assessed and articles were qualitatively analysed on additional information about reasons for non-adherence. Issues that arose from the scoping review were discussed with experts. MAIN OUTCOME MEASURES: Adherence to guideline items of the included economic evaluations studies. Analytical themes describing reasons for non-adherence, resulting from qualitative analysis of articles and interviews with experts. RESULTS: A total of 184 economic evaluations and 45 other type of articles were included. Guideline items frequently not complied with were time horizon, type of economic evaluation and effect measure. Reasons for non-adherence had to do with paucity of long-term health data and assessing and combining outcomes for mother and child resulting from obstetric interventions. CONCLUSIONS: This study identified items of guidelines that are frequently not complied with and the reasons behind this. The results are a starting point for a broad consensus building on how to deal with these challenges that can result in special guidance for the conduct of economic evaluations in obstetric care. TWEETABLE ABSTRACT: Non-adherence to guidelines in obstetric economic evaluation studies: the difficulties in detail.
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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 | 0.547 | 0.783 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.021 | 0.026 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.023 | 0.023 |
| Open science | 0.008 | 0.011 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".