Systematic review of the measurement properties of indices of prenatal care utilization
Bibliographic record
Abstract
Abstract Background An accurate assessment of the adequacy of prenatal care utilization is critical to inform the relationship between prenatal care and pregnancy outcomes. This systematic review critically appraises the evidence on measurement properties of prenatal care utilization indices and provides recommendations about which index is the most useful for this purpose. Methods MEDLINE, EMBASE, CINAHL, and Web of Science were systematically searched from database inception to October 2018 using keywords related to indices of prenatal care utilization. No language restrictions were imposed. Studies were included if they evaluated the reliability, validity, or responsiveness of at least one index of adequacy of prenatal care utilization. We used the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist. We conducted an evidence synthesis using predefined criteria to appraise the measurement properties of the indices. Results From 2664 studies initially screened, 13 unique studies evaluated the measurement properties of at least one index of prenatal care utilization. Most of the indices of adequacy of prenatal care currently used in research and clinical practice have been evaluated for at least some form of reliability and/or validity. Evidence about the responsiveness to change of these indices is absent from these evaluations. The Adequacy Perinatal Care Utilization Index (APNCUI) and the Kessner Index are supported by moderate evidence regarding their reliability, predictive and concurrent validity. Conclusion The scientific literature has not comprehensively reported the measurement properties of commonly used indices of prenatal care utilization, and there is insufficient research to inform the choice of the best index. Lack of strong evidence about which index is the best to measure prenatal care utilization has important implications for tracking health care utilization and for formulating prenatal care recommendations.
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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 | 0.032 | 0.176 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".