Decision-making and evidence use during the process of prenatal record review in Canada: a multiphase qualitative study
Bibliographic record
Abstract
BACKGROUND: Prenatal records are potentially powerful tools for the translation of best-practice evidence into routine prenatal care. Although all jurisdictions in Canada use standardized prenatal records to guide care and provide data for health surveillance, their content related to risk factors such as maternal smoking and alcohol use varies widely. Literature is lacking on how prenatal records are developed or updated to integrate research evidence. This multiphase project aimed to identify key contextual factors influencing decision-making and evidence use among Canadian prenatal record committees (PRCs), and formulate recommendations for the prenatal record review process in Canada. METHODS: Phase 1 comprised key informant interviews with PRC leaders across 10 Canadian jurisdictions. Phase 2, was a qualitative comparative case study of PRC factors influencing evidence-use and decision-making in five selected jurisdictions. Interview data were analysed using qualitative content analysis. Phase 3 involved a dissemination workshop with key stakeholders to review and refine recommendations derived from Phases 1 and 2. RESULTS: Prenatal record review processes differed considerably across Canadian jurisdictions. PRC decision-making was complex, revealing the competing functions of the prenatal record as a clinical guide, documentation tool and data source. Internal contextual factors influencing evidence use included PRC resources to conduct evidence reviews; group composition and dynamics; perceived function of the prenatal record; and expert opinions. External contextual factors included concerns about user buy-in; health system capacities; and pressures from public health stakeholders. Our recommendations highlight the need for: broader stakeholder involvement and explicit use of decision-support strategies to support the revision process; a national template of evidence-informed changes that can be used across jurisdictions; consideration of both clinical and surveillance functions of the prenatal record; and dissemination plans to communicate prenatal record modifications. CONCLUSIONS: Decision-making related to prenatal record content involves a negotiated effort to balance research evidence with the needs and preferences of prenatal care providers, health system capacities as well as population health priorities. The development of a national template for prenatal records would reduce unnecessary duplication of PRC work and enhance the consistency of prenatal care delivery and perinatal surveillance data across Canada.
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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 | 0.084 | 0.109 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".