Healthcare providers’ perspectives of first-tier NIPS' implementation in Canada
Bibliographic record
Abstract
Objective This article presents an analysis of barriers and facilitators concerning the implementation of first-tier non-invasive prenatal screening (NIPS) in Canada, as identified by healthcare providers, using the Consolidated Framework for Implementation Research (CFIR). Study Design Semi-structured interviews were conducted with 16 healthcare professionals. Obstetricians-Gynecologists (OBGYN), family physicians, geneticist, midwives, and genetic counselors from 5 provinces were recruited. CFIR was used both for the interview guide and the coding dictionary. Discourse analysis was done for all interviews after data saturation was attained. Results The findings reveal a contrast in participant perspectives. While NIPS is perceived as a superior screening tool with the potential to replace traditional screening, concerns linger regarding its impact on pregnant individuals and the healthcare system. Participants acknowledge the positive perception of NIPS and its potential to replace traditional screening. They emphasize that NIPS does not address a gap in the screening pathway since other methods already detect the screened conditions. Despite facilitators like positive perceptions and increased accessibility to information, it necessitates careful consideration concerning NIPS' place in the prenatal screening pathway. Access to NIPS is considered a facilitator, potentially reducing inequalities, but widespread availability may compromise care for some pregnant individuals. Barriers include the lack of novelty in NIPS information and its inability to replace diagnostic tests. Conclusion Our research offers a comprehensive understanding of barriers and facilitators, aiding anticipation of potential implementation as a first-tier test and maximizing the likelihood of successful implementation. The use of CFIR to analyze the prenatal screening pathway provides a structured approach to identify possible tensions in implementing first-tier NIPS, and actionable insights. This research provides valuable insights for policymakers and decision-makers, underscoring the importance of education and deliberate consideration when determining NIPS's appropriate role in prenatal screening.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.022 | 0.007 |
| Scholarly communication | 0.013 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 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".