Changing the Use of Electronic Fetal Monitoring and Labor Support: A Case Study of Barriers and Facilitators
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Decreasing the use of continuous electronic fetal monitoring and increasing professional labor support for low-risk pregnancies are recommended by the Society of Obstetricians and Gynecologists of Canada. This study explored factors influencing the successful (and unsuccessful) introduction of an evidence-based fetal health surveillance guideline. METHODS: This qualitative case study was conducted at two tertiary and one community hospital. Data were collected in 14 clinician focus groups (51 nurses), followed by 8 interviews with nurse administrators and educators. Analysis of verbatim transcripts and unit records included coding and categorizing data to form profiles that were compared across hospitals. RESULTS: Implementation of the guideline recommendations in the hospital settings was affected by many different factors originating in the practice environment, with the potential adopters, and related to the characteristics of the guideline. The influences of these diverse factors interacted sometimes to magnify or counteract each other's effect. The physical setting, adopter concerns, and the medicolegal issues surrounding the guideline played critical roles in uptake. In addition, changes preceding the introduction of the recommendations, the institution's agenda, and nursing and medical leadership influenced the uptake of guideline recommendations. The number and experience of nurses in each setting and availability of equipment also affected guideline acceptance and use. CONCLUSIONS: When implementing best practice, it is important to identify organizational barriers to the change that will need managing by the appropriate level of administration in the organization. Careful tailoring of implementation interventions to the barriers originating with the potential adopters is also necessary. Be prepared for unanticipated effects.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it