Walk the Talk: The Transforming Journey of Facility‐Based Death Review Committee from Stillbirths to Neonates
Bibliographic record
Abstract
BACKGROUND: Facility-based death review committee (DRC) of neonatal deaths and stillbirths can encourage stakeholders to enhance the quality of care during the antenatal period and labour to improve birth outcomes. To understand the benefits and impact of the DRCs, this study was aimed at exploring the DRC members' perception about the role and benefits of the newly developed facility-based DRCs in five pilot hospitals in Jordan, to assess women empowerment, decision-making process, power dynamics, culture and genderism as contributing factors for deaths, and impact of COVID-19 lockdown on births. METHODS: A descriptive study of a qualitative design-using focus group discussions-was conducted after one year of establishing DRCs in 5 pilot large hospitals. The number of participants in each focus group ranged from 8 to10, and the total number of participants was 45 HCPs (nurses and doctors). Questions were consecutively asked in each focus group. The moderator asked the main questions from the guide and then used probing as needed. A second researcher observed the conversation and took field notes. RESULTS: Overall, there was an agreement among the majority of DRC members across all hospitals that the DRC was successful in identifying the exact cause of neonatal deaths and stillbirths as well as associated modifiable factors. There was also a consensus that the DRC contributed to an improvement in health services provided for pregnant women and newborns as well as protecting human rights and enabling women to be more interdependent in taking decisions related to family planning. Moreover, the DRC agreed that a proportion of the neonatal deaths and stillbirths occurring in the hospitals could have been prevented if adequate antenatal care was provided and some traditional harmful practices were avoided. CONCLUSIONS: Facility-based neonatal death review audit is practical and can be used to identify exact causes of maternal and neonatal deaths and is a valuable tool for hospital quality indicators. It can also change the perception and practice of health care providers, which may be reflected in improving the quality of provided healthcare services.
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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 | 0.049 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.010 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.022 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".