Development of an instrument to evaluate intrapartum care quality in Senegal: evaluation quality care
Bibliographic record
Abstract
OBJECTIVE: To evaluate the reliability of direct observation for measuring intrapartum care and compare this method with clinical audits using objective criteria based on patients' medical charts. DESIGN: Cross-sectional study, data collected by two independent evaluators. SETTING: Hospital in Dakar, Senegal. PARTICIPANTS: Thirty consecutive intrapartum care episodes provided by midwives and the corresponding medical charts. Outcome Measure The presence or absence of each of twelve criteria selected on the basis of national and international norms for monitoring of labour and delivery (six criteria) and the immediate postpartum period (six criteria). RESULTS: For direct observation, the labour and delivery mean quality scores ranged from 5.34 to 5.77. In contrast, for the chart-based method, the scores ranged from 0.32 to 0.45. For postpartum care evaluated only with direct observation, the scores were also high (5.21-5.65). For direct observation, inter-evaluator agreement was high: kappa coefficients varied from 0.78 to 0.93 depending on the criterion (total score ICC = 0.74). For the chart-based method, inter-evaluator agreement was also high: 0.66 to 1 (total score ICC = 0.72). Comparison of the two methods showed strong differences by items and subscores. CONCLUSION: Using direct observation, the quality of obstetric care was high for both the monitoring of labour and delivery and postpartum care. Both measurement instruments showed high reliability. The chart-based method underestimated the quality of care because of poor medical record documentation. Medical-record-based measurement may not be appropriate for the evaluation of the quality of obstetric care in Senegal and other low-income settings.
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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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".