Validity and reliability of criterion based clinical audit to assess obstetrical quality of care in West Africa
Bibliographic record
Abstract
BACKGROUND: In Mali and Senegal, over 1% of women die giving birth in hospital. At some hospitals, over a third of infants are stillborn. Many deaths are due to substandard medical practices. Criterion-based clinical audits (CBCA) are increasingly used to measure and improve obstetrical care in resource-limited settings, but their measurement properties have not been formally evaluated. In 2011, we published a systematic review of obstetrical CBCA highlighting insufficient considerations of validity and reliability. The objective of this study is to develop an obstetrical CBCA adapted to the West African context and assess its reliability and validity. This work was conducted as a sub-study within a cluster randomized trial known as QUARITE. METHODS: Criteria were selected based on extensive literature review and expert opinion. Early 2010, two auditors applied the CBCA to identical samples at 8 sites in Mali and Senegal (n = 185) to evaluate inter-rater reliability. In 2010-11, we conducted CBCA at 32 hospitals to assess construct validity (n = 633 patients). We correlated hospital characteristics (resource availability, facility perinatal and maternal mortality) with mean hospital CBCA scores. We used generalized estimating equations to assess whether patient CBCA scores were associated with perinatal mortality. RESULTS: Results demonstrate substantial (ICC = 0.67, 95% CI 0.54; 0.76) to elevated inter-rater reliability (ICC = 0.84, 95% CI 0.77; 0.89) in Senegal and Mali, respectively. Resource availability positively correlated with mean hospital CBCA scores and maternal and perinatal mortality were inversely correlated with hospital CBCA scores. Poor CBCA scores, adjusted for hospital and patient characteristics, were significantly associated with perinatal mortality (OR 1.84, 95% CI 1.01-3.34). CONCLUSION: Our CBCA has substantial inter-rater reliability and there is compelling evidence of its validity as the tool performs according to theory. TRIAL REGISTRATION: Current Controlled Trials ISRCTN46950658.
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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 | 0.070 | 0.189 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".