Repeat Auditing of Primary Health-care Facilities Against Standards for Occupational Health and Infection Control: A Study of Compliance and Reliability
Bibliographic record
Abstract
BACKGROUND: The elevated risk of occupational infection such as tuberculosis among health workers in many countries raises the question of whether the quality of occupational health and safety (OHS) and infection prevention and control (IPC) can be improved by auditing. The objectives of this study were to measure (1) audited compliance of primary health-care facilities in South Africa with national standards for OHS and IPC, (2) change in compliance at reaudit three years after baseline, and (3) the inter-rater reliability of the audit. METHODS: The study analyzed audits of 60 primary health-care facilities in the Western Cape Province of South Africa. Baseline external audits in the time period 2011-2012 were compared with follow-up internal audits in 2014-2015. Audits at 25 facilities that had both internal and external audits conducted in 2014/2015 were used to measure reliability. RESULTS: At baseline, 25% of 60 facilities were "noncompliant" (audit score<50%), 48% "conditionally compliant" (score >50 < 80%), and only 27% "compliant" (score >80%). Overall, there was no significant improvement in compliance three years after baseline. Percentage agreement on specific items between internal and external audits ranged from 28% to 92% and kappa from -0.8 to 0.41 (poor to moderate). CONCLUSION: Low baseline compliance with OHS-IPC measures and lack of improvement over three years reflect the difficulties of quality improvement in these domains. Low inter-rater reliability of the audit instrument undermines the audit process. Evidence-based investment of effort is required if repeat auditing is to contribute to occupational risk reduction for health workers.
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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 | 0.061 | 0.159 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| 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".