GHIT FujiLAM II — Multi-Country Diagnostic Accuracy Study
BCHPR · GHIT Fund · FUJIFILM · ZRC Nigeria · 2024 – present
21,036-line data platform for a diagnostic accuracy study evaluating FujiLAM, Alere LAM, GeneXpert, and molecular tests across 12 sites in Cameroon and Nigeria — supporting WHO prequalification evidence for next-generation TB diagnostics.
Highlights
- 12 sites (9 Cameroon + 3 Nigeria) across 4 REDCap projects (country × project type) with 28 instruments and 500 fields per participant.
- 160+ automated data-quality queries — 91 hand-coded (Q1–Q94) plus auto-generated compulsory / validation / date-consistency / initials-consistency queries.
- Centralised query_config.py as a single source of truth for every threshold, regex, and validation rule.
- Country-specific ID pattern validation — Cameroon FC#-#### vs Nigeria ZRC#/####.
- Multi-specimen specimen tracking (sputum ×3, urine, blood, tongue swabs, X-ray) with specimen-quality validation and turnaround-time monitoring.
- Dual-country protocol harmonisation — separate exclusion criteria per country (Q-41 to Q-45) with Nigeria-only fields detected and flagged.
- Hourly production refresh (6am–6pm) with < 0.5% post-QC error rate and > 98% compulsory-field completion.
- Incremental audit logging via auto_query_tracker.db prevents query double-counting across runs.
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