Across a multi-region TB programme in Cameroon, participants and specimens must be identified and matched reliably from enrolment in the field all the way through to the laboratory bench, by a distributed team working in parallel.
Hand-written and re-typed IDs caused mismatches and duplicate entries, and a distributed team generating labels in parallel risked number collisions across hundreds of sites.
I built a QR-rendering engine (reportlab/qrcode) that lays unique, site-formatted codes into print-ready PDF sheets, backed by a file-locked, multi-user auto-increment counter so concurrent operators never collide, plus a Microsoft Graph reconciliation script that matches generated codes against site usage and study data.
Scanning replaced manual ID entry across hundreds of sites, the shared counter eliminated number collisions for a distributed team, and roughly two million traceable codes were issued and reconciled against study records.