CLEIG: An Institutional Diagnostic Framework for Digital Health Data Governance in Africa

Methods: We developed CLEIG (Custodianship, Legal accountability, Equitable benefit-sharing, Inclusive participation, and Governance capacity) through structured conceptual policy analysis informed by institutional governance theory. The framework draws on narrative synthesis of governance literature, African policy frameworks (including the African Union Data Policy Framework and Africa CDC digital health strategies), and applied governance cases from H3Africa, DS-I Africa, Rwanda COVID-19 mobility data governance, and South African national digital health systems. The synthesis followed four iterative stages: open conceptual extraction, mechanism clustering, abductive synthesis to identify stabilised structural governance challenges, and institutional mapping using mechanism-interruption logic. 

Framework: CLEIG translates existing governance principles into five measurable institutional conditions: Custodianship (decision authority in data-origin institutions), Legal accountability (enforceable oversight and redress), Equitable benefit-sharing (fair distribution of value), Inclusive participation (binding inclusion in governance decisions), and Governance capacity (implementation infrastructure). Each domain is operationalised through a 4-point ordinal diagnostic rubric generating a governance profile vector (CLEIG-V) for identifying institutional gaps and supporting policy prioritisation. The framework is proposed as a conceptual diagnostic tool requiring empirical validation.

Implications: CLEIG provides a diagnostic tool for policy engagement and institutional design, enabling ministries of health, data protection authorities, research funders, and ethics review boards to assess governance readiness and target reforms. The framework is conceptual and requires empirical validation through inter-rater reliability testing, cross-country calibration, and criterion validity assessment.