Assessing Infrastructure and Workforce Predispositions for Nigeria’s National Health Logistics Management Information System Adoption

Abstract

Background: The success of public health interventions in developing countries is often hindered by poor data quality and fragmented reporting systems. Nigeria’s National Health Logistics Management Information System (NHLMIS) was developed to digitize supply chain data, yet its success depends on the intersection of infrastructure and workforce readiness. This study evaluates pre-implementation readiness among health workers to inform evidence-based rollout strategies.
Methods: A cross-sectional descriptive survey was conducted in 2019 among 514 health facility representatives across four states: Kogi (n=175), Taraba (n=143), Cross River (n=99), and Kano (n=97). Data were collected via a paper-based tool prior to the NHLMIS training to capture authentic predispositions. A digital readiness index (0–4) was constructed based on personal and facility hardware ownership, mobile phone access, and prior training. Data was analyzed using descriptive statistics and cross-tabulations in Python.
Results: High individual readiness was observed, with 92.1% mobile phone ownership and 62.5% having prior computer training. However, a significant institutional gap exists; only 40.1% of facilities possessed a functional computer. Despite high mobile penetration, 64.6% of participants preferred computer-based data entry, citing a superior user interface (55.4%) as the primary driver. The readiness index revealed disparities by facility level (Tertiary: 2.58 vs. Primary: 2.21) and ownership (Private: 3.12 vs. Public: 2.31).
Conclusion: The study identifies a "readiness paradox" where health workers possess the necessary skills and personal tools, but lack the institutional hardware required for sustained digital reporting. To ensure the sustainability of digitized systems in resource-constrained settings, implementation must move beyond software training to prioritize hardware availability at all levels of health facilities and a software with optimized mobile interfaces for complex logistics tasks. These findings provide a blueprint for closing the last mile infrastructure gap in digital health transitions.