Diagnostic devices in resource-limited settings often face challenges such as high costs, limited infrastructure, and inadequate training for healthcare workers. The study employed a mixed-methods approach involving design of low-cost diagnostic tools, pilot testing in five clinics, and a user satisfaction survey among healthcare workers. Pilot tests indicated an average accuracy rate of 95% for the new devices, with minimal variability across different settings. User feedback supported device usability and acceptance. The developed diagnostic tools demonstrated high performance and broad applicability in resource-limited Zambian healthcare environments. Further large-scale deployment should include continuous monitoring of device operation to ensure consistent accuracy over time. Diagnostic Devices, Resource-Limited Settings, Biomedical Engineering Innovations, Healthcare Facilities The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Nkombo et al. (2006) studied this question.