Introduction Diabetes mellitus accounts for a significant share of morbidity and mortality in ages 30–70 years worldwide. In sub-Saharan Africa, diabetes care is often suboptimal for reasons ranging from health system weaknesses to patient illiteracy and non-compliance with recommendations. This study explores the potential costs and health benefits of optimising care for uncomplicated type 2 diabetes in Lagos State, Nigeria. Methods Longitudinal data on medical care patterns and resource use (consultations, medications, diagnostics and lifestyle counselling) over a 1-year period were collected retrospectively from 84 health facilities in Lagos. Medical resource prices were obtained from a subsample of 26 facilities. Patient care gaps were assessed by comparing actual journeys to official diabetes management guidelines. Mixed-effect regression analyses were employed to explore the impact of care elements on blood glucose control and model the potential complications averted if all patients received recommended care, with extrapolation to the entire Lagos population. Results Data from 642 patients with uncomplicated type 2 diabetes were analysed. A one-unit increase in consultation score (a measure of the adequacy of consultation visits) and having health insurance coverage were linked to 47-unit and 29-unit lower blood glucose levels, respectively. Optimising diabetes care requires US3716 per patient annually, totalling US2. 1 billion statewide, with medications comprising 97% of costs. Enhanced care could reduce stroke and myocardial infarction by 2% (12 675 cases) and 4% (22 282 cases) over 7 years, respectively, at a cost of US61 492 per complication averted. Conclusions The investment required to optimise diabetes care in Lagos is currently unfeasible in the existing approaches. There is a need to explore innovative financing and delivery options, including digital value-based care interventions and cost-saving care approaches such as pooled medication procurement, while also investing in local medicines production capacity and expansion of the health insurance coverage.
Ifeanyichi et al. (Fri,) studied this question.