Cost-effectiveness of a Community-based Hypertension Improvement Project (ComHIP) in Ghana: results from a modelling study

Objective To undertake a cost-effectiveness analysis of a Community-based Hypertension Improvement Project (ComHIP) compared with standard hypertension care in Ghana. Design Cost-effectiveness analysis using a Markov model. Setting Lower Manya Krobo, Eastern Region, Ghana. Intervention We evaluated ComHIP, an intervention with multiple components, including: community-based education on cardiovascular disease (CVD) risk factors and healthy lifestyles; community-based screening and monitoring of blood pressure by licensed chemical sellers and CVD nurses; community-based diagnosis, treatment, counselling, follow-up and referral of hypertension patients by CVD nurses; telemedicine consultation by CVD nurses and referral of patients with severe hypertension and/or organ damage to a physician; information and communication technologies messages for healthy lifestyles, treatment adherence support and treatment refill reminders for hypertension patients; Commcare, a cloud-based health records system linked to short-message service (SMS)/voice messaging for treatment adherence, reminders and health messaging. ComHIP was evaluated under two scale-up scenarios: (1) ComHIP as currently implemented with support from international partners and (2) ComHIP under full local implementation. Main outcome measures Incremental cost per disability-adjusted life-year (DALY) averted from a societal perspective over a time horizon of 10 years. Results ComHIP is unlikely to be a cost-effective intervention, with current ComHIP implementation and ComHIP under full local implementation costing on average US$12 189 and US$6530 per DALY averted, respectively. Results were robust to uncertainty analyses around model parameters. Conclusions High overhead costs and high patient costs in ComHIP suggest that the societal costs of ensuring appropriate hypertension care are high and may not produce sufficient impact to achieve cost-effective implementation. However, these results are limited by the evidence quality of the effectiveness estimates, which comes from observational data rather than from randomised controlled study design.