Financing Novel Diabetes Prevention and Management Models
Financing Novel Diabetes Prevention and Management Models
Year: August 2019
Collaborator: Access Health International
Team: Sarang Deo, Harish Kumar, Preeti Singh
Background
India’s non-communicable diseases (NCDs) burden continues to grow owing to underutilization of care due to high out-of-pocket expenditures (OOPE) despite government insurance schemes. Private sector implemented innovative models but lacks incentives to manage diseases proactively. In India, where the private sector caters to most care seekers, public-private engagement models--where the health services are financed by the public sector with provisioning of the services by the private sector-- can effectively address the rising NCD burden. Evidence indicates that such models can reduce provider fragmentation, create incentives for quality, provide subsidies for targeted populations and high-impact interventions, and use technologies that expand access and improve quality.
About the Study
In the study, we understand three delivery models for improving diabetes care and determine if the models are cost-effective in improving health outcomes. We studied three models – Community Health Workers (CHW) Model, Telemedicine-based Model (TMU) and Telemedicine-equipped Mobile Medical Unit-based Model (MMU) – of providing care, based on ongoing or completed pilot initiatives undertaken in India. The CHW model leveraged community health workers to provide door-to-door screening for diabetes and offered a diabetes management program to those screened as diabetes. Under the TMU model, e-clinics were set up to provide screening and care to any individual visiting the clinic. The consultation services were provided through teleconsultation. The MMU model provided door-to-door screening services through mobile units and provided follow-up care to diabetic patients through rural diabetes centres.
Methodology
We compared the cost-effectiveness associated with screening and prevention of diabetes through different delivery models with status-quo (care currently available to the population). The cost of care for each program differed depending on their operational models. Therefore, we collected clinical, operational, and cost data for each program to assess the health benefits and healthcare cost reduction associated with different screening and management strategies. Activity-based costing was used to analyse the costs. We developed a cohort-based Markov model to estimate costs and disability-adjusted life years over a period of 20 years with a cycle time of one month.
Outcomes
The CHW and TMU models are not cost effective across cohorts but show promise if the cost of intervention can be reduced further. If the OOPE costs can be covered by an external payor such as an insurance program, the health outcomes and health equity can improve. Moreover, the model coverage needs to be improved to get a greater number of individuals under treatment. This would require both financial and operational support for the implementer. A government agency can fulfil both the roles as it can reduce the out-of-pocket expenditure for patients and help the models reach scale. Further, these models can then be implemented within the ambit of public health infrastructure to improve health outcomes among patients accessing care at public health facilities.