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• W2013487890 abstract "Abstract Background Cost-effectiveness analysis (CEA) is widely used as a tool for prioritising health interventions, particularly in low-income and middle-income settings. However, among the major limitations of CEA are the omission of health-care seeking behaviour, heterogeneous mechanisms across populations or regions that determine the delivery and quality of health interventions, and the economic benefits of such interventions. Extended CEA complements basic CEA and provides a basis for a multicriteria decision-making approach that looks beyond health measures, but is far less complex than a benefit–cost analysis. Methods We developed a dynamic agent-based simulation model, the Disease Control Priorities Simulation (DCPSim) model, to estimate the health and economic benefits of health interventions and policies. Using data from the District Level Household Survey (2007–08) and National Sample Survey (2004) of India, we created an underlying population characterised by various demographic and socioeconomic attributes. Additional interdependencies related to the disease, the health intervention, treatment seeking, and fertility behaviour of model households, and the quality of health-care system, were included. As a case study, we examined two different policies that can scale up the availability of drugs for secondary prevention of acute myocardial infarction (AMI) in India: a universal public provision (UPP) that provides a drug for free at public health facilities, and a universal public finance (UPF) that provides a drug for free at public facilities and fully finances it at private facilities. Findings In addition to measuring the number of lives saved by scaling up the availability of drugs such as aspirin and combination therapies, we also estimated the economic benefits of the UPP and UPF policies. In particular, we found that for every 1 million Indians, these policies averted out-of-pocket private medical expenditure ranging from US$255 726 to $300 061 related to both the secondary and primary treatment of AMIs in India. We also found that these policies provided up to a $56 932 value of insurance against financial risk and increased access to capital by reducing debt burden. Interpretation We build on the new method of extended CEA to examine the economic benefits of scaling up various drug combinations for the prevention of AMI in India. Our agent-based model attempts to capture various interdependencies between demographic change, health-care seeking, disease epidemiology, intervention efficacy, and the quality of service delivery. Resultant economic outcomes are measured from a health-systems accounting perspective. Funding Disease Control Priorities (DCP-3) Project funded by the Bill & Melinda Gates Foundation." @default.
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• W2013487890 date "2013-06-01" @default.
• W2013487890 modified "2023-09-27" @default.
• W2013487890 title "An agent-based simulation modelling approach to extended cost-effectiveness analysis of health interventions" @default.
• W2013487890 doi "https://doi.org/10.1016/s0140-6736(13)61350-1" @default.
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