ESTIMATING COST OF DIABETES AND ITS COMPLICATIONS IN INDONESIA, VIETNAM AND THE PHILIPPINES USING NATIONAL CLAIMS DATABASES

Author(s)

Ng J1, Hidayat B2, Kiet PH3, Jimeno C4, Wiebols E5
1IQVIA, Singapore, Singapore, 2University of Indonesia, Depok, Indonesia, 3Vietnam Health Economics Association, Hanoi, Viet Nam, 4University of the Philippines, Manila, Philippines, 5Novo Nordisk, Kuala Lumpur, Malaysia

Background According to International Diabetes Federation, in 2017, there are about 10.3 million, 3.5 million, 3.7 million people with type 2 diabetes mellitus (T2DM) in Indonesia, Vietnam and the Philippines, respectively. Previous studies have shown that more than half of the treated people with diabetes patients have uncontrolled HbA1c. Due to the limited availability of suitable data sources for investigation, there is a lack of a comprehensive picture of diabetes epidemiology, health care costs and resource utilization for its complications to inform policy makers. The present study will provide the first national estimates of costs of diabetes by leveraging recently established national claims databases in these countries. Through this study, we seek to estimate the societal cost and healthcare resource utilization of diabetes and its complications. Methods Country-specific analyses will be conducted to estimate the national economic burden of diabetes and its individual complications, in the form direct medical and indirect costs. National claims databases will be the cornerstone in capturing prevalence, direct medical cost and health care resource utilization for diabetes and its complications. Diabetes-related complications will be categorized into cardiovascular, nephropathy, retinopathy, neuropathy, peripheral vascular disease, metabolic diseases and others. Inclusion criteria are national citizens aged 18 or above and have ICD-10 E11 (for T2DM) claim(s) or are prescribed with antidiabetic medications in the year of interest. Due to the heterogeneous characteristics of the databases, gaps identified from the individual databases would be filled by physician interviews or hospital databases. Economic modelling will be conducted to estimate range of uncertainty. Indirect costs will be estimated based on data from claims databases and published data from neighboring countries. All costs will be converted to US dollar. In addition, the study will also inform potential data gaps and pave the path for further research work.

Conference/Value in Health Info

2018-09, ISPOR Asia Pacific 2018, Tokyo, Japan

Value in Health, Vol. 21, S2 (September 2018)

Code

PCP18

Topic

Methodological & Statistical Research

Topic Subcategory

Confounding, Selection Bias Correction, Causal Inference

Disease

Diabetes/Endocrine/Metabolic Disorders

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