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  • Title: Health Care Costs Associated With Macrovascular, Microvascular, and Metabolic Complications of Type 2 Diabetes Across Time: Estimates From a Population-Based Cohort of More Than 0.8 Million Individuals With Up to 15 Years of Follow-up.
    Author: Chen HY, Kuo S, Su PF, Wu JS, Ou HT.
    Journal: Diabetes Care; 2020 Aug; 43(8):1732-1740. PubMed ID: 32444454.
    Abstract:
    OBJECTIVE: Developing country-specific unit-cost catalogs is a key area for advancing economic research to improve medical and policy decisions. However, little is known about how health care costs vary by type 2 diabetes (T2D) complications across time in Asian countries. We sought to quantify the economic burden of various T2D complications in Taiwan. RESEARCH DESIGN AND METHODS: A nationwide, population-based, longitudinal study was conducted to analyze 802,429 adults with newly diagnosed T2D identified during 1999-2010 and followed up until death or 31 December 2013. Annual health care costs associated with T2D complications were estimated, with multivariable generalized estimating equation models adjusted for individual characteristics. RESULTS: The mean annual health care cost was $281 and $298 (2017 U.S. dollars) for a male and female, respectively, diagnosed with T2D at age <50 years, with diabetes duration of <5 years, and without comorbidities, antidiabetic treatments, and complications. Depression was the costliest comorbidity, increasing costs by 64-82%. Antidiabetic treatments increased costs by 72-126%. For nonfatal complications, costs increased from 36% (retinopathy) to 202% (stroke) in the event year and from 13% (retinopathy or neuropathy) to 49% (heart failure) in subsequent years. Costs for the five leading costly nonfatal subtype complications increased by 201-599% (end-stage renal disease with dialysis), 37-376% (hemorrhagic/ischemic stroke), and 13-279% (upper-/lower-extremity amputation). For fatal complications, costs increased by 1,784-2,001% and 1,285-1,584% for cardiovascular and other-cause deaths, respectively. CONCLUSIONS: The cost estimates from this study are crucial for parameterizing diabetes economic simulation models to quantify the economic impact of clinical outcomes and determine cost-effective interventions.
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