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Healthcare costs associated with macrovascular, microvascular, and metabolic complications of type 2 diabetes across time: Estimates from a population-based cohort of over 0.8 million individuals with up to 15 years of follow-up

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posted on 2020-05-22, 14:31 authored by Hsuan-Ying Chen, Shihchen Kuo, Pei-Fang Su, Jin-Shang Wu, Huang-Tz Ou
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 healthcare 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 December 31, 2013. Annual healthcare costs associated with T2D complications were estimated with the multivariable generalized estimating equations models adjusting for individual characteristics.

Results:

The mean annual healthcare 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 non-fatal 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 non-fatal 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.

Funding

This work was supported by the Ministry of Science and Technology, Taiwan, under grant MOST 108-2320-B-006 -048. This work was also supported by Grant Number P30DK092926 (MCDTR and MCDTR’s Methods and Measurement Core) from the National Institute of Diabetes and Digestive and Kidney Diseases. The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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