Health Policy and Management (보건행정학회지)

Korean Academy of Health Policy and Management (한국보건행정학회)
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Prediction of Changes in Health Expenditure of Chronic Diseases between Age group of Middle and Old Aged Population by using Future Elderly Model

Future Elderly Model을 활용한 중·고령자의 연령집단별 3대 만성질환 의료비 변화 예측

  • Baek, Mi Ra (Department of Health Services Management, Kyung Hee University Graduate School) ;
  • Jung, Kee Taig (Department of Health Services Management, Kyung Hee University Graduate School)
  • 백미라 (경희대학교 일반대학원 의료경영학과) ;
  • 정기택 (경희대학교 일반대학원 의료경영학과)
  • Received : 2016.08.01
  • Accepted : 2016.09.21
  • Published : 2016.09.30
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Abstract

Background: The purpose of this study is to forecast changes in the prevalence of chronic diseases and health expenditure by age group. Methods: Based on the Future Elderly Model, this study projects the size of Korean population, the prevalence of chronic diseases, and health expenditure over the 2014-2040 period using two waves (2012, 2013) of the Korea Health Panel and National Health Insurance Service database. Results: First, the prevalence of chronic diseases increases by 2040. The population with hypertension increases 2.04 times; the diabetes increases 2.43 times; and the cancer increases 3.38 times. Second, health expenditure on chronic diseases increases as well. Health expenditure on hypertension increases 4.33 times (1,098,753 million won in 2014 to 4,760,811 million won in 2040); diabetes increases 5.34 times (792,444 million won in 2014 to 4,232,714 million won in 2040); and cancer increases 6.09 times (4,396,223 million won in 2014 to 26,776,724 million won in 2040). Third, men and women who belong to the early middle-aged group (44-55 years old) as of 2014, have the highest increase rate in health spending. Conclusion: Most Korean literature on health expenditure estimation employs a macro-simulation approach and does not fully take into account personal characteristics and behaviors. Thus, this study aims to benefit medical administrators and policy makers to frame effective and targeted health policies by analyzing personal-level data with a microsimulation model and providing health expenditure projections by age group.

Keywords

References

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