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KMID : 1146320170050020089
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Journal of Health Technology Assessment
2017 Volume.5 No. 2 p.89 ~ p.94
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Cost Estimation of Productivity Loss of Elderly Over 70 due to Premature Mortality Reflecting Elderly Employment in an Aged Society
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Gong Young-Hoon
Jo Min-Woo
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Abstract
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Objectives: Previous cost of illness studies in Korea only have been included people from 15 to 69 years old, because domestic data sources of wage and employment-population ratio are not distinguished the older age over 60’s. Considering the demographic and socioeconomic characteristics of Korea, which is rapidly aging and has a high employment rate of the elderly, it is highly probable that the cost calculated only for this age group is underestimated. Therefore, we compare the results of cost applying previous age range and expanded age up to 89 years old.
Methods: The study population was between the ages of 15 and 69 and between 15 and 89 in 2013. In the analysis of the former, we used the annual report on the economically active population survey and survey report on labor conditions by employment type, and in the latter, the data including the survey of the elderly were synthesized.
Results: The proportion of workers over 70 was 34.3% for males and 19.0% for females. And annual average wage was 1770000 Korean won of the age group. In terms of whole nation, the loss of productivity increased from 4.5 trillion won to 5.4 trillion won for men and 1.4 trillion won to 1.7 trillion won for women, compared to applying narrow age range.
Conclusion: The cost shows that the past estimated result was under-estimated to 22?28% in male, 52?56% in female. It is reasonable to extend the inclusion age when estimating cost of productivity loss. This implies not only the problem of cost estimation but also the change of the priority of diseases with higher incidence and mortality in the elderly. In an aged society, older ages should be subdivided according to their health and socioeconomic characteristics, and appropriate analysis for each age group is required.
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KEYWORD
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Cost of illness, Population dynamics, Health priorities
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