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Looking into the Black Box of “Medical Progress”: Rising Health Expenditures by Illness Type and Age

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Abstract

There is agreement among health economists that on the whole medical innovation causes health care expenditures (HCE) to rise. This paper analyzes for which diagnoses and in which age groups HCE per patient have grown significantly faster than average HCE. We distinguish decedents (patients in their last four years of life) from survivors and use a unique dataset comprising detailed HCE of all members of a regional health insurance fund in Upper Austria for the period 2005-2018. Our results indicate that among decedents in particular the expenditures for treatment of neoplasms have exceeded the general trend in HCE. This confirms that medical progress for this group of diseases has been particularly strong over the last 15 years. For survivors, we find a noticeable growth in cases and cost per case for pregnancies and childbirth and also for treatment of mental and behavioral disorders. The pattern of expenditures over age groups shows that among decedents the younger age groups (below 75) exhibit both the highest HCE per capita and the highest expenditure growth over time. For survivors, we find a steady increase in annual per capita HCE over age in both sexes, but the highest growth rates are observed in the age groups between 20 and 50 years.

Suggested Citation

  • Friedrich Breyer & Normann Lorenz & Gerald Pruckner & Thomas Schober, 2021. "Looking into the Black Box of “Medical Progress”: Rising Health Expenditures by Illness Type and Age," CDL Aging, Health, Labor working papers 2021-01, The Christian Doppler (CD) Laboratory Aging, Health, and the Labor Market, Johannes Kepler University Linz, Austria.
    • Handle: RePEc:jku:cdlwps:wp2101
    Note: English
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    2. Stefan Fetzer & Stefan Moog, 2021. "Indicators for Measuring Intergenerational Fairness of Social Security Systems—The Case of the German Social Health Insurance," Sustainability, MDPI, vol. 13(10), pages 1-18, May.
    3. Valeska Hofbauer-Milan & Stefan Fetzer & Christian Hagist, 2023. "How to Predict Drug Expenditure: A Markov Model Approach with Risk Classes," PharmacoEconomics, Springer, vol. 41(5), pages 561-572, May.

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    Keywords

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    JEL classification:

    • H51 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Health
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts
    • I19 - Health, Education, and Welfare - - Health - - - Other

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