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Demand-side determinants of rising hospital admissions in Germany: the role of ageing.

Jonas KrämerJonas Schreyögg
Published in: The European journal of health economics : HEPAC : health economics in prevention and care (2019)
In this study, we investigated the relationship between changes in demand-side determinants and changes in hospital admissions. We used longitudinal market-wide data, including a novel detailed measure of population morbidity. To assess the effect of ageing, we interacted age with shifts in the population structure for both the surviving population and the population in their last year of life. We used fixed effects models and addressed the endogeneity of morbidity with instrumental variables. We found that changes in morbidity had the largest impact on changes in hospital admissions. Changes in the size of the surviving population had the second largest impact, which differed substantially across the age spectrum. There was a large response in admissions to changes in the size of the population aged 60-79 years. The end-of-life effect had the smallest impact and began to play a greater role only in the population aged 80 years and older. In many studies, end of life presumably approximates high morbidity. Our results demonstrated robustness in several tests. We performed estimations in separate major diagnostic categories and included changes in personal preferences. We argue that the determinants included in our estimations capture the vast majority of change on the demand side. Taken together, our findings provide evidence that these determinants explain one-fifth of changes in hospital admissions.
Keyphrases
  • machine learning
  • health insurance
  • artificial intelligence