Predicting mortality and visualizing health care spending by predicted mortality in Danes over age 65

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Health care expenditure in the last year of life makes up a high proportion of medical spending across the world. This is often framed as waste, but this framing is only meaningful if it is known at the time of treatment who will go on to die. We analyze the distribution of health care spending by predicted mortality for the Danish population over age 65 over the year 2016, with one-year mortality predicted by a machine learning model based on sociodemographics and use of health care services for the two years before entry into follow-up. While a reasonably good model can be built, extremely few individuals have high ex-ante probability of dying, and those with a predicted mortality of more than 50% account for only 2.8% of total health care expenditure. Decedents outspent survivors by a factor of more than ten, but compared to survivors with similar predicted mortality they spent only 2.5 times as much. Our results suggest that while spending in the last year of life is indeed high, this is nearly all spent in situations where there is a reasonable expectation that the patient can survive.

Original languageEnglish
Article number1203
JournalScientific Reports
Issue number1
Number of pages7
Publication statusPublished - 2023

Bibliographical note

© 2023. The Author(s).

    Research areas

  • Humans, Aged, Health Expenditures, Delivery of Health Care, Health Facilities, Denmark/epidemiology

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