Predicting mortality and visualizing health care spending by predicted mortality in Danes over age 65.
Ontology highlight
ABSTRACT: 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 f
SUBMITTER: Hansen AV
PROVIDER: S-EPMC9867694 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
ACCESS DATA