Predictive modeling of U.S. health care spending in late life | Zendy

Liran Einav | Zendy; Amy Finkelstein | Zendy; Sendhil Mullainathan | Zendy; Ziad Obermeyer | Zendy

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Predictive modeling of U.S. health care spending in late life

Author(s) -

Liran Einav,

Amy Finkelstein,

Sendhil Mullainathan,

Ziad Obermeyer

Publication year - 2018

Publication title -

science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 12.556

H-Index - 1186

eISSN - 1095-9203

pISSN - 0036-8075

DOI - 10.1126/science.aar5045

Subject(s) - quarter (canadian coin) , ex ante , demography , interpretation (philosophy) , economics , demographic economics , health care , health spending , actuarial science , gerontology , medicine , geography , economic growth , sociology , computer science , macroeconomics , health insurance , archaeology , programming language

End-of-life health care spending In the United States, one-quarter of Medicare spending occurs in the last 12 months of life, which is commonly seen as evidence of waste. Einavet al. used predictive modeling to reassess this interpretation. From detailed Medicare claims data, the extent to which spending is concentrated not just on those who die, but on those who are expected to die, can be estimated. Most deaths are unpredictable; hence, focusing on end-of-life spending does not necessarily identify “wasteful” spending.Science , this issue p.1462

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