Determinants of Total End-of-Life Health Care Costs of Medicare Beneficiaries: A Quantile Regression Forests Analysis.

ABSTRACT:

Background

To identify and rank the importance of key determinants of end-of-life (EOL) health care costs, and to understand how the key factors impact different percentiles of the distribution of health care costs.

Method

We applied a principled, machine learning-based variable selection algorithm, using Quantile Regression Forests, to identify key determinants for predicting the 10th (low), 50th (median), and 90th (high) quantiles of EOL health care costs, including costs paid for by Medicare, Medicaid, Medicare Health Maintenance Organizations (HMOs), private HMOs, and patient's out-of-pocket expenditures.

Results

Our sample included 7 539 Medicare beneficiaries who died between 2002 and 2017. The 10th, 50th, and 90th quantiles of EOL health care cost are $5 244, $

SUBMITTER: Li L 

PROVIDER: S-EPMC9071433 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature