Elevated end-of-life spending: A new measure of potentially wasteful health care spending at the end of life.
Academic Article
Overview
abstract
OBJECTIVE: To construct a new measure of end-of-life (EoL) spending-the elevated EoL spending-and examine its associations with measures of quality of care and patient and physician preferences in comparison with the commonly used total Medicare EoL spending measures. DATA SOURCES AND STUDY SETTING: Medicare claims data for a 20% random sample of Medicare fee-for-service (FFS) patients, from the health care quality data for 2015-2016, from the Hospital Compare and the Medicare Geographic Variation public use file, and survey data about patient and physician preferences. STUDY DESIGN: We constructed the elevated EoL spending measure as the differential monthly spending between decedents and survivors with the same one-year mortality risk, where the risk was predicted using machine learning models. We then examined the associations of the hospital referral region (HRR)-level elevated EoL spending with various health care quality measures and with the survey-elicited patient and provider preferences. We also examined analogous associations for monthly total EoL spending on decedents. DATA EXTRACTION METHODS: Medicare FFS patients who were continuously enrolled in Medicare Parts A & B in 2015 and were alive as of January 1, 2016. PRINCIPAL FINDINGS: We found a large variation in the elevated EoL spending across HRRs in the United States. There was no evidence of an association between HRR-level elevated EoL spending and established health care quality measures, including those specific to EoL care, whereas total EoL spending was positively associated with certain quality of care measures. We also found no evidence that elevated EoL spending was associated with patient preferences for EoL care. However, elevated EoL spending was positively and significantly associated with physician preferences for treatment intensity. CONCLUSIONS: Our findings suggested that elevated EoL spending captures different resource use from conventional measures of EoL spending and may be more valuable in identifying potentially wasteful spending.
