Evidence map›Paper›PMID 36303444›Full record

ArticleHealth services research2023

Elevated end-of-life spending: A new measure of potentially wasteful health care spending at the end of life.

Yongkang Zhang, Atul Gupta, Sean Nicholson, Jing Li

Abstract read
In one paragraph

Article in Health services research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Reversing Decline in Aging Muscles: Expected Trends, Impacts and Remedies.Journal of functional morphology and kinesiology · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yongkang ZhangDepartment of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, New York, USA.ORCID 0000-0001-6312-9686
Atul GuptaDepartment of Health Care Management, The Wharton School, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Sean NicholsonDepartment of Economics, Brooks School of Public Policy, Cornell University, Ithaca, New York, USA.
Jing LiThe Comparative Health Outcomes, Policy and Economics Institute, Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington, USA.ORCID 0000-0003-1768-3664

Funding

SYNERGY: The Dartmouth Center for clinical and Translational ScienceUL1TR001086 · NCATS · DARTMOUTH COLLEGE · PI GREEN, ALAN I · 2013 to 2017
$18.3M
Technology Diffusion, Health Outcomes, and Healthcare ExpendituresU01AG046830 · NIA · DARTMOUTH COLLEGE · PI SKINNER, JONATHAN S · 2013 to 2017
$4.5M
Effect of Medicare Reimbursement for Care Planning on End of Life Care among Patients with Alzheimer's Disease and Related Dementias: A Quasi-Experimental StudyK01AG066946 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI LI, JING · 2020 to 2024
$633k
Understanding and Predicting High-Need, High-Cost Patients among Older AdultsR00AG064030 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI ZHANG, YONGKANG · 2022 to 2023
$498k
Understanding and Predicting High-Need, High-Cost Patients among Older AdultsK99AG064030 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI ZHANG, YONGKANG · 2020 to 2021
$250k
NCATS NIH HHS UL1 TR001086NIA NIH HHS K01 AG066946NIA NIH HHS K99 AG064030NIA NIH HHS R00 AG064030NIA NIH HHS U01 AG046830
6 · The paper itself

Abstract

objectiveTo 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

settingMedicare 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

designWe 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

methodsMedicare FFS patients who were continuously enrolled in Medicare Parts A & B in 2015 and were alive as of January 1, 2016. PRINCIPAL

findingsWe 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.

conclusionsOur 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.

Indexed as

Medicare Part ATerminal CareAgedDeathHealth ExpendituresHumansMedicareUnited Statesend-of-lifehealth care qualityMedicarepatient preferencesphysician preferenceswaste in health care

Identifiers

PMID36303444
PMCPMC9836947

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.