Evidence map›Paper›PMID 40151593›Full record

ArticleFrontiers in public health2025

Dying to pay: end-of-life medical costs for middle-aged and older adult patients with cardiovascular and cerebrovascular diseases.

Guoheng Hu, Haining Zhao, Xiaolong Bian, Ying Li

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Guoheng HuYanshan University, Qinhuangdao, Hebei, China.
Haining ZhaoYanshan University, Qinhuangdao, Hebei, China.
Xiaolong BianYanshan University, Qinhuangdao, Hebei, China.
Ying LiYanshan University, Qinhuangdao, Hebei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to investigate end-of-life healthcare expenditures among middle-aged and older patients with cardiovascular and cerebrovascular diseases, with a particular focus on the existence of the "nearing-death effect." Methods: Using inpatient discharge summary data from the Chinese National Medical Insurance Settlement Platform, we identified a cohort of middle-aged and older adults (aged 45 and above) diagnosed with cardiovascular and cerebrovascular diseases in Province H, China, during 2018-2019. Propensity Score Matching (PSM) was employed to examine differences in end-of-life healthcare expenditures between deceased and surviving patients. Robustness checks were performed using Multidimensional Fixed Effects (MDFE) and Difference-in-Differences Machine Learning (DDML). Results: The findings reveal a substantial increase in end-of-life healthcare expenditures among patients with cardiovascular and cerebrovascular diseases. Specifically, Total Medical Costs, Comprehensive Service Fees, Diagnosis Fees, Treatment Fees, Pharmaceutical Fees, and Nursing Care Fees rose by 34.3, 44.0, 35.7, 62.5, 49.9, and 46.8%, respectively, all statistically significant at the 1% level. These results highlight a pronounced escalation in healthcare expenditures associated with patient mortality. Conclusion: Among middle-aged and older patients with cardiovascular and cerebrovascular diseases, healthcare expenditures exhibit a distinct "end-of-life effect," characterised by a sharp surge in medical spending during the final stages of life. This phenomenon underscores the intensive utilization of medical resources at the end of life, markedly differing from healthcare expenditure patterns at other stages of life.

Indexed as

Cardiovascular DiseasesCerebrovascular DisordersHealth ExpendituresTerminal CareAgedAged, 80 and overChinaFemaleHumansMaleMiddle AgedPropensity Scorecardiovascular and cerebrovascular diseasesdifference-in-differences machine learning (DDML)end-of-life healthcare expenditurespropensity score matching (PSM)terminal stage

Identifiers

PMID40151593
PMCPMC11949274

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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.