Evidence map›Paper›PMID 32610810›Full record

ArticleInternational journal of health policy and management2022

Hospital Expenditure at the End-of-Life: A Time-to-Death Approach.

Vahid Alipour, Abolghasem Pourreza, Majid Kosheshi, Hassan Heydari, Sara Emamgholipour Sefiddashti

Abstract read
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Article in International journal of health policy and management, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers 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

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Vahid AlipourHealth Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran.ORCID 0000-0003-1010-9571
Abolghasem PourrezaDepartment of Health Education and Promotion, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-6957-6660
Majid KosheshiDepartment of Demography, Social Science Faculty, Tehran University, Tehran, Iran.ORCID 0000-0003-4829-2762
Hassan HeydariDepartment of Economic Sciences, School of Management and Economics, Tarbiat Modares University, Tehran, Iran.ORCID 0000-0001-8915-6076
Sara Emamgholipour SefiddashtiDepartment of Health Management and Economics, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-5982-8983

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recent years the use of time to death (TTD) variables in the modeling of individual health expenditures has been of interest to health economics researchers. The aim of this study was to investigate the effect of age and TTD on hospital inpatient expenditure (HIE).

methodsWe used a claims database from Iran Health Insurance Organization of Tehran city that includes considerable proportion of Tehran residents and contains information on insured individuals' HIE. We included HIE of all insured decedents (30 to 90 years old) who died during March 2013 and March 2014 (n=1018). No sampling was required. According to the decedents' date of death, we extracted their last 24 months HIE. The period of time March 30, 2011 until March 30, 2014 (3 years) was used to guarantee a full 24 months of observations for decedents. A two-part econometric model was employed to investigate the effect of age, TTD, and some demographic variables on probability and conditional amount of individuals' hospital expenditure. Stata software (version 16.0) was used for data processing and analysis.

resultsOur results demonstrated that the month-based TTDs especially near months before death of decedents (TTD1 to TTD10) significantly affected both probability and conditional amount of HIE. One month before death incurred more HIE than the rest of the months. A further interesting finding is that after including TTD, age variable as a conditional driver of HIE loses its direct effect on decedents' HIE, but age TTD interaction effect on HIE is still positive and statistically significant.

conclusionThe results confirm that TTD as a proxy of mortality indicator has a considerable effect on decedents' HIE. The age variable has not directly affected decedents' HIE but indirectly and through its interaction with TTD has a statistically significant effect on HIE. In addition to age, policy-makers should consider TTD to make better predictions of future HIE.

Indexed as

Health ExpendituresInsurance, HealthAdultAgedAged, 80 and overDeathHospitalsHumansIranMiddle AgedAgingHospital ExpenditureIranTime-To-Death

Identifiers

PMID32610810
PMCPMC9278609

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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.