Evidence map›Paper›PMID 42271302›Full record

ArticleBMC palliative care2026

Referral and utilization patterns for home-based palliative care services among older adults.

Joohyun Chung, Aaron Langlois, TylaAnn Burger, David L Chin

Abstract read
In one paragraph

Article in BMC palliative care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Joohyun ChungElaine Marieb College of Nursing, University of Massachusetts Amherst, 224 Skinner Hall651 North Pleasant Street, Amherst, MA, 01003, United States. joohyunchung@umass.edu.
Aaron LangloisPalliative & Hospice Care, VNA Care, Worcester, MA, United States.
TylaAnn BurgerPalliative & Hospice Care, VNA Care, Worcester, MA, United States.
David L ChinSchool of Public Health & Health Science, University of Massachusetts Amherst, Amherst, MA, United States.

Funding

Public Service Endowment Grants (PSEG) at the University of Massachusetts Amherst P1PSEG000000051
6 · The paper itself

Abstract

backgroundHome-based palliative care (HPC) improves quality of life for individuals with serious illness but remains underutilized in the United States, with persistent disparities in access. HPC is also frequently misconceived as appropriate only at the end of life.

aimThis study examined disparities in access to HPC by comparing patients who received services with those who were referred but not enrolled.

methodsA secondary analysis was conducted using 567 clinical records from a healthcare facility in the eastern United States between 2022 and 2023. Descriptive statistics, chi-square tests, and Cox proportional hazards regression model were used to compare demographic and clinical characteristics between groups.

resultsNo significant differences were observed by gender or race between patients who received HPC and those who did not. Significant differences were found for age (t = 2.33, p = 0.02), insurance type (p < 0.001), and referral source (p = 0.02). Patients who received HPC were more likely to be older, female, insured through Medicare Part B, and referred from larger hospitals.

conclusionThese findings underscore ongoing structural disparities in access to home-based palliative care and highlight the need for targeted strategies to improve equitable access to HPC services.

Indexed as

Home Care ServicesPalliative CarePatient Acceptance of Health CareReferral and ConsultationAgedAged, 80 and overFemaleHumansMaleProportional Hazards ModelsUnited Statesequity in palliative careHome-based palliative carereferral patterns

Identifiers

PMID42271302
PMCPMC13445677

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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.