Evidence map›Paper›PMID 39560634›Full record

ArticleThe American journal of hospice & palliative care2025

Making Community-Based Palliative Care Eligibility Determinations: Palliative Care Team Member Perspectives on Access to Information and Algorithm Use.

Kira G Sheldon, Kathryn H Bowles, Carolyn Sage, June Stanley, Elizabeth A Luth

Abstract read
In one paragraph

Article in The American journal of hospice & palliative care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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

5 authors.

Kira G SheldonRutgers University, New Brunswick, NJ, USA.ORCID 0009-0006-7076-469X
Kathryn H BowlesCenter for Home Care Policy & Research, VNS Health, University of Pennsylvania School of Nursing, Philadelphia, PA, USA.
Carolyn SageVNS Health, New York, NY, USA.
June StanleyVNS Health, New York, NY, USA.
Elizabeth A LuthRutgers University, New Brunswick, NJ, USA.ORCID 0000-0003-1496-1235

Funding

New Jersey Alliance for Clinical Translational Science: NJ ACTSUL1TR003017 · NCATS · RUTGERS BIOMEDICAL/HEALTH SCIENCES-RBHS · PI PANETTIERI, REYNOLD ALEXANDER · 2019 to 2023
$28.9M
NCATS NIH HHS UL1 TR003017
6 · The paper itself

Abstract

backgroundSeriously ill older adults have high risk of mortality, symptom burden, and compromised functional status, and may benefit from community-based palliative care ("palliative care"). However, identifying potentially eligible individuals is challenging.

objectivesIdentify how a palliative care team makes eligibility determinations, including the use of a mortality risk algorithm.

designSemi-structured focus groups were conducted with palliative care providers to understand how health information is used to assess Medicare Advantage plan patients' eligibility for palliative care. Transcripts were analyzed to identify categories related to how participants used health information in making eligibility determinations. SETTING/

participantsAll outreach and care management team members and nurse practitioners (n = 7) working for a palliative care program at a not-for-profit health care agency.

resultsThe palliative care team used information on symptoms, diagnoses, and acute care utilization when making eligibility determinations. The algorithm generated lists of potentially eligible patients but was deemed not useful because it provided limited information about current health status and was not well integrated into existing health record systems. Participants would like information to be current, detailed, and presented in one location.

conclusionsPalliative care team members used a variety of indicators of unmet care needs to make eligibility determinations. A mortality risk algorithm to identify potentially eligible patients was insufficiently detailed to be useful in final eligibility determinations. These findings provide insights into how health data can be presented to better integrate health information from mortality risk algorithms into existing workflows to support palliative care eligibility decision making.

Indexed as

AlgorithmsCommunity Health ServicesEligibility DeterminationPalliative CarePatient Care TeamAgedFemaleFocus GroupsHumansMaleMedicareUnited Statesalgorithmsdecision makingdelivery of health careeligibility determinationfocus groupspalliative care

Identifiers

PMID39560634
PMCPMC12865692

What OpenQuestion holds

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Registered trials

None linked

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.