Evidence map›Paper›PMID 26252181›Full record

ArticleSocial work in public health2015

From discharge planner to "concierge": recommendations for hospital social work by clients with intracerebral hemorrhage.

Kristen F Linton, Marissa M Ing, Megan A Vento, Kazuma Nakagawa

Abstract read
In one paragraph

Article in Social work in public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact, top 95% of its field
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

2 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Article
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 at 1 institution in 1 country.

Kristen F Lintona California State University , Channel Islands, Camarillo , California , USA.
Marissa M Ing
Megan A Vento
Kazuma Nakagawa
Queen's Medical Center · US

Funding

UNDERSTANDING AND REDUCING ETHNIC DISPARITIES IN PREVENTABLE HOSPITALIZATIONSP20MD000173 · NIMHD · UNIVERSITY OF HAWAII AT MANOA · PI MAU, MARJORIE K. LEIMOMI MALA · 2002 to 2017
$21.0M
NIMHD NIH HHS P20 MD000173NIMHD NIH HHS P20MD000173
6 · The paper itself

Abstract

The Affordable Care Act and budget cuts have changed the role of hospital social workers by placing pressure on them to conduct speedy discharges and decrease readmission rates. This qualitative study aimed to assess if hospital social work is meeting the needs of clients in the hospital and postdischarge. Semistructured interviews with 10 clients with intracerebral hemorrhage (ICH) and 11 caregivers were conducted. Participants reported that social work services were not meeting their needs. Clients with ICH and their caregivers expressed needs from social workers that surpassed their roles as discharge planners, including counseling, help with finances and insurance, and advocacy. Participants wanted social work services to begin early in acute treatment with continuity postdischarge. Social workers should conduct ethical social work by meeting clients where they are, addressing needs as prioritized by the client, and advocating individually and organizationally for clients.

Indexed as

Health Services Needs and DemandPatient DischargeSocial Work Department, HospitalAgedBudgetsCaregiversCerebral HemorrhageEconomics, HospitalFemaleHumansMaleMiddle AgedPatient Protection and Affordable Care ActProfessional-Patient RelationsQualitative ResearchUnited Statescase managementDischarge planninghospital social workPatient Protection and Affordable Care Actstroke

Identifiers

PMID26252181
PMCPMC5022556
OpenAlexW1771503675

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.