Evidence map›Paper›PMID 26180045›Full record

ReviewMedical care research and review : MCRR2016

Patient Characteristics Predicting Readmission Among Individuals Hospitalized for Heart Failure.

Melissa O'Connor, Christopher M Murtaugh, Shivani Shah, Yolanda Barrón-Vaya, Kathryn H Bowles, Timothy R Peng, Carolyn W Zhu, Penny H Feldman

Abstract readReview
In one paragraph

Review in Medical care research and review : MCRR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
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  6. Article
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  8. Article
  9. Incorporating home healthcare nurses' admission information needs to inform data standards.Journal of the American Medical Informatics Association : JAMIA · 2020
    Observational
  10. What Predicts Health Care Transitions for Older Adults Following Introduction of LTSS?Journal of applied gerontology : the official journal of the Southern Gerontological Society · 2020
    Article
  11. Observational
  12. Article
  13. Article
  14. Observational
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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

8 authors.

Melissa O'ConnorVillanova University, Villanova, PA, USA melissa.oconnor@villanova.edu.
Christopher M MurtaughVisiting Nurse Service of New York, New York, NY, USA.
Shivani ShahVisiting Nurse Service of New York, New York, NY, USA.
Yolanda Barrón-VayaVisiting Nurse Service of New York, New York, NY, USA.
Kathryn H BowlesVisiting Nurse Service of New York, New York, NY, USA University of Pennsylvania, Philadelphia, PA, USA.
Timothy R PengVisiting Nurse Service of New York, New York, NY, USA.
Carolyn W ZhuIcahn School of Medicine at Mount Sinai, New York, NY, USA.
Penny H FeldmanVisiting Nurse Service of New York, New York, NY, USA.

Funding

Individualized Care for At Risk Older AdultsT32NR009356 · NINR · UNIVERSITY OF PENNSYLVANIA · PI Lauren M Massimo, MARY D NAYLOR · 2007 to 2026
$7.8M
Comparative Effectiveness of Intensive Home Health and MD Visits in Heart FailureR01HS020257 · AHRQ · VISITING NURSE SERVICE OF NEW YORK · PI MURTAUGH, CHRISTOPHER MICHAEL · 2011 to 2013
$1.0M
AHRQ HHS R01 HS020257AHRQ HHS R01HS020257NINR NIH HHS T32 NR009356NINR NIH HHS T32-NR009356
6 · The paper itself

Abstract

Heart failure is difficult to manage and increasingly common with many individuals experiencing frequent hospitalizations. Little is known about patient factors consistently associated with hospital readmission. A literature review was conducted to identify heart failure patient characteristics, measured before discharge, that contribute to variation in hospital readmission rates. Database searches yielded 950 potential articles, of which 34 studies met inclusion criteria. Patient characteristics generally have a very modest effect on all-cause or heart failure-related readmission within 7 to 180 days of index hospital discharge. A range of cardiac diseases and other comorbidities only minimally increase readmission rates. No single patient characteristic stands out as a key contributor across multiple studies underscoring the challenge of developing successful interventions to reduce readmissions. Interventions may need to be general in design with the specific intervention depending on each patient's unique clinical profile.

Indexed as

Heart FailureHumansPatient ReadmissionPatientsRisk AssessmentRisk FactorsTime Factorsheart failurepatient characteristicsreadmissionrehospitalization

Identifiers

PMID26180045
PMCPMC4712072

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.