Evidence map›Paper›PMID 25431752›Full record

ArticleCurrent geriatrics reports2014

Strategies to Reduce 30-Day Readmissions in Older Patients Hospitalized with Heart Failure and Acute Myocardial Infarction.

Kumar Dharmarajan, Harlan M Krumholz

Open access · greenAbstract read
In one paragraph

Article in Current geriatrics reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 6% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Analysis of Machine Learning Techniques for Heart Failure Readmissions.Circulation. Cardiovascular quality and outcomes · 2016
    Pooled it
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  3. Development and psychometric properties of a short version of the Patient Continuity of Care Questionnaire.Health expectations : an international journal of public participation in health care and health policy · 2023
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  20. Risk after hospitalization: we have a lot to learn.Journal of hospital medicine · 2015
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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

2 authors at 1 institution in 1 country.

Kumar DharmarajanSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT.
Harlan M KrumholzSection of Cardiovascular Medicine, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, CT; Robert Wood Johnson Foundation Clinical Scholars Program, Department of Internal Medicine, Yale University School of Medicine, New Haven, CT; Department of Health Policy and Management, Yale University School of Public Health, New Haven, CT.
Yale New Haven Hospital · US

Funding

Center for Cardiovascular Outcomes Research at Yale UniversityU01HL105270 · NHLBI · YALE UNIVERSITY · PI CURTIS, JEPTHA PELHAM, KRUMHOLZ, HARLAN MARC · 2010 to 2013
$5.8M
Geriatric Conditions and Readmission after Acute Myocardial InfarctionK23AG048331 · NIA · YALE UNIVERSITY · PI DHARMARAJAN, KUMAR · 2014 to 2017
$692k
NHLBI NIH HHS U01 HL105270NIA NIH HHS K23 AG048331
6 · The paper itself

Abstract

Readmission within 30 days after hospital discharge for common cardiovascular conditions such as heart failure and acute myocardial infarction is extremely common among older persons. To incentivize investment in reducing preventable rehospitalizations, the United States federal government has directed increasing financial penalties to hospitals with higher-than-expected 30-day readmission rates. Uncertainty exists, however, regarding the best approaches to reducing these adverse outcomes. In this review, we summarize the literature on predictors of 30-day readmission, the utility of risk prediction models, and strategies to reduce short-term readmission after hospitalization for heart failure and acute myocardial infarction. We report that few variables have been found to consistently predict the occurrence of 30-day readmission and that risk prediction models lack strong discriminative ability. We additionally report that the literature on interventions to reduce 30-day rehospitalization has significant limitations due to heterogeneity, susceptibility to bias, and lack of reporting on important contextual factors and details of program implementation. New information is characterizing the period after hospitalization as a time of high generalized risk, which has been termed the

Indexed as

Acute myocardial infarctionCare transitionsElderlyHeart failurePost-hospital syndromeReadmissionRehospitalization

Identifiers

PMID25431752
PMCPMC4242430
OpenAlexW2031187207

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.