Evidence map›Paper›PMID 28606799›Full record

ArticleThe American journal of medicine2017

Patterns of Readmissions for Three Common Conditions Among Younger US Adults.

Devraj Sukul, Shashank S Sinha, Andrew M Ryan, Michael W Sjoding, Scott L Hummel, Brahmajee K Nallamothu

Abstract read
In one paragraph

Article in The American journal of medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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

6 authors.

Devraj SukulDivision of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor. Electronic address: dsukul@med.umich.edu.
Shashank S SinhaDivision of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor; Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor.
Andrew M RyanInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor; Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor.
Michael W SjodingMichigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor; Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor.
Scott L HummelDivision of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor; Center for Clinical Management Research, Ann Arbor Veterans Affairs Healthcare System, Mich.
Brahmajee K NallamothuDivision of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor; Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor; Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor; Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor; Center for Clinical Management Research, Ann Arbor Veterans Affairs Healthcare System, Mich.

Funding

PULMONARY CELLULAR AND MOLECULAR BIOLOGY TRAININGT32HL007749 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Robert Pickett Dickson · 1993 to 2026
$19.9M
TRAINING IN MOLECULAR AND CELLULAR CARDIOLOGYT32HL007853 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI David J. Pinsky · 1996 to 2026
$11.6M
The Effects of Bundled Payment on Acute Cardiovascular Outcomes Among Older AdultsR01AG047932 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Andrew M Ryan · 2015 to 2026
$4.9M
DASH-SRD Post Acute Decompensated Heart Failure HospitalizationR21AG047939 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI HUMMEL, SCOTT L, MAURER, MATHEW S · 2014 to 2015
$418k
NHLBI NIH HHS T32 HL007749NHLBI NIH HHS T32 HL007853NIA NIH HHS R01 AG047932NIA NIH HHS R21 AG047939
6 · The paper itself

Abstract

backgroundThirty-day readmissions among elderly Medicare patients are an important hospital quality measure. Although plans for using 30-day readmission measures are under consideration for younger patients, little is known about readmission in younger patients or the relationship between readmissions in younger and elderly patients at the same hospital.

methodsBy using the 2014 Nationwide Readmissions Database, we examined readmission patterns in younger patients (18-64 years) using hierarchical models to evaluate associations between hospital 30-day, risk-standardized readmission rates in elderly Medicare patients and readmission risk in younger patients with acute myocardial infarction, heart failure, or pneumonia.

resultsThere were 87,818, 98,315, and 103,251 admissions in younger patients for acute myocardial infarction, heart failure, and pneumonia, respectively, with overall 30-day unplanned readmission rates of 8.5%, 21.4%, and 13.7%, respectively. Readmission risk in younger patients was significantly associated with hospital 30-day risk-standardized readmission rates for elderly Medicare patients for all 3 conditions. A decrease in an average hospital's 30-day, risk-standardized readmission rates from the 75th percentile to the 25th percentile was associated with reduction in younger patients' risk of readmission from 8.8% to 8.0% (difference: 0.7%; 95% confidence interval, 0.5-0.9) for acute myocardial infarction; 21.8% to 20.0% (difference: 1.8%; 95% confidence interval, 1.4-2.2) for heart failure; and 13.9% to 13.1% (difference: 0.8%; 95% confidence interval, 0.5-1.0) for pneumonia.

conclusionsAmong younger patients, readmission risk was moderately associated with hospital 30-day, risk-standardized readmission rates in elderly Medicare beneficiaries. Efforts to reduce readmissions among older patients may have important areas of overlap with younger patients, although further research may be necessary to identify specific mechanisms to tailor initiatives to younger patients.

Indexed as

AdolescentAdultAge FactorsFemaleHeart FailureHumansLength of StayMaleMedicareMiddle AgedMyocardial InfarctionPatient ReadmissionPneumoniaRisk FactorsUnited StatesYoung AdultAcute myocardial infarctionHeart failurePatient readmissionPneumonia

Identifiers

PMID28606799
PMCPMC5699907

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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.