Evidence map›Paper›PMID 29462075›Full record

ArticleMedical care2018

Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization.

Leora I Horwitz, Yongfei Wang, Faseeha K Altaf, Changqin Wang, Zhenqiu Lin, Shuling Liu, Jacqueline Grady, Susannah M Bernheim, Nihar R Desai, Arjun K Venkatesh and 1 more

Abstract read
In one paragraph

Article in Medical care, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

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

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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

11 authors.

Leora I HorwitzDepartment of Population Health, Division of Healthcare Delivery Science, NYU School of Medicine.
Yongfei WangCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Faseeha K AltafCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Changqin WangCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Zhenqiu LinCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Shuling LiuCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Jacqueline GradyCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Susannah M BernheimCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Nihar R DesaiCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Arjun K VenkateshCenter for Outcomes Research and Evaluation, Yale New Haven Hospital.
Jeph HerrinDepartment of Medicine, Section of Cardiovascular Medicine.

Funding

Understanding hospital value: provider, hospital and community effectsR01HS022882 · AHRQ · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI HORWITZ, LEORA · 2014 to 2023
$2.9M
AHRQ HHS R01 HS022882
6 · The paper itself

Abstract

backgroundWhether types of hospitals with high readmission rates also have high overall postdischarge acute care utilization (including emergency department and observation care) is unknown.

designCross-sectional analysis. SUBJECTS: Nonfederal United States acute care hospitals. MEASURES: Using methodology established by the Centers for Medicare & Medicaid Services, we calculated each hospital's "excess days in acute care" for fee-for-service (FFS) Medicare beneficiaries aged over 65 years discharged after hospitalization for acute myocardial infarction, heart failure (HF), or pneumonia, representing the mean difference between predicted and expected total days of acute care utilization in the 30 days following hospital discharge, per 100 discharges. We assessed the multivariable association of 8 hospital characteristics with excess days in acute care and the proportion of hospitals with each characteristic that were statistical outliers (95% credible interval estimate does not include 0).

resultsWe included 2184 hospitals for acute myocardial infarction [228 (10.4%) better than expected, 549 (25.1%) worse than expected], 3720 hospitals for HF [484 (13.0%) better and 840 (22.6%) worse], and 4195 hospitals for pneumonia [673 (16.0%) better, 1005 (24.0%) worse]. Results for all conditions were similar. Worse than expected outliers for pneumonia included: 18.8% of safety net hospitals versus 26.1% of nonsafety net hospitals; 16.7% of public hospitals versus 33.1% of for-profit hospitals; 19.5% of nonteaching hospitals versus 52.2% of major teaching hospitals; 7.9% of rural hospitals versus 42.1% of large urban hospitals; 5.9% of hospitals with 24-<50 beds versus 58% of hospitals with >500 beds; and 29.0% of hospitals with nurse-to-bed ratios >1.0-1.5 versus 21.7% of hospitals with ratios >2.0.

conclusionsIncluding emergency department and observation stays in measures of postdischarge utilization produces similar results as measuring only readmissions in that major teaching, urban and for-profit hospitals still perform disproportionately poorly versus nonteaching or public hospitals. However, it enables identification of more outliers and a more granular assessment of the association of hospital factors and outcomes.

Indexed as

Cross-Sectional StudiesEmergency Service, HospitalFee-for-Service PlansHeart FailureHospital AdministrationHospitals, PublicHumansMedicareMyocardial InfarctionNursing Staff, HospitalOwnershipPatient ReadmissionPneumoniaResidence CharacteristicsRetrospective StudiesSafety-net Providers

Identifiers

PMID29462075
PMCPMC6170884

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Registered trials

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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.