Evidence map›Paper›PMID 33095775›Full record

ArticlePloS one2020

Community factors and hospital wide readmission rates: Does context matter?

Erica S Spatz, Susannah M Bernheim, Leora I Horwitz, Jeph Herrin

Abstract read
In one paragraph

Article in PloS one, 2020. 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.

  1. Article
  2. Article
  3. Review
  4. Article
  5. A state-level analysis of macro-level factors associated with hospital readmissions.The European journal of health economics : HEPAC : health economics in prevention and care · 2024
    Article
  6. Observational
  7. Article
  8. Observational
  9. Article
  10. Article
  11. 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.

Erica S SpatzSection of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, United States of America.ORCID 0000-0002-1557-7713
Susannah M BernheimYale/Yale New Haven Health Center for Outcomes Research and Evaluation, New Haven, CT, United States of America.
Leora I HorwitzDivision of Healthcare Delivery Science, Department of Population Health, NYU School of Medicine, New York, NY, United States of America.ORCID 0000-0003-1800-6040
Jeph HerrinSection of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, United States of America.

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

backgroundThe environment in which a patient lives influences their health outcomes. However, the degree to which community factors are associated with readmissions is uncertain.

objectiveTo estimate the influence of community factors on the Centers for Medicare & Medicaid Services risk-standardized hospital-wide readmission measure (HWR)-a quality performance measure in the U.S. RESEARCH

designWe assessed 71 community variables in 6 domains related to health outcomes: clinical care; health behaviors; social and economic factors; the physical environment; demographics; and social capital. SUBJECTS: Medicare fee-for-service patients eligible for the HWR measure between July 2014-June 2015 (n = 6,790,723). Patients were linked to community variables using their 5-digit zip code of residence.

methodsWe used a random forest algorithm to rank variables for their importance in predicting HWR scores. Variables were entered into 6 domain-specific multivariable regression models in order of decreasing importance. Variables with P-values <0.10 were retained for a final model, after eliminating any that were collinear.

resultsAmong 71 community variables, 19 were retained in the 6 domain models and in the final model. Domains which explained the most to least variance in HWR were: physical environment (R2 = 15%); clinical care (R2 = 12%); demographics (R2 = 11%); social and economic environment (R2 = 7%); health behaviors (R2 = 9%); and social capital (R2 = 8%). In the final model, the 19 variables explained more than a quarter of the variance in readmission rates (R2 = 27%).

conclusionsReadmissions for a wide range of clinical conditions are influenced by factors relating to the communities in which patients reside. These findings can be used to target efforts to keep patients out of the hospital.

Indexed as

Patient ReadmissionPublic HealthAgedAlgorithmsDemographyHumansSocial Environment

Identifiers

PMID33095775
PMCPMC7584172

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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.