Evidence map›Paper›PMID 20930150›Full record

SynthesisStroke2010

Predictors of hospital readmission after stroke: a systematic review.

Judith H Lichtman, Erica C Leifheit-Limson, Sara B Jones, Emi Watanabe, Susannah M Bernheim, Michael S Phipps, Kanchana R Bhat, Shantal V Savage, Larry B Goldstein

Abstract readSystematic Review
In one paragraph

Synthesis in Stroke, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed, 3 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

77 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Rapid systematic review of readmissions costs after stroke.Cost effectiveness and resource allocation : C/E · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Spatial distribution of stroke readmission within 30 days and the influencing factors in Hunan Province.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Article

17 more citing papers are in PubMed but not listed here.

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

9 authors.

Judith H LichtmanYale University School of Medicine, New Haven, CT 06520-8088, USA. judith.lichtman@yale.edu
Erica C Leifheit-Limson
Sara B Jones
Emi Watanabe
Susannah M Bernheim
Michael S Phipps
Kanchana R Bhat
Shantal V Savage
Larry B Goldstein

Funding

Stroke Hospitalization in the Elderly with Medicare FFSR01NS043322 · NINDS · YALE UNIVERSITY · PI LICHTMAN, JUDITH H · 2005 to 2009
$2.2M
NINDS NIH HHS R01 NS043322NINDS NIH HHS R01 NS043322-01
6 · The paper itself

Abstract

background and purposeRisk-standardized hospital readmission rates are used as publicly reported measures reflecting quality of care. Valid risk-standardized models adjust for differences in patient-level factors across hospitals. We conducted a systematic review of peer-reviewed literature to identify models that compare hospital-level poststroke readmission rates, evaluate patient-level risk scores predicting readmission, or describe patient and process-of-care predictors of readmission after stroke.

methodsRelevant studies in English published from January 1989 to July 2010 were identified using MEDLINE, PubMed, Scopus, PsycINFO, and all Ovid Evidence-Based Medicine Reviews. Authors of eligible publications reported readmission within 1 year after stroke hospitalization and identified ≥ 1 predictors of readmission in risk-adjusted statistical models. Publications were excluded if they lacked primary data or quantitative outcomes, reported only composite outcomes, or had < 100 patients.

resultsOf 374 identified publications, 16 met the inclusion criteria for this review. No model was specifically designed to compare risk-adjusted readmission rates at the hospital level or calculate scores predicting a patient's risk of readmission. The studies providing multivariable models of patient-level and/or process-of-care factors associated with readmission varied in stroke definitions, data sources, outcomes (all-cause and/or stroke-related readmission), durations of follow-up, and model covariates. Few characteristics were consistently associated with readmission.

conclusionsThis review identified no risk-standardized models for comparing hospital readmission performance or predicting readmission risk after stroke. Patient-level and system-level factors associated with readmission were inconsistent across studies. The current literature provides little guidance for the development of risk-standardized models suitable for the public reporting of hospital-level stroke readmission performance.

Indexed as

Models, StatisticalStrokeHumansPatient ReadmissionPredictive Value of TestsQuality of Health CareRisk Factors

Identifiers

PMID20930150
PMCPMC3021413

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.