Literature DB >> 23245581

When projecting required effectiveness of interventions for hospital readmission reduction, the percentage that is potentially avoidable must be considered.

Carl van Walraven1, Alan J Forster.   

Abstract

OBJECTIVES: Hospitals have strong incentives to decrease readmission rates. Not all hospital readmissions are potentially avoidable. Therefore, only a component of all hospital readmissions can be influenced by interventions designed to decrease them. In this study, we determined how effective interventions must be to attain specific reductions in hospital readmission rates. STUDY DESIGN AND
SETTING: A conceptual model of all readmissions and potentially avoidable readmissions was used to derive a mathematical relationship between the relative reduction in the total number of readmissions, the relative reduction in potentially avoidable readmissions, and the proportion of readmissions that are potentially avoidable.
RESULTS: When 22% of readmissions were potentially avoidable, achieving a 20% reduction in the total number of readmissions required a 91% reduction in potentially avoidable readmissions; decreasing potentially avoidable readmissions by 20% reduced total readmissions by 4.4%.
CONCLUSION: These results highlight that relative reductions in the total number of readmissions are notably lower than that for potentially avoidable readmissions. This separation in relative reduction of all and potentially avoidable readmissions increases as the proportion of readmissions deemed potentially avoidable decreases. These results have important implications for health care planners and researchers.
Copyright © 2013 Elsevier Inc. All rights reserved.

Mesh:

Year:  2012        PMID: 23245581     DOI: 10.1016/j.jclinepi.2012.08.005

Source DB:  PubMed          Journal:  J Clin Epidemiol        ISSN: 0895-4356            Impact factor:   6.437


  5 in total

1.  Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients.

Authors:  Andrew D Auerbach; Sunil Kripalani; Eduard E Vasilevskis; Neil Sehgal; Peter K Lindenauer; Joshua P Metlay; Grant Fletcher; Gregory W Ruhnke; Scott A Flanders; Christopher Kim; Mark V Williams; Larissa Thomas; Vernon Giang; Shoshana J Herzig; Kanan Patel; W John Boscardin; Edmondo J Robinson; Jeffrey L Schnipper
Journal:  JAMA Intern Med       Date:  2016-04       Impact factor: 21.873

2.  Assessing preventability in the quest to reduce hospital readmissions.

Authors:  Julia G Lavenberg; Brian Leas; Craig A Umscheid; Kendal Williams; David R Goldmann; Sunil Kripalani
Journal:  J Hosp Med       Date:  2014-06-25       Impact factor: 2.960

3.  Post-discharge follow-up visits and hospital utilization by Medicare patients, 2007-2010.

Authors:  Derek DeLia; Jian Tong; Dorothy Gaboda; Lawrence P Casalino
Journal:  Medicare Medicaid Res Rev       Date:  2014-05-09

4.  Factors associated with unplanned readmissions within 1 day of acute care discharge: a retrospective cohort study.

Authors:  Julie Considine; Debra Berry; Evan Newnham; Matthew Jiang; Karen Fox; David Plunkett; Melissa Mecner; Peteris Darzins; Mary O'Reilly
Journal:  BMC Health Serv Res       Date:  2018-09-14       Impact factor: 2.655

5.  Development and Implementation of a Complex Health System Intervention Targeting Transitions of Care from Hospital to Post-acute Care.

Authors:  Elizabeth J Austin; Jen Neukirch; Thuan D Ong; Louise Simpson; Gabrielle N Berger; Carolyn Sy Keller; David R Flum; Elaine Giusti; Jennifer Azen; Giana H Davidson
Journal:  J Gen Intern Med       Date:  2020-08-31       Impact factor: 5.128

  5 in total

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