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Prior hospital admission predicts thirty-day hospital readmission for heart failure patients
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Abstract
Background: Hospital readmission is a significant health burden. More than 20% of heart failure (HF) patients are readmitted within 30 days of discharge leading to billions of dollars in health care expenditures. However, the role of prior hospital admissions to predict 30-day readmission for HF patients is not fully understood.
Methods: We retrospectively analyzed HF hospitalization data for 4 years at a single medical center. Association between prior admission and 30-day readmission after HF hospitalization was assessed using a multivariate logistic regression model.
Results: A total of 1,999 patients with index HF hospitalizations were identified, and 366 of them (18%) were readmitted within 30 days. The rate of readmission was 14%, 20%, and 33% in patients with 0, 1, ≥ 2 prior admissions. Patients with one prior admission had a 50% higher risk (confidence interval [CI] 1.10–2.05, p = 0.011) for readmission, while those with ≥ 2 prior admissions had a more than 3-fold increase in readmission (CI 2.27–4.09, p < 0.001), after adjustments for relevant clinical covariates. Prior hospital admission provided incremental value in predicting readmissions, shown by the significant improvement in the readmission predictive model (C-statistics increased from 0.57 to 0.63). However, neither the length of stay nor recency of prior admission was a significant factor in predicting readmissions.
Conclusions: Hospital admission prior to an index HF hospitalization is associated with a significantly increased risk for 30-day hospital readmission and could be used to identify patients at high-risk for readmission and potentially target interventions to reduce the risk of readmission for these patients
Abstract
Background: Hospital readmission is a significant health burden. More than 20% of heart failure (HF) patients are readmitted within 30 days of discharge leading to billions of dollars in health care expenditures. However, the role of prior hospital admissions to predict 30-day readmission for HF patients is not fully understood.
Methods: We retrospectively analyzed HF hospitalization data for 4 years at a single medical center. Association between prior admission and 30-day readmission after HF hospitalization was assessed using a multivariate logistic regression model.
Results: A total of 1,999 patients with index HF hospitalizations were identified, and 366 of them (18%) were readmitted within 30 days. The rate of readmission was 14%, 20%, and 33% in patients with 0, 1, ≥ 2 prior admissions. Patients with one prior admission had a 50% higher risk (confidence interval [CI] 1.10–2.05, p = 0.011) for readmission, while those with ≥ 2 prior admissions had a more than 3-fold increase in readmission (CI 2.27–4.09, p < 0.001), after adjustments for relevant clinical covariates. Prior hospital admission provided incremental value in predicting readmissions, shown by the significant improvement in the readmission predictive model (C-statistics increased from 0.57 to 0.63). However, neither the length of stay nor recency of prior admission was a significant factor in predicting readmissions.
Conclusions: Hospital admission prior to an index HF hospitalization is associated with a significantly increased risk for 30-day hospital readmission and could be used to identify patients at high-risk for readmission and potentially target interventions to reduce the risk of readmission for these patients
Keywords
heart failure, readmissions, prior admissions, predictive model
About this articleTitle
Prior hospital admission predicts thirty-day hospital readmission for heart failure patients
Journal
Issue
Pages
155-162
Published online
2016-01-07
Page views
2467
Article views/downloads
2001
DOI
10.5603/CJ.a2016.0005
Pubmed
Bibliographic record
Cardiol J 2016;23(2):155-162.
Keywords
heart failure
readmissions
prior admissions
predictive model
Authors
Donald P. McLaren
Roy Jones
Ronald Plotnik
Wojciech Zareba
Scott McIntosh
Jeffrey Alexis
Leway Chen
Robert Block
Charles J. Lowenstein
Valentina Kutyifa
