Patterns and Predictors of Early Hospital Readmission in Patients With Congestive Heart Failure

Hallerbach, M.; Francoeur, Amanda; Pomerantz, Sherry; Oliner, Craig; Morris, D. Lynn; Eiger, Glenn; Cohn, Jeffrey; Goldfinger, Michael

doi:10.1177/1062860607310916

Cited by 31 publications

(34 citation statements)

References 29 publications

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“…28 Claims-based algorithms may overestimate the preventability by not fully accounting for patient characteristics (eg, severity of chronic condition) and planned readmissions. 29,30 Medical record review, on the other hand, may provide added clinical detail but may be limited in ascertaining the contribution of sociodemographic characteristics that may not be documented in the medical record (eg, unmet social needs, medication adherence) or may occur outside of the hospital (eg, missed appointments, transportation barriers), thereby leading to underestimation of the likelihood of preventability. 13, 25, 31 -34 Interviews in combination with medical record review may provide a more global understanding of these circumstances leading up to, and after, a child's hospitalization.…”

Section: Figurementioning

confidence: 99%

Potentially Preventable 30-Day Hospital Readmissions at a Children’s Hospital

Toomey

Peltz

Loren³

et al. 2016

Pediatrics

104

117

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Section: Figurementioning

confidence: 99%

Potentially Preventable 30-Day Hospital Readmissions at a Children’s Hospital

Toomey

Peltz

Loren³

et al. 2016

Pediatrics

104

117

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“…Associated diagnosis of anemia, hypertension, and diabetes confer higher risk and are likely indicator of disease progression and are predictors of re-admissions and mortality [6,10,26,28,40]. Comorbidity has been shown as a predictor of unplanned readmission [41]. In addition, comorbidities were associated with increasing readmission in >80 year old within 30 days with comorbidities odds ratio = 2.6; 95% CI, 1.5-4.7 [42].…”

Section: Literature Reviewmentioning

confidence: 89%

Factors associated with heart failure readmissions from skilled nursing facilities

Ak¹

2017

Interventional-Cardiology

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Background: Despite guideline-driven pharmacological therapies and careful transitional care, the rates of preventable hospital re-admission of heart failure patients and associated costs remain unacceptably high in the SNF populations. Transfer to SNF is one strategy to limit hospitalizations. As such, 25% of patients are still symptomatic at time of discharge.Purpose: The objective of this study is to identify patient factors affecting re-admissions of HF patients residing in SNF within 30-days.Methods: A retrospective electronic chart review was completed on patients > 65 years with HF who were admitted into large medical center between 2012 and 2014. Descriptive statistics and univariate analyses using the chi-square test or Fisher's exact test for categorical variables and the Mann-Whitney test for continuous data was used to compare patients readmitted within 30 days vs. those who were not readmitted within 30 days. Significant factors associated with readmission in the univariate analysis (p < 0.10) were included for a multivariate logistic regression model. The analysis of LOS was accomplished by applying standard methods of survival analysis, i.e., computing the Kaplan-Meier product limit curves, where the data were stratified by readmission within 30 days (Yes vs. No). No data were considered 'censored'. The groups were compared using the log-rank test. The median rates for each group were obtained from the Kaplan-Meier/Product-Limit Estimates and their corresponding 95% confidence intervals were computed, using Greenwood's formula to calculate the standard error. Unless otherwise specified, a result was considered statistically significant at the p < 0.05 level of significance.Results: Fifteen variables: creatinine, weight difference, CKD, Angina, Arrhythmia, VHD, Tobacco, ADL, independent in bathing, independent in the toilet, S3 Heart sounds present, HJR, AF, Nitrates, and Hydralazine, were identified for the multivariate logistic regression as potential risk factors associated with "readmission within 30 days". Based on 23 readmissions within 30 days, our final model included only 2 predictor variables. Creatinine and ADLs were included in the final model as this subset of predictors was found to be the best for prediction of "readmission within 30 days". Creatinine (p < 0.0087) and ADLs (p < 0.0077) were both significantly associated with readmission within 30 days in the final logistic regression model. Every 1-unit increase in creatinine was associated with an 87% increase in the odds of being readmitted within 30 days (OR = 1.87). Those patients who require assistance with ADLs were over 9 times more likely to be readmitted within 30 days (OR = 9.25) as compared to patients who are independent.

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“…[9] Subsequently, a retrospective manual chart review at a large community teaching hospital found that focusing on renal failure alone could lead to major improvements in readmission rates. [10] Telehome monitoring was also found to reduce the number of readmissions and to improve functional status, leading to better quality of life. [11] In the mid-2000's, readmission reduction strategies gained a process improvement perspective, which involved an integrated delivery system model, process redesign, evidencebased practices, a multidisciplinary approach, and real time data collection.…”

Section: Evolution Of Readmission Reduction Strategiesmentioning

confidence: 99%

An environmental analysis of the evolution of readmission reduction strategies: A study of United States hospitals

Upadhyay

Opoku-Agyeman

Borkowski

2017

JHA

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Objective: Environmental factors have changed the manner in which issues in the U.S. healthcare industry are addressed. One of these changes is in the area of quality improvement, specifically readmission reduction. The purpose of this paper is two-fold: (1) analyze macro-environmental segments (political, technological, economic, and socio-demographic); and (2) trace the historic evolution of readmission reduction programs to understand how macro-environmental factors have shaped the development of readmission reduction strategies. Methods: Scopus, PubMed, and ABI/Inform electronic databases were searched for articles on readmission reduction programs from 2000 to 2014. In addition, literature on macro-environment was retrieved from these sources for the same time period. Studies were identified using specific search terms and inclusion criteria. A total of 24 articles were selected for review. Data on the following variables were extracted: type of organization studied, type of quality improvement strategy used, type of patients studied, and results of the strategy. In addition, an examination of macro-environmental factors that may have affected the above variables was done. Finally, results were integrated and presented in a chronological order. Results: Findings suggest that macro-environmental factors have influenced the development of readmission reduction strategies over time. This paper informs healthcare managers about being cognizant of environmental trends when devising readmission reduction strategies within hospitals. Conclusions: Insights from this paper urge hospital administrators to forge collaborations with key stakeholders while developing new quality improvement strategies when facing an unstable and complex environment.

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Patterns and Predictors of Early Hospital Readmission in Patients With Congestive Heart Failure

Cited by 31 publications

References 29 publications

Potentially Preventable 30-Day Hospital Readmissions at a Children’s Hospital

Potentially Preventable 30-Day Hospital Readmissions at a Children’s Hospital

Factors associated with heart failure readmissions from skilled nursing facilities

An environmental analysis of the evolution of readmission reduction strategies: A study of United States hospitals

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