Reducing Unnecessary Hospitalizations of Nursing Home Residents

Ouslander, Joseph G.; Berenson, Robert A.

doi:10.1056/nejmp1105449

Cited by 151 publications

(145 citation statements)

References 5 publications

(5 reference statements)

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“…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]. Comorbidities were found to be frequently associated with 7 and 30 day readmission of SNF patients [43]. Older HF patients from SNFs residents who had acute episode leading to readmission had higher level of comorbidities with acute HF [26].…”

Section: Literature Reviewmentioning

confidence: 94%

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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Section: Literature Reviewmentioning

confidence: 94%

Factors associated with heart failure readmissions from skilled nursing facilities

Ak¹

2017

Interventional-Cardiology

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“…Processes associated with the ageing population will result in a steady increase of interest in long-term care services, such us long-term care units or nursing houses (Ouslander, Berenson 2011). Residential care refers to services of care and social support, other than nursing homes, provided in supported living arrangements (OECD 2008).…”

Section: Introductionmentioning

confidence: 99%

“…2) show only the complexity of the level of the services' quality measuring. Measurement of the quality of services performed by the residents and their families appears to be significant because of the rising cost of care and the expected value with respect to the expenditure incurred by them (Ouslander, Berenson 2011). The measurement of quality from the perspective of the family is an important element in making a decision regarding the selection of the facility.…”

Section: Introductionmentioning

confidence: 99%

Prospective Quality Attributes of Nursing Home Care Services

Ejdys

2016

9th International Scientific Conference “Business and Management 2016”

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Abstract. One of the forms of care for the elderly are the nursing homes, long-term care homes. Still, in many countries the low level of quality of such services is still the main criterion for the perception of objects as a final option, in the absence of alternative forms of care for an older person. The aim of the article is to seek answers to the questions about the expected quality of the services offered by nursing homes. The article presents the results of research on the expectations of the society in terms of quality of services, carried out on a sample of 602 Polish citizens. The study allowed to identify the key characteristics that determine the quality of services from the perspective of the future decisions related to the choice of the resort.

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“…This non-modifiable risk factor is often associated with cognitive deficits. Older age, disability status and increased LOS were associated with re-admission (Muus et al, 2010). Social and environmental factors may influence the severity and adaptability of aging process in older HF patients.…”

mentioning

confidence: 97%

“…The re-admission rate was increased from 23% to 27% within 30days (Allen et al, 2011). In addition, advanced age was identified as a significant contributor to re-admission among US veterans residing at SNFs (Muus et al, 2010). Likewise, there were high correlation between increasing age and readmission within 30 days and 90days (Schrager et al, 2013).…”

mentioning

confidence: 99%

Factors Associated With Heart Failure Readmissions From Skilled Nursing Facilities

Akande¹

2017

IJCH

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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. A receiver operating characteristic (ROC) curve was constructed to look at the final model's ability to predict the outcome. A numerical measure of the accuracy of the model was obtained from the area under the curve (AUC), where an area of 1.0 signifies near perfect accuracy. 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 is associated with an 87% increase in the odds of being readmitted within 30 days (OR = 1.87). Those patients who require assistance with ADLs are over 9 times more likely to be readmitted within 30 days (OR=9.25) as compared to patients who are independent.

show abstract

Reducing Unnecessary Hospitalizations of Nursing Home Residents

Cited by 151 publications

References 5 publications

Factors associated with heart failure readmissions from skilled nursing facilities

Factors associated with heart failure readmissions from skilled nursing facilities

Prospective Quality Attributes of Nursing Home Care Services

Factors Associated With Heart Failure Readmissions From Skilled Nursing Facilities

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