Abstracts Health Sciences

Quality of Care for Long-term Care Residents Living with Heart Failure in Ontario and Predictors of Hospitalization

by Mudathira Kadu

Background Heart failure (HF) is a disease that is on the rise, particularly in the aging population. It is common amongst residents of long-term care homes (LTCHs). Complicating the diagnosis and treatment of HF is the interaction of geriatric symptoms and comorbidities. Literature also suggests that in addition to being under-detected, HF management is suboptimal in the long-term care setting. The combination of the complex nature of the disease in older adults, as well as poor management practices can lead to adverse outcomes such as hospitalization, depression, cognitive decline, loss in activities of daily living (ADL) and mortality. This study addressed the following research questions: 1. Upon admission, what are the clinical and demographic characteristics of residents living with HF, compared to those living without HF? 2. In residents with HF, what admission clinical and demographic characteristics are associated with hospitalization? 3. What is the quality of care for residents with HF in Ontario LTCHs? 4. Are there regional variations in quality of care for residents with HF in Ontario? Methods The data in this study were based on the InterRAI Minimum Data Set Instrument (MDS) 2.0 assessments of residents aged 65 years and older, who were admitted to LTCHs in Ontario between January 1st, 2011 and December 31st, 2013. Residents with HF that had an end-stage disease, an expected survival of less than six months, receiving hospice care or in palliative units at admission, were excluded. Demographic and clinical information of residents with HF, and no HF at admission were summarized using means and standard deviations (SD) for continuous measures, and frequencies and percentages for categorical measures. Chi-square test was be used to evaluate whether the differences were significant in categorical measures, while continuous measures were analyzed using t-tests. To examine predictors of hospitalization, bivariate associations of demographic and clinical characteristics with spending at least one day in a hospital, were analyzed at the significance level of alpha= 0.05. In addition to p-values and odds ratios, 95% confidence intervals (CI) were used to determine whether the clinical variables were significantly associated with hospitalization. For the multivariable analysis, variables found to be significant at a bivariate level were included. Logistic regression modeling using generalized estimating equations (GEE) was used. Variables identified from the bivariate analysis were individually added to the model using step-wise selection. The C-statistic estimated the model sensitivity to predicting hospitalization The MDS Third Generation QI scores across all local health integration network (LHIN) were used to demonstrate variability between them by quality domain. Two steps were carried out to understand the overall variability in QI scores among LHINs over time: 1) the adjusted QI scores for each LHIN were calculated within each quarter; 2) the aggregated median, interquartile range,…