Year of Publication
Doctor of Nursing Practice
Dr. Martha Biddle
Dr. Tara Blair
Dr. Debra Moser
Background: There is an increased need to identify factors associated with higher risk for excessive HF re-hospitalizations due to hospitals receiving financial penalties related to these re-hospitalizations and poorer patient outcomes. Identifying HF patients at highest risk for re-hospitalization with a screening instrument upon admission to the hospital would allow for early implementation of interventions tailored around reducing risk factors for re-hospitalization.
Objectives: The specific aims of this study were to 1) identify characteristics that were predictive of HF re-hospitalization; and 2) use those characteristics to create a screening instrument.
Methods: A total of 158 patients (age=63±13; 50.6% female; 73.4% Caucasian; 63.3% NYHA class III/IV) admitted with a primary or secondary diagnosis of HF were included in this study. Patient’s knowledge of HF symptoms, along with socio-demographic, biophysical, and cognitive information was assessed by data collected with validated instruments as well as the electronic medical record. Chi square tests and independent t-tests were used to examine bivariate differences in the readmitted and the non readmitted groups. Cox proportional hazards modeling was used to predict the outcome, or time to hospitalization, based on the predictor variables.
Results: The mean time to re-hospitalization was 68 days. Only 8 patients were re-hospitalized within the first 30 days. Depressive symptoms scores was the only variable identified as being significantly different (p
Conclusions: Screening HF patients at highest risk for re-hospitalization and those with depressive symptoms will allow healthcare providers to individualize interventions to improve HF patient outcomes and reduce costly hospital re-hospitalizations.
Taylor, Kelly L., "Prediction Screening to Identify Heart Failure Patients at High Risk for Readmission" (2016). DNP Projects. 79.