Online Program

Predicting hospital readmission in patients with heart failure: Usefulness of psychosocial factors not included in established risk scores

Tuesday, November 5, 2013 : 8:56 a.m. - 9:14 a.m.

Julia Logan, Research and Development, Veterans Affairs Medical Center, NY, NY
Carrie Freeman, Research and Development, Department of Veterans Affairs, NY, NY
John Choi, MPH, Research and Development, Department of Veterans Affairs, NY, NY
Maria Antonia Rodriguez, PhD, Research and Development, Department of Veterans Affairs, NY, NY
Binhuan Wang, PhD, Research and Development, Department of Veterans Affairs, NY, NY
Sundar Natarajan, MD, MSc, Medicine, VA New York Harbor Healthcare System/NYU School of Medicine, NY, NY
Background: Frequent readmissions are a major healthcare problem. Heart failure (HF) is the leading cause of readmission. We incorporated psychosocial factors into the In-Patient Evaluation Center (IPEC) and Yale risk scores to evaluate if they provide better prediction of readmission within thirty days than the risk scores alone.

Methods: The additional factors selected were smoking, alcohol use, living alone, depression/anxiety, and enrollment in Telehealth and the Visiting Nurse Services. Data were collected using patient surveys and medical record review. Receiver Operating Characteristic (ROC) curve analyses were performed by comparing the Area Under the Curve (AUC) for the two risk scores as well as augmented risk scores that included the aforementioned six factors to determine their accuracy in predicting hospital readmission. All comparisons were to chance (AUC=0.5).

Results: We evaluated 83 discharged HF patients. The AUC (with standard error) for the IPEC and Yale risk scores were 0.5608 (0.0791) and 0.5547 (0.0723). After the addition of the covariates, the augmented IPEC and augmented Yale AUC's were 0.6563 (0.0748) and 0.6428 (0.0702). When compared to chance, the IPEC (p= 0.44) and the Yale (p=0.45) scores were not statistically different; the augmented IPEC (0.03) and the augmented Yale (0.04) were statistically different.

Conclusion: Psychosocial factors significantly improve the prediction of readmission. This could lead to developing more accurate risk score calculators and programs to target psychosocial issues relevant to readmission. This improvement in care may lead to a decrease in readmissions, which would benefit both HF patients and the healthcare system.

Learning Areas:

Chronic disease management and prevention
Clinical medicine applied in public health
Public health or related research
Social and behavioral sciences

Learning Objectives:
Compare the IPEC and Yale risk calculators used to predict readmission for patient with Heart Failure with augmented risk scores integrating social factors. Evaluate how well the raw and augmented Yale and IPEC scores predict time to readmission. Demonstrate the need to consider the following psychosocial factors when predicting readmission: Living Alone, Tobacco Use, Alcohol Use, Enrollment in Telehealth, Enrollment in Visiting Nurse Services, and Depression/Anxiety.

Keyword(s): Heart Disease, Prevention

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am an experienced researcher with formal training in clinical medicine and epidemiology. I have been on the faculty at NYU for the past ten years and have published several papers in epidemiology.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.