Decision Support System Helps Hospitals Prevent Heart Failure Readmissions

Abstract

University of Central Florida researchers have invented a decision support tool for enhancing patient care and reducing hospital readmissions related to heart failure (HF). The innovative support tool identifies and analyzes patient-centric human factors that affect hospital readmissions of patients diagnosed with heart failure. Results generated by the tool enable medical practitioners and patients to develop and use interventions that mitigate the risks of readmission. The tool analyzes items such as choice, rest, environment, nutrition, habits, activity and other human factors that affect a patient's health outcomes. 

Technical Details

The invention comprises a novel algorithm that identifies the significance of human factors related to hospital readmissions of heart failure patients. The algorithm incorporates structural equation modeling and meta-analysis to obtain the associated probability value for individual human factors that help to reduce readmissions of heart failure patients. In one example application, the invention uses data from a systematic review and meta-analysis of clinical trial studies on heart failure hospitalization and care management strategies. The system extracts and generates relevant data, rating the significance of human factors that influence heart failure patients' knowledge, motivation, attitude, preventive practices, and health outcomes. Care managers use the results to determine the clinical interventions and practices needed to help a particular heart failure patient avoid rehospitalization.

Benefit

Market Application