LAUSR

Hospital readmission is an important quality-of-care indicator that reflects challenges in quality of in-patient care and the difficulty of coordination of care after the transition back into the community. It can also be a significant financial burden, especially as it relates to Medicare and Medicaid costs now and into the future. In this study, we develop a text-mining-based methodology for providing decision support to identify patients with Chronic Obstructive Pulmonary Disease (COPD), one of the leading causes of disability and mortality worldwide, that are likely to be readmitted. The proposed methodology is tested with real-life data to demonstrate how it can be used to help healthcare providers target high-risk discharged patients to reduce readmission.