Data Analytics for Readmission

Our team works closely with Emory Healthcare's Office of Quality, Information Services, the Department of Surgery, and nursing staff to leverage our data analytics capabilities to develop tools that can be used to carryout quality data analyses and decision support.  We have also established a collaborative relationship with University Healthsystem Consortium (UHC). A current joint study focuses on analyzing historical datasets to obtain detailed temporal characterizations of co-morbidities. The intended goal is to then use these co-morbidity characterizations to improve healthcare professionals' ability to predict readmissions, length of stay, and in-hospital mortality.

Papers

Sharath Cholleti, Andrew Post, Jingjing Gao, Xia Lin, William Bornstein, Dedra Cantrell, Joel Saltz. "Leveraging Derived Data Elements in Data Analytic Models for Understanding and Predicting Hospital Readmissions." AMIA 2012 Annual Symposium. Nov. 3-7, 2012. Chicago, IL.

CCI presentation at UHC Conference September 2011

Data Analytics for Readmission: Temporal features, predictive modeling