SAS Institute, Inc.
The implementation and adoption of Electronic Health Records, driven by advances in technology and disruptive legislative measures such as the Affordable Care Act, have created an unprecedented opportunity for researchers to apply innovative analytic approaches to the wealth of previously unavailable data. Although the opportunity to develop novel analytic methods in support of true data driven decision making in health care are significant, so are the challenges. The predominantly observational and highly dimensional nature of health care data and the lack of a common data model across diverse data sources present significant limits to current analytics methods. Of particular interest are challenges associated with understanding Heterogeneous Treatment Effects (HTEs) in diverse patient populations and more broadly, complexities associated with inferring causal relationships from observational data. Using publicly available health care data we will evaluate existing and novel analytic methods as well as data visualization and presentation methods.