Rapid Learning Systems to Improve Patient Outcomes and Control Health Costs
Bharat Rao, Siemens Healthcare USA
Abstract
Healthcare is on the verge of a revolution, which will be driven by “knowledge.” Traditionally, medical knowledge has being derived from carefully conducted clinical studies; now, a new form of knowledge is emerging – that created by “rapid learning systems” that will mine vast amounts of electronic patient data collected in routine care.
Consider these trends over the past two decades: the quantity and precision of diagnostic data available for a single patient has increased dramatically, the amount of published medical knowledge is doubling every few years, and a number of promising therapies have been developed. Despite all these advances, medicine remains largely mired in a ‘one size fits all’ paradigm that has led to an explosive increase in patient costs without a concomitant improvement in patient care.
Data Mining has tremendous potential in healthcare: by individualizing care to the specific patient it is possible to achieve the dual aims of controlling healthcare costs while improving patient outcomes.
In this talk, I will briefly present data mining solutions that analyze millions of patient records, impacting three major areas in healthcare. These include automated quality measurement and decision-support from hospitals EMR’s, computer-aided diagnosis systems to identify suspicious lesions on medical images, and “rapid learning systems” to develop predictive models for personalized medicine. The last is based on a first-of-kind rapid learning system: a Euro-US health IT network spanning cancer centers in 5 nations to learn personalized therapies for lung cancer.
The majority of the talk will present case studies that illustrate some of the challenges unique to mining healthcare data, and identify a few promising areas for research. These include the breakdown of traditional assumptions inherent in most mining algorithms, learning from multi-source systems, and the development of predictive models for personalized medicine. We conclude with a glimpse of a more-efficient healthcare future, where treatment decisions are driven by evolving knowledge that is continuously mined from patient records collected in health systems all over the world.
Biography
Bharat Rao, PhD is Senior Director, and Head of the Knowledge Solutions (KS) group, for the Health Services business unit in Siemens Healthcare. The KS group, headquartered in Malvern, PA, USA, has developed and deployed data analytics solutions that analyze millions of patient records, impacting three major areas in healthcare. These include, automated quality measurement and decision-support from hospitals EMR’s, computer-aided diagnosis systems to identify suspicious lesions on medical images, and predictive models for personalized medicine.
Dr. Rao has received multiple international awards, including the ACM SIGKDD (Data Mining society) Service Award in 2011 for “service to society for pioneering data mining applications in healthcare products that reduce healthcare costs and improve patient care.” He was also named the Siemens Inventor of the Year in 2005, awarded yearly to one employee in Siemens Healthcare (45,000 employees worldwide) for the REMIND data mining platform. He is the only two-time winner of the International Data Mining Practice Prize, for the best deployed industrial and government data mining application, awarded by IEEE & ACM respectively.
Dr. Rao is recognized as a leading international expert in machine learning, healthcare analytics and mining ‘big data.’ He has been granted 41 patents (50 more pending), received multiple best paper awards and has published over 100 scholarly publications and one book. He is currently leading an international consortium to develop a Euro-US cancer research health IT network to develop personalized therapies for lung cancer. The products developed by Dr. Rao’s group are used daily by thousands of radiologists worldwide to analyze medical images, and in dozens of US hospitals to help meet the needs of US health reform and qualify for incentive payments.
Dr. Rao received a B.Tech in Electronics Engineering from the Indian Institute of Technology, Madras, and an M.S. and Ph.D. focusing on machine learning from the Dept. of Electrical & Computer Engineering, University of Illinois, Urbana-Champaign, in 1993. After his PhD, he joined Siemens Corporate Research, and formed the Data Mining group. In 2002, he moved to Siemens Healthcare to help found the “Computer-Aided Diagnosis & Therapy” group.
Dr. Rao's passions outside of the sphere of Science and Business include the sport of Cricket, Classic Rock, the history of Science, and the study of Philosophy and Religion. He is married and has two children.
