Trends over the past two decades indicate that 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.
We are on the verge of a paradigm shift in healthcare. Traditionally, medical knowledge has being derived from carefully conducted clinical studies, namely evidence-based-medicine; now, a new form of evidence is emerging – that created by rapid learning systems that will mine vast amounts of electronic patient data collected in routine care, to create “evidence generated medicine.” Thus, mining the millions of patient records collected routinely in the daily care of patients has tremendous potential to individualize care to the specific patient.
In this presentation, I will describe a first-of-its-kind US/Euro health IT network consisting of 10 cancer centers in 5 nations. In this network, cancer centers are able to securely learn personalized models from patient data collected across all centers. Learned models for predicting patient survival and side effects for 3 different cancers (lung, rectal, larynx) have been made available to the public and physicians at www.predictcancer.org.
Creating models from patient data collected across multiple centers provides statistical power, but leads to several challenges:
In this presentation, we will describe how we overcome these issues to learn personalized models that have been statistically validated and published in leading conferences and journals. Additionally, we describe how pharma companies can mine these patient records to more efficiently find patients for clinical trials. The majority of the talk will present case studies and results that illustrate some of the challenges and opportunities unique to mining healthcare data. 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.
Bharat Rao, PhD is Senior Director and Head of the newly-formed Center for Innovations in the Health Services (HS) business unit in Siemens Healthcare, headquartered in Malvern PA. The Siemens HS unit develops and markets enterprise information technology and business intelligence solutions for hospitals and other healthcare providers. The Center for Innovations was established in May 2012 with the vision to foster thought-leadership for Siemens in the dynamic field of healthcare IT. The Center’s goals are to create a continuous-innovation pipeline of new products, services and capabilities; to develop and rollout processes to translate innovation into commercial success; establish collaborations with luminary customers, academic & industry partners; and to drive an innovation agenda that impacts the entire HS portfolio and workforce.
Previously, Dr. Rao led the Knowledge Solutions group, Healthcare Analytics and Business Intelligence which develops and deploys 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. The group launched the first-to-market startup offering in healthcare quality, Soarian Quality Measures (and its cloud counterpart, the Quality Reporting Service) which is now an essential part of Siemens solution to satisfy the meaningful use requirements for US health reform.
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 Case Studies & 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 45 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.
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.
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