Areas of Expertise
Areas of Expertise
Time Zone
Time Zone
(GMT-08:00) Pacific Time (US & Canada)
San Francisco, USA

Bob Rogers PhD is Chief Data Scientist at Apixio, whose mission is to use Big Data analytics to organize the world's patient information to improve quality and lower cost in healthcare. Dr. Rogers is responsible for strategic direction and development of the algorithms at the core of Apixio's applications. He is also Apixio's liaison to the medical and academic communities. Dr. Rogers is the founder of Counterpart Consulting, a consulting firm specializing in advanced analytics for hedge fund and medical applications. Prior to Counterpart Consulting, Dr. Rogers was Senior Product Manager at Carl Zeiss Meditec where he was responsible for ...See All


Bob received his undergraduate degree in physics from UC Berkeley and his PhD in physics from Harvard University.

Other Sites
Expert Academy on LiL
1 Completed Sessions
Last Session:
Thu Sep 19 2013 at 07:00 pm EDT
Last Log-in:
Mon Sep 23 2013 at 08:52 pm EDT
On Learn It Live Since:
Friday Sep 6, 2013
Learning Intrest
About Bob Rogers
Group Classes (1)
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Bob Rogers Big Data Master Class - One Time Only! Thursday September 19th 2pm PT/5pm ET $25 Description: In this presentation, Bob Rogers will demonstrate the potential value of Big Data to healthcare organizations with two very timely use cases: Risk Assessment in the Affordable Care Act: When the Affordable Care Act (ACA) takes effect in January, 2014, it will profoundly change the landscape of the healthcare business. One key element of the ACA is the requirement that risk scores, based on conditions documented in the clinical record, be computed for entire populations of insured patients. Unfortunately, more than 63% of the key clinical information in a healthcare system is missing from the coded data in the EHR and can only be found in text and scanned documents. Healthcare provider organizations are using Big Data analytics to extract the required information from documents to power risk assessment and other applications such as quality reporting, population management and proactive real-time alerting. Big Data in Pharma: Recent exciting results show that Big Data analytical techniques can be effectively used to analyze the clinical data for large numbers of patients (including both structured data and textual documents such as encounter notes, consult letters and discharge summaries) to reveal new facts about drugs. Specifically, adverse events can be seen in the data, as well as safety and effectiveness of off-label drug usage. The implications of real-time monitoring of such patterns "in the wild," a true Big Data application, for pharmaceutical portfolio management and public safety are profound. These use cases will provide participants with a context for understanding some of the more important technical aspects of Big Data. Learning Objectives 1. Highlight the importance of unstructured data to healthcare organizations. 2. Understand how Big Data can surface information that is crucial to healthcare. 3. Identify which Big Data technologies support key use cases, and why.