Digital Health Innovation and Informatics
EDU 41 - Practical Big Data - Applications and Results
1:30 PM - 3:00 PM
Location: Room 008
Session Type: Educational
1.50 AMA PRA Category 1 Credits™
1.50 CAMPEP Credits
1.50 MDCB Credits
The rate at which Big Data applications are progressing beyond hype to practical reality is increasing as a few groups begin to incorporate aggregation and analysis into their clinical routines. These efforts are targeted at improving practice quality improvement (PQI), shortening clinical pathways for translational research and participation in multi-institutional studies. In addition, US based practices anticipate value of these systems to respond to emerging requirements of the Medicare Access and Children's Health Insurance Program Reauthorization Act of 2015 (MACRA) and the Medicare Merit-based Incentive Payment System (MIPS). To facilitate expanding Big Data applications to the wider community, this session will present examples, lessons learned from these efforts and recommendations from the multi-institutional 2017 Practical Big Data Workshop to provide motivational demonstrations for effort required to bring big data analytics to clinical practice. Specific recommendations for approaches to incorporate these objectives into routine clinical practice will be presented. With a focus on experience with practical rather than projected solutions, presenters will detail 5 key areas: 1. Results from application of big data to clinical practice 2. Practical recommendations on best practices with Electronic Health Record, Radiation Oncology Information Systems and Treatment Planning Systems 3. Using Big Data to improve patient safety 4. Standardization to improve clinical practice flow, big data aggregation and federated databases 5. Application of Machine Learning to Clinical Data
- Discuss results demonstrating benefits of big data applied to practice quality improvement.
- Develop a plan of action to make data in their clinic more accessible for aggregation and analysis.
- Describe specific machine learning approaches and implications for their data.
1:30 PM - 1:45 PM
Practical Results from Application of Big Data Analytics to Clinical Practice
Speaker: – University of Michigan
1:45 PM - 2:00 PM
Practical Steps and Driving Factors (MACRA, MIPS, PQI) For Making Big Data Aggregation Clinical Routine
2:00 PM - 2:15 PM
Mining Clinical Big Data for Patient Safety in Radiotherapy
2:15 PM - 2:30 PM
Role of Standardizations for Multi-Institutional Data Exchange (TG-263 and beyond)
2:30 PM - 2:45 PM
Applying Machine Learning Methods to Clinical Data