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Session 4: Digital Technology and Machine Learning in RWD Collection and Analysis
Session Chair(s)
Paul M. Coplan, DRSC, MBA, MSC, FISPE
VP, Medical Device Epidemiology & Real-World Data Analytics, Johnson & Johnson, United States
Data gathered through personal digital devices is a rapidly growing area of RWD that can be used to understand patient health and quantify interventions’ effects on health in new ways. Such mobile health technologies can be used to aggregate data from wearable technologies, collect data on patient reported outcomes from patient-completed self-assessment questionnaires, and aggregate patient clinical records (eg, EHR and claims data) across multiple healthcare provider systems. In addition, the data generated by wearable technologies from the monitoring of human physical activities and behaviors, as well as physiological and biochemical parameters during daily life, are ripe for the application of pattern-recognition tools such as machine learning and artificial intelligence. The goal of this session is to learn from visionaries in the field about the potential for using digital technology for collecting RWD for health assessment and evaluation, and approaches to analyzing digital data to provide clinically relevant insights.
Learning Objective : - Enhance their understanding of progress in using apps like the FDA MyStudy app and the Hugo app to collect patient wearable, PRO and integrated EHR data for use in RWE studies
- Understand how machine learning analytical tools can enhance the understanding obtained from wearable data
- When ML models can be helpful vs standard regression models in prediction models using digital data of treatment safety and effectiveness
Speaker(s)
Incorporating Patient Reported Outcomes and Wearables into Studies: Progress with the MyStudy App at FDA
Senior Medical Advisor for RWE, Office of Medical Policy, CDER, FDA, United States
Using Digital Apps to Improve RWE Studies: Lessons Learned with Hugo Digital App
Harold H. Hines, Jr. Prof of Medicine and Director, Center for Outcomes Research, Yale University, United States
Michael Kattan, PHD, MBA
Department Chairman, Quantitative Health Sciences, Cleveland Clinic, United States