Data science is rapidly growing in many industries, including healthcare. However, the amount of healthcare information available for longitudinal research is often relatively small, with only sporadic data being available for any single patient. For example, information within the electronic health record (EHR) is typically obtained at large time intervals (usually hours or days), and nearly no data are captured from patients between healthcare encounters.
In this session, Dr. Schulz will describe the benefits of incorporating patient-generated data into clinical care and translational research. He will also describe how other large data sets can be combined with this information to advance precision medicine. From a technical perspective, this session will describe how Yale New Haven Health has worked to collect patient-generated data and integrate provider-generated data, such as genomics and continuous patient monitoring, into their data science platform.