Session (CTI)

Separate registration required.

This course will focus on the opportunities and practical applications of conducting real-world data (RWD) studies and generating real-world evidence (RWE) for medical devices and diagnostics (MDD). RWD is increasingly being leveraged to support a variety of purposes in the MDD space, including regulatory, reimbursement, health technology assessment (HTA), and business needs. Leveraging RWD, especially secondary data sources, for MDD poses unique challenges, such as the difficulty in identifying devices in RWD sources, device operator characteristics potentially influencing outcomes, and the need to consider continuous device iterations in RWE generation. Thus, high-quality data and carefully designed studies are critical to increase the credibility and acceptance of RWD/E for MDD.

Additionally, the course will provide an overview of the best practices, processes, and methods to design and execute studies to gather market insights and generate high-quality evidence for multiple stakeholders. The course will review different types of secondary data sources and methods to conduct descriptive analyses and comparative effectiveness research along the MDD product lifecycle. Specific topics will include the common questions that are answered with secondary data and the challenges and potential solutions that are unique to MDD products. Case studies will focus on a variety of technologies, from new technologies to follower products, and the strategies that are used to increase the chances of acceptance to gain and expand market access.

PREREQUISITES: Participants should be familiar with general HEOR methods and tools used in MDD, and the general concepts of real-world data and evidence, including the types of healthcare data that is generated as part of routine healthcare.