New white paper from Evidation on person-generated health data
New white paper from Evidation on person-generated health data
In a new white paper, Evidation – the company measuring health in everyday life – describes best practices for organizations seeking to use PGHD to enhance their clinical product development programs, including real-world examples and case studies.
In the paper, Evidation builds upon the five takeaways of a 2021 joint FDA-industry meeting on this topic, providing insights from the company’s 10 years of working with the world’s top biopharma companies and other researchers to identify clinically relevant signal from wearables, surveys, and remote monitoring devices. Evidation expands upon the following actionable insights from the FDA meeting:
-
Provide value to research participants to improve retention by making data collection easy for participants (passive whenever possible), building community among participants, and developing meaningful content to help them manage their conditions.
-
Use evidence-based study designs to ensure collection of high-quality data by making questions patient-centric, applying thoughtful data cleaning and quality checks to address oddities and discrepancies, actively monitoring data quality, and listening to participant feedback.
-
Apply tried-and-true tools from traditional clinical research when appropriate by leveraging technology to remove barriers to entry, e.g., widening the enrollment funnel to be more inclusive, harnessing digital advertising to attract a more diverse participant pool, facilitating at-home testing, consolidating/transferring medical records, and conducting online pre-screening.
-
Leverage PGHD to gain unique insights into what matters most to participants by providing participants with choices and observing how they engage, which has critical implications for the development and optimization of interventions and management of symptoms and diseases.
-
Deploy PGHD methods to identify what isn’t being learned from clinical trials by using technology to capture information on disease progression, symptom experience, the economic burden of disease, and other questions that traditional trials are not asking.
