Decentralization of clinical research has been discussed and promised for some time; however, reliance upon sites still presents limitations, including the need to locate appropriate sites for recruiting a suitable patient population, the need for research staff to dedicate time to manual data abstraction, and the costs associated with each of these challenges. It’s time to disrupt the fragmented EHR landscape with patient-mediated medical record release to drive cost savings, lower burden on health care providers, eliminate data latency, and increase data quality.
The key to unlocking a hybrid or fully decentralized study design that will optimize your research objective(s) is in direct-to-patient research. Greatly minimizing, or even eliminating, the necessity of a research site is a tremendous feat, but how do you easily obtain longitudinal medical records in a standardized, fit-for-research format?
Seqster’s proprietary operating system integrates with EHR providers nationwide to standardize, harmonize, and visualize health data regardless of the EHR source. Patients can be recruited into any study directly or via sites. They are then able to seamlessly aggregate their comprehensive healthcare data in one secure location – for their own benefit as well as for any study they opt into.
Learn how patient-mediated medical record acquisition can fundamentally optimize study designs. By opening the possibility for truly decentralized research, you can generate powerful evidence of your product’s safety, effectiveness, and value with tremendous efficiency. Explore the details and practical possibilities with UBC’s VP of Real World Evidence Aaron Berger and Seqster’s CEO and Co-Founder Ardy Arianpour during this webinar.
Key Learning Objectives
- What is Patient-Mediated Medical Record Access and how is it critical to obtaining Real World Data?
- How does Real World Data Access relate to Clinical Study Design?
- What does a study that incorporates Real World Data Access look like, and how does it solve the challenge of siloed data in healthcare?
- Use cases including accessing more diverse and inclusive patient populations
