Leveraging Patient-Centered Health Data Sharing Platforms for Medical Product Evaluation: The Future of Real-World Evidence?

Published in Healthcare & Nursing
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By Sanket Dhruva, Joseph Ross and Nilay Shah

In March 2020, both the Centers for Medicare & Medicaid Services (CMS) and Office of the National Coordinator for Health Information Technology (ONC) released Final Rules that will provide patients with easy access and control over their electronic health data by establishing standards-based application programming interface requirements. Patients will be able to aggregate these data using smartphone-based applications and securely share with other parties, including researchers.

Today in npj Digital Medicine, we report the results of our study testing use of a patient-centered health data sharing platform, Hugo Health, to aggregate electronic health data from multiple sources (Figure), enrolling sixty patients undergoing bariatric surgery or catheter-based atrial fibrillation ablation at 2 tertiary care centers (Yale-New Haven Hospital and Mayo Clinic).

Our results are promising. We successfully obtained electronic health data from all patients at these two health systems, as well as 13 additional health systems. In addition, pharmacy data were aggregated for the 24 patients who used CVS or Walgreens pharmacies, including their prescribed medications.

More notably, we successfully aggregated personal digital device data from wearable activity monitors, tracking daily step counts, as well as digital weight scales for the patients who underwent bariatric surgery and single-lead electrocardiogram devices for patients the patients who underwent atrial fibrillation ablation.

Finally, we used the platform to survey all patients using patient-reported outcome measures, offering unique insights into patients’ post-procedural recovery, functional status, and disease-specific symptoms. All of these data were made available to patients and, with patient consent, aggregated by the platform and shared with the research team.

This study demonstrates the potential to use digital health technologies to enable research through patient-centered health data sharing platforms, using data collected during routine clinical care and in people’s everyday lives. This approach is unique because it engages patients as research partners and it can be employed for efficient development and deployment of registries, as well as for pragmatic clinical trials. Importantly, this approach has great potential when used for medical product evaluations and may offer a glimpse of the future of real-world evidence generation.

We are currently leveraging this research approach for several other pragmatic clinical trials, including two multi-center randomized clinical trials. For one, we will be testing the impact of a smartwatch’s electrocardiogram and irregular rhythm notification features as compared to an activity tracker on patient-reported quality of life and clinical utilization. For another, we will be examining clinical and patient outcomes associated with use of a prescription digital therapeutic (delivered via mobile app) for treatment of insomnia and depression as compared to usual care. Both trials will begin enrollment later this year. Finally, we are using this approach to prospectively assess the experience and management of acute pain among patients presenting to primary care, emergency departments or dental offices who receive new prescriptions for opioids.

We encourage other researchers to consider using digital tools to conduct patient-centered pragmatic research. With federal regulations increasingly ensuring patients have access to and agency over their electronic health data, there is great opportunity to advance meaningful, patient-centered research.

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  • npj Digital Medicine npj Digital Medicine

    An online open-access journal dedicated to publishing research in all aspects of digital medicine, including the clinical application and implementation of digital and mobile technologies, virtual healthcare, and novel applications of artificial intelligence and informatics.

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