Holmusk Joins Diverse Group of RWE Leaders to Publish Key Considerations for the Future of Real-World Data

January 18, 2022

Holmusk, a leading global data science and digital health company building the world's largest real-world evidence (RWE) platform for behavioral health, recently contributed to key considerations that will enable the continued expansion of real-world data (RWD) usage over the next decade.

The considerations, which were included in a paper published in PLOS Digital Health on Jan. 18, outline what will be needed to ensure the safe and meaningful use of RWD in the future and touches on a multitude of critical topics, from data privacy to leveraging machine learning.

The new paper represents a unique collaboration that incorporates the diverse perspectives of many leaders key to the RWD space, including pharmaceutical companies, academic institutions, and companies that specialize in health technology and real-world evidence. In addition to Holmusk, the authorship list includes representatives from Verana Health; DATA-CAN UK Health Data Research Hub for Cancer, hosted by UCLPartners; University College London; Imperial College London; and Mayo Clinic.

“Health data generation continues to increase, alongside the proliferation of digital health solutions. It is vital to increase sustainable data aggregation that can enhance direct patient care and enable equitable population health research and artificial intelligence development,”said the paper’s lead authors, Joe Zhang, MD, of Imperial College London, andSanjay Budhdeo, MD, MSc, of University College London. “This paper brings together viewpoints from stakeholders in diverse sectors to delineate key best practices for enhancing health data resources.”

 The paper sets forth a framework of seven best practices that all stakeholders—including providers, payors, health systems, and academic organizations—should consider as they look to the future of RWD. They include:

·      Adhering to international data standards

·      Considering and customizing quality assurance depending on use case

·      Incentivizing careful and complete data entry to maximize data’s value

·      Using natural language processing to tap into unstructured data sources

·      Implementing solutions that enable flexible analytics that can be used in nearly real time

·      Ensuring data privacy and patient protection, while returning value to patients

·      Actively working toward equity and representation within RWD datasets

“It was a privilege to work with such an accomplished group of authors to set forth best practices that will pave the way for a successful future for RWD,” said co-author Jordan Abdi, MD, of Holmusk. “We’re actively working to champion many of these best practices, such as leveraging natural language processing models to transform unstructured clinician notes into research-grade data.”

 To read the full paper, which was released from embargo Tues., Jan. 18, at 2 p.m. ET, visit PLOS Digital Health.

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