Future of Real-World Evidence: Common Data Models and OHDSI Tools Used in the COVID-Real Case Study

The future of real-world evidence (RWE) requires the use of Common Data Models to streamline the analysis of electronic health records (EHR) in near real-time. The Observational Medical Outcomes Partnership (OMOP) data model is gaining global acceptance thanks to the Observational Health Data Sciences and Informatics (OHDSI, pronounced “Odyssey”) community, composed of more than 350 researchers with a coordinating center at Columbia University. Besides OMOP, OHDSI develops high-quality, open-source tools to analyze real-world data (RWD). In March 2020, these tools were quickly leveraged in an enormous effort to provide fast and reliable evidence to fight against COVID-19 using volunteer data partners.

In this webinar, featured speakers will explain “COVID-Real,” an OHDSI sub-study conducted in Spanish hospitals by TFS, a contract research organization (CRO) with large RWE experience, and IOMED, a technology company using OMOP and natural language processing (NLP) to extract free text information. Study procedures and results will be explained, together with the main challenges and lessons learned under the first approach to OHDSI-OMOP tools by the participating EU hospitals.

Source databases included all subjects with at least one healthcare encounter with the participating hospitals, with several million data points and thousands of variables and cohorts. The results comprise all information collected routinely in the clinical practice: inpatient (hospital) care, outpatient specialist care, emergency room visits and partial information from other settings, like primary care and pharmacy care, present in free text notes from EHRs. The main strengths were large patient numbers and comprehensive information. The main limitations were those inherent to retrospective database studies, especially the risk for underestimation/misclassification of conditions or outcomes, due to incomplete coding and/or EHR information.

All data is publicly available at https://data.ohdsi.org/Covid19CharacterizationCharybdis/ and all updates on other ongoing analyses can be found at https://www.ohdsi.org/covid-19-updates/

Register for this webinar to hear expert speakers explain the great experience of engaging hospitals in global COVID-19 research and making them aware of the usefulness of the newest technologies to extract and analyze information in almost near-real-time, which had been impossible only a few years ago. The OMOP data model and related tools constitute a new paradigm in RWE research and will change the perception of observational studies. An increasing number of EU Hospitals are understanding the great potential of their EHRs and starting to trust in external researchers thanks to OHDSI studies. The ongoing European Health Data & Evidence Network (EHDEN) initiative is also contributing to this transition, by providing funding to convert hospital data to OMOP and participate in the OHDSI studies. Since March 2020, global RWE research has become a reality.

Speakers

Neus Valveny, PhD, Senior Director, Head of RWE at TFS HealthScience

With a PhD in Human Genetics and 20+ years´ experience, Neus combines a passion for statistics and epidemiology with experience in designing and running 100+ real-world studies. Neus consults with biopharma on the best RWE and late-phase study design and execution, helping them determine the best path forward.

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Gabriel Maeztu, MD, Co-Founder & CTO at IOMED

As a medical doctor (MD) and mathematician, Gabriel combines his two passions working at the intersection of medicine and machine learning. He works with large amounts of data to build tools that help physicians to contextualize all the information and make better decisions. Gabriel believes that the cross-section between medicine and data-driven technologies will define the medicine of the future.

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