Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory: Table 1

TLDR

Widespread sharing of electronic health record and patient‑reported outcome data can strengthen national capacity for cost‑effective clinical trials and embed research within routine care, while pragmatic clinical trials now draw on rich, continuously fed clinical and operational data; the NIH Health Care Systems Collaboratory, launched in 2012, partners with healthcare systems to promote tools and strategies that leverage heterogeneous real‑world data to improve trial efficiency, relevance, and generalizability. The authors introduce the Collaboratory’s Phenotype, Data Standards, and Data Quality Core and report early observations from researchers implementing pragmatic clinical trials in large healthcare systems. They identify gaps in knowledge and outline an informatics research agenda focused on defining, applying, and validating electronic health record–based phenotypes across diverse settings.

Abstract

Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can draw on rich sources of clinical and operational data that are continuously fed back to inform research and practice. The Health Care Systems Collaboratory program, initiated by the NIH Common Fund in 2012, engages healthcare systems as partners in discussing and promoting activities, tools, and strategies for supporting active participation in PCTs. The NIH Collaboratory consists of seven demonstration projects, and seven problem-specific working group 'Cores', aimed at leveraging the data captured in heterogeneous 'real-world' environments for research, thereby improving the efficiency, relevance, and generalizability of trials. Here, we introduce the Collaboratory, focusing on its Phenotype, Data Standards, and Data Quality Core, and present early observations from researchers implementing PCTs within large healthcare systems. We also identify gaps in knowledge and present an informatics research agenda that includes identifying methods for the definition and appropriate application of phenotypes in diverse healthcare settings, and methods for validating both the definition and execution of electronic health records based phenotypes.