This biostatistical research tool set includes a series of guidance documents developed by the NIH Pragmatic Trials Collaboratory’s Biostatistics and Study Design Core. These documents, which focus on detailed aspects of statistical design for conducting PCTs, provide a synthesis of current developments, discuss possible future directions, and, where appropriate, make recommendations for application to pragmatic clinical research.

• Key Issues in Extracting Usable Data from Electronic Health Records for Pragmatic Clinical Trials
• The Intraclass Correlation Coefficient
• Unequal Cluster Sizes in Cluster-Randomized Clinical Trials
• Pair-Matching vs Stratification in Cluster-Randomized Trials
• Frailty Models in Cluster-Randomized Trials
• Small-Sample Robust Variance Correction for Generalized Estimating Equations for Use in Cluster-Randomized Trials
• Statistical Analysis Plan Checklist for Addressing COVID-19 Impacts

In 2019, the NIH Pragmatic Trials Collaboratory held a comprehensive workshop to explore and discuss statistical issues encountered with embedded PCTs. The Workshop Summary describes panel discussions with the principal investigators and statisticians of the NIH Collaboratory Trials and the challenges and solutions encountered during the design and analysis of their trials.

The 4 panel discussions covered the following topics:

• Measurement and Data: Outcomes, Exposures, and Subgroups Based on EHR Data
• To Cluster or Not to Cluster?
• Choosing a Parallel Group or Stepped-Wedge Design
• Unique Complications

This Workshop Summary also provides lessons learned and recommends tools to help others design and analyze future PCTs embedded in healthcare systems. For more on the design and analysis of PCTs, see the tools provided by the Biostatistics and Study Design Core.

The Biostatistics and Study Design Core thanks David M. Murray, PhD, director of the Office of Disease Prevention, National Institutes of Health, for his invaluable input into the creation of the research tools.