PCORnet Q&A:
How does external validity come into play when planning and conducting projects in the database? PCORnet research teams take a variety of different approaches depending on the clinical question at hand. They often specifically discuss the degree to which in-network study populations are representative of the overall population of interest, which can vary substantially based on the goals of the research. This representativeness can include demographic factors, comorbidities, health care delivery-level factors, and broader societal factors. If new populations are being recruited into pragmatic trials or observational cohorts within PCORnet, the study coordinators may either target the overall PCORnet population or more specific recruiting targets (such as specific underserved populations). Finally, just like Sentinel and CNODES, differences between study sites and recruitment groups are frequently explored when different associations or effects are observed within nodes of the network.
What target populations, if any, underlie most analyses? Because of the broad mission of PCORnet, specific target populations vary. That said, most target populations are some subset of patients residing in the United States with access to healthcare.
Are there ways to generalize the findings of the nodes to the network? There are some existing ways to generalize site-specific estimates, like meta-analyzing the estimates after checking for heterogeneity. The focus is generally on estimating a network-wide treatment effect. How these methods are applied varies depending on the research team conducting the study and their importance for the clinical question at hand.
How easily can node-specific estimates be transported between nodes or to external populations? Currently, there are no out-of-the box solutions for transporting estimates in this fashion. That said, research groups can generate (if analyzing individual-level data) or request (if the PCORnet Coordinating Center is generating aggregate tables) cross-tabulation tables to stratify queries based on potential effect measure modifiers.
Are choices ever made to maximize target validity, rather than internal validity or precision? Target validity is frequently a major consideration when PCORnet’s partner networks conduct large distributed pragmatic trials. The diversity of the data and the direct relationships with clinicians enable researchers to assess this target validity and perform in-depth evaluation of study results within participating sites.