Abstract
Purpose: While much has been written about how distributed networks
address internal validity, external validity is rarely discussed. We
aimed to define key terms related to external validity, discuss how they
relate to distributed networks, and identify how three networks (the US
Food and Drug Administration’s Sentinel System, the Canadian Network for
Observational Drug Effect Studies [CNODES], and PCORnet, the
National Patient Centered Clinical Research Network, initiated and
supported by the Patient-Centered Outcomes Research Institute. Methods:
We define external validity, target populations, target validity,
generalizability, and transportability and describe how each relates to
distributed networks. We then describe Sentinel, CNODES, and PCORnet and
how each approaches these concepts. Results: Each network approaches
external validity differently Sentinel answers regulatory questions in
the general US population using data from commercial health plans and
Medicare fee-for-service beneficiaries and considers external validity
when exploring outliers or performing subgroup analyses to examine
potential heterogeneity of treatment effects. CNODES focuses on a
Canadian target population but includes UK and US data and thus has to
make decisions about which partners can be included in each analysis.
PCORnet supports a wider array of studies including randomized trials
and often assesses whether a given study will be representative of the
wider US population. Conclusions: There is no one-size-fits-all approach
to external validity within distributed networks. With these networks
and comparisons between their findings becoming a key part of
pharmacoepidemiology, there is a need to adapt tools for improving
external validity to the distributed network setting.