Process guide for inferential studies using healthcare data from routine clinical practice to evaluate causal effects of drugs (PRINCIPLED): considerations from the FDA Sentinel Innovation Center

Non-interventional studies, also referred to as observational studies, are conducted using real world data sources typically including healthcare data that are generated during provision of routine clinical care (including health insurance claims and electronic health records). These studies provide an opportunity to fill in evidence gaps for questions that have not been answered by randomized trials.1 However, generating decision grade evidence from healthcare data requires a robust causal framework to avoid introducing bias. Numerous tools aimed at improving the conduct or reporting of these non-interventional studies are available. Broad guidance documents discuss the methodology for non-interventional studies—such as the best practices for pharmacoepidemiological safety studies by the Food and Drug Administration (FDA)2 and the European Network of Centres for Pharmacoepidemiology and Pharmacovigilance (EncEPP) guide on methodological standards in pharmacoepidemiology.3 Quality assessment tools such as ROBINS-I4 and GRACE checklist5 assist with the evaluation of bias in published studies. Reporting tools such…
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