Causal inference is used to answer cause and effect research questions and yield estimates of effect. These study design considerations and statistical methods address the effects of confounding variables and other potential biases, and allow researchers to answer questions such as, “Does treatment A produce better patient outcomes as compared to Treatment B?”
Causal study interpretations have traditionally been restricted to randomized controlled trials; however, causal inference applied to observational data is growing in importance, driven by the need for generalizable and rapidly delivered real-world evidence to inform regulatory, payor, and patient/provider decision making. The application of causal inference methods leads to stronger and more powerful evidence, and when these techniques are applied to observational data, the results generated are both from and for the real world.
A life sciences client wanted to know whether patients with type 2 diabetes taking a specific GLP-1 RA agent were more adherent and persistent relative to other antidiabetic medications.
Causal inference with observational data combines numerous theoretical and technical concepts, necessitating specialized training and competency. HealthCore’s Health Economics & Outcomes Research (HEOR) and Safety & Epidemiology (S&E) Research teams offer highly specialized scientists, access to a robust source of integrated real-world data, and decades of experience necessary for successfully employing these methods.
HealthCore’s experienced scientists can collaborate with your team to curate the most appropriate research questions and identify the optimal study design and analytic approach to address your specific needs. Whether working to satisfy regulatory requirements or generating evidence regarding an important public health concern or other creative scientific endeavor, HealthCore can help you find evidence and truth at the core of healthcare.
“Causal inference applied to observational data is growing in importance, driven by the need for generalizable and rapidly delivered real-world evidence to inform regulatory, payor, and patient/provider decision making.”— Michael Grabner, PhD