Causal inference with real-world data in health care research: a scoping review protocol and study within a review protocol

OBJECTIVE: This study will improve the understanding and application of causal inference methods in health care research using real-world data (RWD). It seeks to systematically synthesize existing methods across different data sources, and assess whether large language models (LLMs) can support key steps in review processes. INTRODUCTION: Randomized controlled trials are considered the gold standard for evaluating treatment effects, as randomization balances confounders and enables causal inference. However, randomized controlled trials are often costly, time-consuming, or ethically infeasible. As a result, RWD, such as electronic health records, medical registries, and health insurance claims, are increasingly used in medical research. Complex methods are necessary to derive causal inference from RWD. ELIGIBILITY CRITERIA: Studies that use RWD, evaluate any type of health outcome as a primary endpoint in order to investigate patient health status, address a causal question related to a treatment or intervention, and estimate a causal effect size related to the causal question will be eligible for inclusion. METHODS: PubMed, Embase.com, and Web of Science will be searched for articles published in peer-reviewed journals between January 1, 2010, and January 29, 2026. A scoping review will be conducted to identify and categorize causal inference methods applied to RWD, focusing on theoretical frameworks, data requirements, and inferential assumptions in order to develop a taxonomy of methods. The frequency, context of use, and quality of reporting will be systematically assessed. In parallel, a study within a review (SWAR) will evaluate the performance of LLMs for title and abstract screening and full-text data extraction compared with human reviewers. REVIEW REGISTRATION: OSF https://osf.io/69mcd; SWAR Store (ID 66) https://www.qub.ac.uk/sites/TheNorthernIrelandNetworkforTrialsMethodologyResearch/FileStore/SWARFileStore/SWAR66%20Stella%20Erdmann%20(2025%20AUG%2001%202302).pdf.