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Updated: Jun 29, 2025

RBDT: A Computerized Task System based in Transposition for the Continuous Analysis of Relational Behavior Dynamics in Humans
Published on: July 17, 2021
Making causal inferences from transactional data: A narrative review of opportunities and challenges when
Santiago Esteban1,2, Alejandro Szmulewicz3
1Instituto de Efectividad Clínica y Sanitaria, Centro de Implementación e Innovación en Políticas de Salud, Buenos Aires, Argentina.
Abstract:
The target trial framework has emerged as a powerful tool for addressing causal questions in clinical practice and in public health. In the healthcare sector, where decision-making is increasingly data-driven, transactional databases, such as electronic health records (EHR) and insurance claims, present an untapped potential for answering complex causal questions. This narrative review explores the potential of the integration of the target trial framework with real-world data to enhance healthcare decision-making processes. We outline essential elements of the target trial framework, and identify pertinent challenges in data quality, privacy concerns, and methodological limitations, proposing solutions to overcome these obstacles and optimize the framework's application.
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