Work

Making causal inferences from transactional data: A narrative review of opportunities and challenges when implementing the target trial framework

Year: 2024

Type: review

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.

Source: Journal of International Medical Research

DOI: 10.1177/03000605241241920

Authors: Santiago Esteban, Alejandro Szmulewicz

Institutions: Hospital Italiano de Buenos Aires, Instituto de Efectividad Clínica y Sanitaria, Harvard University

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $4,155