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Are Randomized Controlled Trials the (G)old Standard? From Clinical Intelligence to Prescriptive Analytics.
Sven Van Poucke1, Michiel Thomeer, John Heath
1Department of Anesthesiology, Critical Care, Emergency Medicine, Pain Therapy, Ziekenhuis Oost-Limburg, Genk, Belgium. svanpoucke@gmail.com.
Clinical research faces challenges in answering urgent questions. While randomized controlled trials remain vital, big data and advanced analytics offer new avenues for medical discovery and validation.
Area of Science:
- Medical Research
- Clinical Epidemiology
- Health Informatics
Background:
- Current clinical research struggles to address critical health questions efficiently.
- Decision-making often relies on observational data due to limitations in clinical trials.
Purpose of the Study:
- To explore the philosophical underpinnings of medical research (Popper's falsificationism).
- To evaluate the limitations of randomized controlled trials (RCTs).
- To highlight the potential and challenges of big data in observational studies for clinical research.
Main Methods:
- Review of scientific epistemology and research methodologies.
- Analysis of randomized controlled trials (RCTs) and their constraints.
- Exploration of big data analytics and machine learning in observational studies.
Main Results:
- Randomized controlled trials (RCTs) face inherent limitations in addressing all clinical questions.
- Observational studies, powered by big data, present significant potential for clinical insights.
- Obstacles exist in utilizing retrospective observational data effectively.
Conclusions:
- Randomized controlled trials (RCTs) will continue to be essential in clinical research.
- Innovations in statistics, machine learning, and big data analytics are creating a new paradigm for clinical evidence generation and validation.

