RedETS methodological approach for real-world data in the preadoption phase
This method outlines how the Spanish Health Technology Assessment Network (RedETS) uses real-world data (RWD) during the early evaluation of health technologies, before they are adopted. It helps tailor assessments to the Spanish population by integrating RWD into standard evaluation processes, such as systematic reviews and decision modeling, using practical steps and a real-world example.
At a glance
Use when
Conducting preadoption HTAs where local context is important and real-world data can supplement clinical evidence
Avoid when
When RWD is inaccessible, of poor quality, or when assessment teams lack capacity to handle complex data
Inputs
Real-world data (e.g., electronic health records, registries), data model specifications, research questions, technology characteristics
Outputs
Context-adjusted HTA reports, decision models, exploratory data analyses, recommendations for data collection and collaboration
How it works
The RedETS methodological approach defines a structured workflow for integrating real-world data (RWD) into preadoption health technology assessments. It includes specifying data requirements via a data model, conducting exploratory data analysis, and building decision models. The framework was developed through a working group and informed by national and international RWD initiatives. A use case on implantable cardiac defibrillators (ICDs) for sudden cardiac death prevention was implemented using data from the Aragon Big Data (BIGAN) project. The method addresses challenges such as missing data, unstructured records, and data access, and emphasizes the need for data scientists in HTA teams and capacity building in RWD analytics and modeling.
- HTA domains
- Clinical Effectiveness, Costs & Economic Evaluation, Organisational aspects
- Assumptions
- Real-world data can be accessed and is sufficiently reliable; data holders are willing to collaborate; data scientists are available to support analysis
- Strengths
- Enhances relevance of HTA to local population; supports dynamic, lifecycle-based assessments; integrates with existing RedETS workflows; provides practical guidance through a use case
- Limitations
- Data access remains a major barrier; quality and structure of RWD may vary; requires specialized skills in data science and modeling; not all variables may be available
- Also known as
- RedETS RWD framework, RedETS preadoption RWD method
Questions this answers
- › How can real-world data be integrated into preadoption HTA processes?
- › What are the key steps in using RWD for HTA within RedETS?
- › How can missing or unstructured data be handled in RWD-based assessments?
- › What role does exploratory data analysis play in RWD-informed HTA?
- › How can decision models be constructed using real-world data?
- › What are the main barriers to using RWD in HTA and how can they be addressed?
References & sources
Similar by meaning
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