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Reflection paper on use of real-world data in noninterventional studies to generate real-world evidence
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Table of contents
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1.
- References ............................................................................................ 15
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Reflection paper on use of real-world data in non-interventional studies to generate
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1.
- Introduction
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This reflection paper discusses methodological aspects of non-interventional studies (NIS) using real-
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world data (RWD) in order to generate real-world evidence (RWE) for regulatory purposes.
- These include absence of randomisation, uncontrolled conditions, non-
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standardised treatments and uncertainties regarding data quality and completeness.
- The
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increasing ability to capture electronic healthcare data and data from registries is now providing new
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opportunities to use RWD and generate RWE that reflects clinical practice.
- Scope
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The scope of this reflection paper is the design, conduct and analysis of NIS using RWD to generate
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RWE for regulatory purposes.
- data collected specifically for the study in
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question, or secondary use of existing data sources.
- In both cases, attention should be paid to the
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possible selection mechanisms in the data collection, for example the inclusion of specific patients or
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the collection of specific clinical data.
- Reference to studies with causal objectives in this document does not
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imply an expectation that specific analytical methods will be used.
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The legal obligations and regulatory requirements applicable to NIS should be followed.
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Regulation (EU) 2016/679 on the protection of natural persons with regard to the processing of
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personal data and on the free movement of such data.
- The specific aim of the study forms the basis for the
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selection of data source(s), study design, and analysis approach.
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4.2.
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Regional differences in clinical practice and healthcare systems management, e.g.
- Misclassification can arise at many different
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steps of data collection and extraction: diagnosis, coding, recording, data transformation, data
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aggregation, summarisation, and analysis.
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6.4.
- For these studies, the study protocol should describe:
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The data elements used to link the data.
- Heterogeneity
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In multi-database studies, different estimates may be found even when the same protocol is applied
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across all data sources (22).
- (2023)
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15.
- Draft guidance Real-World Data: Assessing Electronic Health Records and Medical Claims
Data To Support Regulatory Decision-Making for Drug and Biological Products (2021)
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