Describing diversity of real world data sources in pharmacoepidemiologic studies: The DIVERSE scoping review

Author:

Gini Rosa1ORCID,Pajouheshnia Romin23ORCID,Gardarsdottir Helga245ORCID,Bennett Dimitri6ORCID,Li Lin7ORCID,Gulea Claudia8ORCID,Wientzek‐Fleischmann Angelika9ORCID,Bazelier Marloes T.2ORCID,Burcu Mehmet10ORCID,Dodd Caitlin11ORCID,Durán Carlos E.4ORCID,Kaplan Sigal12ORCID,Lanes Stephan13ORCID,Marinier Karine14ORCID,Roberto Giuseppe1ORCID,Soman Kanaka2ORCID,Zhou Xiaofeng15ORCID,Platt Robert16ORCID,Setoguchi Soko17ORCID,Hall Gillian C.18ORCID

Affiliation:

1. ARS Toscana Florence Italy

2. Division of Pharmacoepidemiology & Clinical Pharmacology Utrecht University Utrecht The Netherlands

3. Department of Epidemiology RTI Health Solutions Barcelona Spain

4. Department of Data Science & Biostatistics University Medical Center Utrecht Utrecht The Netherlands

5. University of Iceland Reykjavik Iceland

6. Takeda Development Center Americas Cambridge Massachusetts USA

7. Epidemiology and Benefit Risk, Sanofi Bridgewater New Jersey USA

8. Center for Observational and Real‐World Evidence, MSD Zürich Switzerland

9. Daiichi‐Sankyo Europe Germany

10. Department of Epidemiology, Merck & Co., Inc. Rahway New Jersey USA

11. Panalgo USA

12. Teva Pharmaceutical Industries Ltd. Israel

13. Carelon Research Wilmington Delaware USA

14. IQVIA, Courbevoie France

15. Global Medical Epidemiology, Pfizer Inc. New York USA

16. McGill University Montreal Canada

17. Rutgers University New Jersey USA

18. Gillian Hall Epidemiology UK

Abstract

AbstractPurposeReal‐world evidence (RWE) is increasingly used for medical regulatory decisions, yet concerns persist regarding its reproducibility and hence validity. This study addresses reproducibility challenges associated with diversity across real‐world data sources (RWDS) repurposed for secondary use in pharmacoepidemiologic studies. Our aims were to identify, describe and characterize practices, recommendations and tools for collecting and reporting diversity across RWDSs, and explore how leveraging diversity could improve the quality of evidence.MethodsIn a preliminary phase, keywords for a literature search and selection tool were designed using a set of documents considered to be key by the coauthors. Next, a systematic search was conducted up to December 2021. The resulting documents were screened based on titles and abstracts, then based on full texts using the selection tool. Selected documents were reviewed to extract information on topics related to collecting and reporting RWDS diversity. A content analysis of the topics identified explicit and latent themes.ResultsAcross the 91 selected documents, 12 topics were identified: 9 dimensions used to describe RWDS (organization accessing the data source, data originator, prompt, inclusion of population, content, data dictionary, time span, healthcare system and culture, and data quality), tools to summarize such dimensions, challenges, and opportunities arising from diversity. Thirty‐six themes were identified within the dimensions. Opportunities arising from data diversity included multiple imputation and standardization.ConclusionsThe dimensions identified across a large number of publications lay the foundation for formal guidance on reporting diversity of data sources to facilitate interpretation and enhance replicability and validity of RWE.

Funder

International Society for Pharmacoepidemiology

Publisher

Wiley

Reference61 articles.

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