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Lessons on the use of real-world data in medical device research: findings from the National Evaluation System for Health Technology Test-Cases

Authors :
Justin W Timbie
Alice Y Kim
Lawrence Baker
Rosemary Li
Thomas W Concannon
Source :
Journal of Comparative Effectiveness Research, Vol 13, Iss 9 (2024)
Publication Year :
2024
Publisher :
Becaris Publishing Limited, 2024.

Abstract

Aim: Although the US FDA encourages manufacturers of medical devices to submit real-world evidence (RWE) to support regulatory decisions, the ability of real-world data (RWD) to generate evidence suitable for decision making remains unclear. The 2017 Medical Device User Fee Amendments (MDUFA IV), authorized the National Evaluation System for health Technology Coordinating Center (NESTcc) to conduct pilot projects, or ‘Test-Cases’, to assess whether current RWD captures the information needed to answer research questions proposed by industry stakeholders. We synthesized key lessons about the challenges conducting research with RWD and the strategies used by research teams to enhance their ability to generate evidence from RWD based on 18 Test-Cases conducted between 2020 and 2022. Materials & methods: We reviewed study protocols and reports from each Test-Case team and conducted 49 semi-structured interviews with representatives of participating organizations. Interview transcripts were coded and thematically analyzed. Results: Challenges that stakeholders encountered in workingwith RWD included the lack of unique device identifiers, capturing key data elements and their appropriate meaning in structured data, limited reliability of diagnosis and procedure codes in structured data, extracting information from unstructured electronic health record (EHR) data, limited capture of long-term study end points, missing data and data sharing. Successful strategies included using manufacturer and supply chain data, leveraging clinical registries and registry reporting processes to collect and aggregate data, querying standardized EHR data, implementing natural language processing algorithms and using multidisciplinary research teams. Conclusion: The Test-Cases identified numerous challenges working with RWD but also opportunities to address these challenges and improve researchers’ ability to use RWD to generate evidence on medical devices.

Details

Language :
English
ISSN :
20426313
Volume :
13
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Journal of Comparative Effectiveness Research
Publication Type :
Academic Journal
Accession number :
edsdoj.8802af65108c41fa878c7711c3193b07
Document Type :
article
Full Text :
https://doi.org/10.57264/cer-2024-0078