Best practices in the real-world data life cycle.
Journal
PLOS digital health
ISSN: 2767-3170
Titre abrégé: PLOS Digit Health
Pays: United States
ID NLM: 9918335064206676
Informations de publication
Date de publication:
Jan 2022
Jan 2022
Historique:
entrez:
22
2
2023
pubmed:
23
2
2023
medline:
23
2
2023
Statut:
epublish
Résumé
With increasing digitization of healthcare, real-world data (RWD) are available in greater quantity and scope than ever before. Since the 2016 United States 21st Century Cures Act, innovations in the RWD life cycle have taken tremendous strides forward, largely driven by demand for regulatory-grade real-world evidence from the biopharmaceutical sector. However, use cases for RWD continue to grow in number, moving beyond drug development, to population health and direct clinical applications pertinent to payors, providers, and health systems. Effective RWD utilization requires disparate data sources to be turned into high-quality datasets. To harness the potential of RWD for emerging use cases, providers and organizations must accelerate life cycle improvements that support this process. We build on examples obtained from the academic literature and author experience of data curation practices across a diverse range of sectors to describe a standardized RWD life cycle containing key steps in production of useful data for analysis and insights. We delineate best practices that will add value to current data pipelines. Seven themes are highlighted that ensure sustainability and scalability for RWD life cycles: data standards adherence, tailored quality assurance, data entry incentivization, deploying natural language processing, data platform solutions, RWD governance, and ensuring equity and representation in data.
Identifiants
pubmed: 36812509
doi: 10.1371/journal.pdig.0000003
pii: PDIG-D-21-00033
pmc: PMC9931348
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
e0000003Subventions
Organisme : Medical Research Council
ID : MC_PC_19006
Pays : United Kingdom
Informations de copyright
Copyright: © 2022 Zhang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Déclaration de conflit d'intérêts
In accordance with the journal’s policy, the authors of this manuscript have the following competing interests to declare: CD has received an honorarium for work with Merck. JTT has previously received research grant support from Innovate UK, NHSX, Office of Life Sciences, Bristol-Meyers-Squibb and Pfizer; has received honorarium from Bayer, Bristol-Meyers-Squibb and Goldman Sachs; holds stock in Amazon, Alphabet, Nvidia, Glaxo Smith Kline; and receives royalties from Wiley-Blackwell Publishing. SB holds equity in Owkin. SB was formerly employed by Boston Consulting Group and Owkin. JZ receives funding from the Wellcome Trust (203928/Z/16/Z) and acknowledges support from the National Institute for Health Research (NIHR) Biomedical Research Centre based at Imperial College NHS Trust and Imperial College London. SB receives funding from the Wellcome Trust (566701). LAC receives funding from the National Institute of Health (NIBIB R01 EB017205). Listed bodies had no role in funding this study, and views expressed are authors’ own.
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