AI Article Synopsis

  • The digitization of healthcare has led to a significant increase in the availability and use of real-world data (RWD), driven by the demand for high-quality evidence in the biopharmaceutical sector since the 2016 21st Century Cures Act.
  • RWD applications are expanding beyond drug development to include population health and direct clinical uses, necessitating the transformation of diverse data sources into reliable datasets to maximize their potential.
  • To improve RWD life cycles, the text outlines seven key best practices, including adherence to data standards and promoting equity in representation, aimed at enhancing data quality and usability for analysis.

Article Abstract

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.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931348PMC
http://dx.doi.org/10.1371/journal.pdig.0000003DOI Listing

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