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An increasing desire for integration across verticals and patient-centric business processes means that metadata automation and collaboration matters more than ever.
The historical definition of metadata is “data about data”, or “metadata is structured information that describes, explains, locates, or otherwise makes it easier to retrieve, use, or manage an information resource”.
In the past, Study conduct was carried out by multiple business functions operating in a siloed manner, such as Data Capture, Clinical Data Management, Analytics & Reporting, Biostatistics, Clinical Operations etc with a more limited, siloed view of metadata.
Now, however, the Healthcare & Life Sciences industries are blurring boundaries and are at a stage of exploiting the potential of a variety and volume of data not only from within each individual industry but also horizontally across both. Each has multiple data sources they can derive benefit from combining individually within the industry and even across both. As the focus is moving towards “Patient-centricity”, straightforward and meaningful access to a broad variety and volume of data is a key aspect of both Healthcare and Life Sciences companies, individually or together, driving innovation at bench-side or at bed-side in the safest, most efficient and costeffective manner; as well as utilizing data-driven insight from bench-side to bed-side or from bedside to bench-side. This need is supported when the data representation is meaningful, and when data is made available on time; and that’s possible when that is supported by a robust foundation of metadata.
In addition, the industry is experiencing a wave of mergers, acquisitions, and consolidations, and all indications point to this trend continuing. As organizations consolidate, they bring with them their existing “legacy” data structures and formats, resulting in the need for integration of global Standards both within the Life Sciences industry itself, and also between the Life Sciences and HealthCare Industries. Such integration is increasingly begin driven by metadata concepts and context around key attributes such as “patient” and “customer”.
In this new paradigm, metadata, along with its storage and usage, has taken on a central role during the lifecycle, from Data Capture through Regulatory Submission. Metadata is stored in multiple formats and types across business functions. To increase reusability, consortiums have implemented standard and customized workflows and process flows for metadata. Many 3rd party consortiums such as CDISC, MedDRA, Who Drug etc., have developed, published, and disseminated multiple versions of key study metadata and standard dictionary terminology that have become not only an integral part of study conduct, but also serve as a direct driver for the realization of cost, time, and resource savings.