Standardized Interoperable Data Collection for Myositis Research: Developing Expert Consensus on Common Data Elements for Myositis Outcome Measures.
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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Saygin Didem, Diller Matthew, Surampudi Varsha, Bodkin Mark, Farhadi Payam Noroozi, Mecoli Christopher A, Kessel Audrey, Aggarwal Rohit, Alexanderson Helene, Amato Anthony, Bartels Christie M, Benveniste Olivier, Best Michelle, Chinoy Hector, de Groot Ingrid, Feldman Brian, Huber Adam M, Kim Hanna, Kim Susan, Kobert Linda, Leclair Valerie, Lubinus Manuel, Machado Pedro M, Mammen Andrew, McCann Liza J, Mozaffar Tahseen, Oddis Chester, Paik Julie J, Ravelli Angelo, Ruperto Nicolino, Schmidt Jens, Werner Ellen, Werth Victoria, Schiffenbauer Adam, Scheuermann Richard H, Rider Lisa G, IMACS Myositis CDE Working Group
Аннотация
METHODS: Data dictionaries of myositis registries were examined to understand how outcome measures are currently captured. We used the Linked data Modeling Language, an open-source data modeling framework, to develop computable CDEs. After drafting CDEs for myositis core set measures (CSMs), an international conference was held with an expert myositis panel to reach consensus on the coding of CDEs and prioritize additional measures for CDE creation, using Delphi and modified nominal group techniques. This workflow was repeated for the prioritized measures in the second phase.
RESULTS: A workflow was established for CDE creation. CDEs for 10 myositis CSMs were drafted. After receiving comments to improve their coding, universal agreement among participants was reached for CSM CDEs. The prioritized measures for future CDEs included myositis response and classification criteria, damage measures, physical function measures, and Patient-Reported Outcomes Measurement Information System instruments. CDEs for 18 additional measures were discussed at a second consensus conference. Similarly, high agreement rates were achieved, except for flare criteria. Altogether, 852 new CDEs were created for 27 myositis forms and achieved consensus, readying their deposit in the NIH CDE Repository.
CONCLUSION: Leveraging multispecialty expertise in myositis and its patient communities and data science expertise of the National Library of Medicine, the first myositis-specific CDEs have been developed to accelerate the ability to conduct interoperable myositis clinical studies and therapeutic trials. The workflow established here should also benefit creation of CDEs and data sharing for other autoimmune diseases.