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Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements.
Weissman, Alexandra; Cheng, Alex; Mainor, Alex; Gimbel, Elizabeth; Nowak, Kayla; Pan, Huaqin Helen; Stratford, Jeran; Merkel, Alyssa; Taylor, Caroline; Meier, Heather; Auman, Jeanette; Nolen, Tracy L; Lindsell, Christopher J; Huang, David T.
Afiliação
  • Weissman A; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
  • Cheng A; Vanderbilt University Medical Center. Nashville, TN, USA.
  • Mainor A; Vanderbilt University Medical Center. Nashville, TN, USA.
  • Gimbel E; Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
  • Nowak K; RTI International, Research Triangle Park, NC, USA.
  • Pan HH; RTI International, Research Triangle Park, NC, USA.
  • Stratford J; RTI International, Research Triangle Park, NC, USA.
  • Merkel A; Vanderbilt University Medical Center. Nashville, TN, USA.
  • Taylor C; Vanderbilt University Medical Center. Nashville, TN, USA.
  • Meier H; RTI International, Research Triangle Park, NC, USA.
  • Auman J; RTI International, Research Triangle Park, NC, USA.
  • Nolen TL; RTI International, Research Triangle Park, NC, USA.
  • Lindsell CJ; Vanderbilt University Medical Center. Nashville, TN, USA.
  • Huang DT; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
J Clin Transl Sci ; 6(1): e142, 2022.
Article em En | MEDLINE | ID: mdl-36590348
ABSTRACT

Background:

Coronavirus Disease 2019 (COVID-19) instigated a flurry of clinical research activity. The unprecedented pace with which trials were launched left an early void in data standardization, limiting the potential for subsequent data pooling. To facilitate data standardization across emerging studies, the National Heart, Lung, and Blood Institute (NHLBI) charged two groups with harmonizing data collection, and these groups collaborated to create a concise set of COVID-19 Common Data Elements (CDEs) for clinical research.

Methods:

Our iterative approach followed three guiding principles 1) draw from existing multi-center COVID-19 clinical trials as precedents, 2) incorporate existing data elements and data standards whenever possible, and 3) alignment to data standards that facilitate data sharing and regulatory submission. We also supported rapid implementation of the CDEs in NHLBI-funded studies and iteratively refined the CDEs based on feedback from those study teams.

Results:

The NHLBI COVID-19 CDEs are publicly available and being used for current COVID-19 clinical trials. CDEs are organized into domains, and each data element is classified within a three-tiered prioritization system. The CDE manual is hosted publicly at https//nhlbi-connects.org/common_data_elements with an accompanying data dictionary and implementation guidance.

Conclusions:

The NHLBI COVID-19 CDEs are designed to aid data harmonization across studies to achieve the benefits of pooled analyses. We found that organizing CDE development around our three guiding principles focused our efforts and allowed us to adapt as COVID-19 knowledge advanced. As these CDEs continue to evolve, they could be generalized for use in other acute respiratory illnesses.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Guideline Idioma: En Revista: J Clin Transl Sci Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Clinical_trials / Guideline Idioma: En Revista: J Clin Transl Sci Ano de publicação: 2022 Tipo de documento: Article