Conclusions: We have successfully migrated the SEVCO/ HEvKA terminology development process to another domain and achieved a remarkable level of consensus. Feasibility and stability of the process have been demonstrated. That success will lead to coherence across GRADE reports and their computability allowing results of the GRADE process to be widely disseminated.
This project is open to everyone, please join the project group using the following link: https://fevir.net/resources/Project/111563.
Reference: Alper BS et al, COVID-19 Knowledge Accelerator (COKA) Initiative. Making science computable: Developing code systems for statistics, study design, and risk of bias. J Biomed Inform. 2021 Mar;115:103685.
Results: | |
# of Terms Approved | 14 Terms |
# of Contributors | 23 Term Editors 35 Voters 42 Meeting Participants 78 Unique Participants |
# of Countries | 24 |
#Total Votes | 748 |
#Ave. Votes/Term | 53 |
#Ave. Ballots/Term | 4.6 (Range 1-11) |
Grading of Recommendations, Assessment, Development,
and Evaluation (GRADE) Ontology Project
J Dehnbostel1,2, P Whaley3, B Alper1,2, S Sayfi4, S Li5, J Bracchiglione6,
H Lehmann1,7, H Keshavarz4, S Mokrane8, T Dalsbø9, K Shahin1,2, K Wilkins10
Background: GRADE is a de facto methodological framework and terminology standard for certainty-of-evidence and evidence-to-decision judgements. Computer applications such as GRADEpro and MAGICapp require crisp and well-defined terms. Formalizing the terminology of GRADE into a harmonized ontology will provide a technical infrastructure that will enhance the efficiency of creating and reusing GRADE data.
Objective: Develop and maintain a standardized, computable vocabulary of terms, an ontology, necessary for the expression of GRADE certainty-of-evidence and evidence-to-decision judgements.
Methods: Using a 13 step HEvKA/SEVCO term definition protocol (Alper et al), an international group of GRADE experts meet virtually each week in open meetings to curate terms from published GRADE guidances, establish preferred and alternative terms for included concepts, define the concepts, and write guidance for application. Voting is supported on the FEvIR Platform at https://fevir.net
Any dissenting comments or votes are discussed until agreement is reached. A globally agreed approach across a diverse community is required to create a comprehensive consensus.
1 Scientific Knowledge Accelerator Foundation, USA 2 Computable Publishing LLC, USA
3 Evidence Based Toxicology Collaboration,
Institute For Evidence Based Toxicology, UK
4 McMaster University , Canada
5 Sichuan University, China
6 Iberoamerican Cochrane Center IR Sant Pau, Spain/CIESAL, Universidad de Valparaiso, Chile
7 Johns Hopkins University, USA
8 Université Libre de Bruxelles, Belgium
9 STAMI, Norway
10 NIDDK, USA