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[GRADE: Using evidence to decision frameworks for adoption, adaptation and de novo generation of trustworthy guideline recommendations - GRADE-ADOLOPMENT]. | LitMetric

[GRADE: Using evidence to decision frameworks for adoption, adaptation and de novo generation of trustworthy guideline recommendations - GRADE-ADOLOPMENT].

Z Evid Fortbild Qual Gesundhwes

Institut für Evidenz in der Medizin (für Cochrane Deutschland Stiftung), Universitätsklinikum Freiburg - Medizinische Fakultät, Albert-Ludwigs-Universität Freiburg, Freiburg, Deutschland; Cochrane Deutschland, Cochrane Deutschland Stiftung, Freiburg, Deutschland.

Published: August 2019

Background: Guideline developers can: (1) adopt existing recommendations from others; (2) adapt existing recommendations to their own context; or (3) create recommendations de novo. Monetary and nonmonetary resources, credibility, maximization of uptake, as well as logical arguments should guide the choice of the approach and processes.

Objectives: To describe a potentially efficient model for guideline production based on adoption, adaptation, and/or de novo development of recommendations utilizing the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence to Decision (EtD) frameworks.

Study Design And Setting: We applied the model in a new national guideline program producing 22 practice guidelines. We searched for relevant evidence that informs the direction and strength of a recommendation. We then produced GRADE EtDs for guideline panels to develop recommendations.

Results: In two waves, a total of 80 EtD frameworks was produced approximately 4 months and 146 EtDs in about 6 months. Use of the EtD frameworks allowed panel members to understand judgments of other guideline groups about the criteria that bear on guideline recommendations and then make their own judgments about those criteria in a systematic approach.

Conclusion: The "GRADE-ADOLOPMENT" approach to guideline production combines adoption, adaptation, and, as needed, de novo development of recommendations. If guideline developers apply EtD criteria more widely and make their work publically available, this approach should prove even more useful.

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Source
http://dx.doi.org/10.1016/j.zefq.2019.06.001DOI Listing

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