GRADE Evidence to Decision (EtD) frameworks for adoption, adaptation, and de novo development of trustworthy recommendations: GRADE-ADOLOPMENT

Holger J Schünemann; Wojtek Wiercioch; Jan Brozek; Itziar Etxeandia-Ikobaltzeta; Reem A Mustafa; Veena Manja; Romina Brignardello-Petersen; Ignacio Neumann; Maicon Falavigna; Waleed Alhazzani; Nancy Santesso; Yuan Zhang; Jörg J Meerpohl; Rebecca L Morgan; Bram Rochwerg; Andrea Darzi; Maria Ximenas Rojas; Alonso Carrasco-Labra; Yaser Adi; Zulfa AlRayees; John Riva; Claudia Bollig; Ainsley Moore; Juan José Yepes-Nuñez; Carlos Cuello; Reem Waziry; Elie A Akl

doi:10.1016/j.jclinepi.2016.09.009

GRADE Evidence to Decision (EtD) frameworks for adoption, adaptation, and de novo development of trustworthy recommendations: GRADE-ADOLOPMENT

J Clin Epidemiol. 2017 Jan:81:101-110. doi: 10.1016/j.jclinepi.2016.09.009. Epub 2016 Oct 3.

Authors

Holger J Schünemann¹, Wojtek Wiercioch², Jan Brozek³, Itziar Etxeandia-Ikobaltzeta², Reem A Mustafa⁴, Veena Manja⁵, Romina Brignardello-Petersen⁶, Ignacio Neumann⁷, Maicon Falavigna⁸, Waleed Alhazzani³, Nancy Santesso², Yuan Zhang², Jörg J Meerpohl⁹, Rebecca L Morgan², Bram Rochwerg², Andrea Darzi¹⁰, Maria Ximenas Rojas¹¹, Alonso Carrasco-Labra⁷, Yaser Adi¹², Zulfa AlRayees¹³, John Riva¹⁴, Claudia Bollig¹⁵, Ainsley Moore¹⁴, Juan José Yepes-Nuñez², Carlos Cuello¹⁶, Reem Waziry¹⁷, Elie A Akl¹⁸

Affiliations

¹ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada. Electronic address: [email protected].
² Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada.
³ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Medicine, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada.
⁴ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Internal Medicine/Nephrology, University of Missouri-Kansas City, 2301 Holmes Street, Kansas City, MO 64108, USA; Department of Biomedical and Health Informatics, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA.
⁵ Division of Cardiology, Department of Medicine, Veterans Affairs Medical Center, 3495 Bailey Avenue, Buffalo, NY 14215, USA; Department of Internal Medicine, University at Buffalo, The State University of New York, 3435 Main street, Buffalo, NY 14214, USA.
⁶ Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College St, Toronto, ON M5T 3M6, Canada; Evidence-Based Dentistry Unit, Faculty of Dentistry, Universidad de Chile, Sergio Livingstone Pohlhammer 943, Independencia, Santiago 8380492, Chile.
⁷ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Internal Medicine, Pontificia Universidad Católica de Chile, Alameda 340, Santiago 8331150, Chile.
⁸ Hospital Moinhos de Vento, Rua Ramiro Barcelos 910, Bairro Moinhos de Vento, Porto Alegre, Brazil; National Institute of Science and Technology for Health Technology Assessment, Federal University of Rio Grande do Sul, Rua Ramiro Barcelos, No. 2359, 90035-903 Porto Alegre, RS, Brazil.
⁹ Cochrane Germany, Medical Center-University of Freiburg, Breisacher Strasse 153, Freiburg 79110, Germany; Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité-U1153, Inserm/Université Paris Descartes, Cochrane France, Hôpital Hôtel-Dieu, 1 place du Parvis Notre Dame, 75181 Paris Cedex 04, France.
¹⁰ Department of Biomedical and Health Informatics, University of Missouri-Kansas City, 2411 Holmes Street, Kansas City, MO 64108, USA.
¹¹ Department of Clinical Epidemiology and Biostatistics, Pontificia Universidad Javeriana, Hospital Universitario de San Ignacio, Cr. 7 40-62 2nd Floor, Bogotá, Colombia.
¹² King Faisal Specialist Hospital and Research Centre, Zahrawi Street, Al Maather, P.O. Box 3354 Riyadh 11211, Saudi Arabia.
¹³ Saudi Centre for Evidence Based Health Care, Ministry of Health, King Abdulaziz Road, Riyadh 11176, Saudi Arabia.
¹⁴ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Family Medicine, McMaster University, David Braley Health Sciences Centre, 100 Main Street West, 6th Floor, Hamilton, Ontario L8P 1H6, Canada.
¹⁵ Cochrane Germany, Medical Center-University of Freiburg, Breisacher Strasse 153, Freiburg 79110, Germany.
¹⁶ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Tecnologico de Monterrey School of Medicine, Avda. Morones Prieto 3000 pte. CP 64710 Monterrey, Nuevo León, Mexico.
¹⁷ Department of Internal Medicine, Faculty of Health Sciences, American University of Beirut, P.O. Box: 11-0236, Riad-El-Solh Beirut 1107 2020, Beirut, Lebanon; The Kirby Institute, University of New South Wales, Wallace Wurth Building, University of New South Wales, Sydney, New South Wales 2052, Australia.
¹⁸ Department of Clinical Epidemiology and Biostatistics, McMaster University, 1280 Main Street West, Hamilton, Ontario L8N 4K1, Canada; Department of Internal Medicine, Faculty of Health Sciences, American University of Beirut, P.O. Box: 11-0236, Riad-El-Solh Beirut 1107 2020, Beirut, Lebanon.

PMID: 27713072
DOI: 10.1016/j.jclinepi.2016.09.009

Abstract

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: We produced a total of 80 EtD frameworks in approximately 4 months and 146 EtDs in approximately 6 months in two waves. Use of the EtD frameworks allowed panel members understand judgments of others 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 developers of guidelines follow EtD criteria more widely and make their work publically available, this approach should prove even more useful.

Keywords: Adaptation; Clinical practice guidelines; Evidence to Decision framework; Evidence-based medicine; GRADE; Recommendation.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adaptation, Physiological
Decision Support Techniques*
Evidence-Based Medicine / methods*
Evidence-Based Medicine / standards*
Humans
Judgment*
Practice Guidelines as Topic / standards*