A framework for synthesizing intervention evidence from multiple sources into a single certainty of evidence rating: Methodological developments from a US National Academies of S ciences, E ngineering, and M edicine C ommittee
Year: 2022
Type: review
Abstract: Despite research investment and a growing body of diverse evidence there has been no comprehensive review and grading of evidence for public health emergency preparedness and response practices comparable to those in medicine and other public health fields. The National Academies of Sciences, Engineering, and Medicine convened an ad hoc committee to develop and use methods for grading and synthesizing diverse types of evidence to create a single certainty of intervention-related evidence to support recommendations for Public Health Emergency Preparedness and Response Research. A 13-step consensus building method was used. Experts were first canvassed in public meetings, and a comprehensive review of existing methods was undertaken. Although aspects of existing review methodologies and evidence grading systems were relevant, none adequately covered all requirements for this specific context. Starting with a desire to synthesize diverse sources of evidence not usually included in systematic reviews and using GRADE for assessing certainty and confidence in quantitative and qualitative evidence as the foundation, we developed a mixed-methods synthesis review and grading methodology that drew on (and in some cases adapted) those elements of existing frameworks and methods that were most applicable. Four topics were selected as test cases. The process was operationalized with a suite of method-specific reviews of diverse evidence types for each topic. Further consensus building was undertaken through stakeholder engagement and feedback The NASEM committee's GRADE adaption for mixed-methods reviews will further evolve over time and has yet to be endorsed by the GRADE working group.
Source: Research Synthesis Methods
DOI: 10.1002/jrsm.1582
Authors: Ned Calonge, Paul G. Shekelle, Douglas K. Owens, Steven Teutsch, Autumn Downey, Lisa Brown, Jane Noyes
Institutions: Colorado School of Public Health, University of Colorado Anschutz, University of Colorado Denver, University of California, Los Angeles, VA Greater Los Angeles Healthcare System, Stanford University, University of Southern California, National Academies of Sciences, Engineering, and Medicine, Bangor University
Language: English
Subfield: Statistics, Probability and Uncertainty
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid: $3,300
OpenAlex ID: W4283158970
