Title
Building better guidelines with BRIDGE-Wiz: development and evaluation of a software assistant to promote clarity, transparency, and implementability.
Abstract
Objective To demonstrate the feasibility of capturing the knowledge required to create guideline recommendations in a systematic, structured, manner using a software assistant. Practice guidelines constitute an important modality that can reduce the delivery of inappropriate care and support the introduction of new knowledge into clinical practice. However, many guideline recommendations are vague and underspecified, lack any linkage to supporting evidence or documentation of how they were developed, and prove to be difficult to transform into systems that influence the behavior of care providers. Methods The BRIDGE-Wiz application (Building Recommendations In a Developer's Guideline Editor) uses a wizard approach to address the questions: (1) under what circumstances? (2) who? (3) ought (with what level of obligation?) (4) to do what? (5) to whom? (6) how and why? Controlled natural language was applied to create and populate a template for recommendation statements. Results The application was used by five national panels to develop guidelines. In general, panelists agreed that the software helped to formalize a process for authoring guideline recommendations and deemed the application usable and useful. Discussion Use of BRIDGE-Wiz promotes clarity of recommendations by limiting verb choices, building active voice recommendations, incorporating decidability and executability checks, and limiting Boolean connectors. It enhances transparency by incorporating systematic appraisal of evidence quality, benefits, and harms. BRIDGE-Wiz promotes implementability by providing a pseudocode rule, suggesting deontic modals, and limiting the use of 'consider'. Conclusion Users found that BRIDGE-Wiz facilitates the development of clear, transparent, and implementable guideline recommendations.
Year
DOI
Venue
2012
10.1136/amiajnl-2011-000172
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Field
DocType
Volume
Transparency (graphic),Data mining,CLARITY,Deontic logic,Controlled natural language,Computer science,Knowledge management,Pseudocode,Guideline,Documentation,Wizard
Journal
19
Issue
ISSN
Citations 
1
1067-5027
7
PageRank 
References 
Authors
0.56
11
4
Name
Order
Citations
PageRank
Richard N. Shiffman112426.09
George Michel2546.80
Richard M. Rosenfeld370.56
Caryn Davidson470.56