Background: Many decision aids convey the relevant facts and evidence but do not convey recommendations from guidelines. It is unclear if conveying recommendations from a global view across guidelines would be similar or dissimilar than what would be conveyed by a single guideline. Conveying a global view for rapid simple patient understanding could quickly become unwieldy.
Objectives: We developed a simple model to report the consistency or inconsistency across guidelines for specific recommendations.
Methods: The Healthcare Guidance for Patients Society (Healthcare GPS) is a group of experts covering the spectrum of developing, rating, and using guidance and shared decision making. We considered the National Academy of Medicine (NAM), Guidelines International Network (G-I-N), and Grading of Recommendations Assessment, Development and Evaluation (GRADE) standards and developed (via a consensus-based approach) a classification system for a recommendation that is represented across multiple entities making recommendations for the same concept.
Results: First the consistency across the guidelines is determined regarding whether all guidelines are for (or against) the particular recommendation. For recommendations that are consistent in direction across guidelines, consistency is checked regarding the certainty that desirable consequences outweigh undesirable consequences. Further checking for consistently strong recommendations involves confirmation of a qualified rationale requiring three elements: a systematic review, multidisciplinary input with conflict of interest management, and explicit reporting of values and preferences to inform judgments about the balance between benefits and harms of treatment alternatives.
Conclusions: Healthcare GPS ratings can provide a simple recognisable method to communicate the comprehensive view to the certainty of a recommendation across guidelines. Such communication can be tested in patient decision aids and shared decision-making tools to determine if it facilitates patient understanding. This approach can also be tested in areas of clinical decision making and policy decision making.