Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis

Area of Science:

• Medical Decision-Making
• Health Informatics
• Clinical Guidelines Development

Background:

• The objective consensus methodology is increasingly used for consensus finding among clinical experts and in guideline development.
• Key advantages include automated, anonymous analysis and comparison of treatment algorithms across participating centers.

Purpose of the Study:

• To identify and discuss the main steps required for the successful implementation of the objective consensus methodology.
• To provide detailed information on collecting and converting decision trees for consensus analysis.

Main Methods:

• Leveraged experience from completed consensus analyses to define implementation steps.
• Investigator discussions were central to identifying and refining the methodology's core components.

Main Results:

• Detailed steps for successful decision tree collection and conversion were identified: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis.
• These steps provide a structured framework for applying the objective consensus methodology.

Conclusions:

• This manuscript delineates crucial steps for effectively collecting decision trees within the objective consensus methodology.
• It summarizes critical aspects at each stage of the analysis, enhancing the methodology's practical application.