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

Cédric Panje, Markus Glatzer, Joscha Von Rappard, Christian Rothermundt, Thomas Hundsberger, Valentin Zumstein, Ludwig Plasswilm & Paul Martin Putora

abstract

BACKGROUND
The objective consensus methodology has recently been applied in consensus finding in several studies on medical decision-making among clinical experts or guidelines. The main advantages of this method are an automated analysis and comparison of treatment algorithms of the participating centers which can be performed anonymously.

METHODS
Based on the experience from completed consensus analyses, the main steps for the successful implementation of the objective consensus methodology were identified and discussed among the main investigators.

RESULTS
The following steps for the successful collection and conversion of decision trees were identified and defined in detail: problem definition, population selection, draft input collection, tree conversion, criteria adaptation, problem re-evaluation, results distribution and refinement, tree finalisation, and analysis.

CONCLUSION
This manuscript provides information on the main steps for successful collection of decision trees and summarizes important aspects at each point of the analysis.
   
citation Panje C, Glatzer M, von Rappard J, Rothermundt C, Hundsberger T, Zumstein V, Plasswilm L, Putora P M. Applied Swarm-based medicine: collecting decision trees for patterns of algorithms analysis. BMC Med Res Methodol 2017; 17:123.
   
type journal paper/review (English)
date of publishing 16-08-2017
journal title BMC Med Res Methodol (17/1)
ISSN electronic 1471-2288
pages 123
PubMed 28814269
DOI 10.1186/s12874-017-0400-y