Use of mind maps and iterative decision trees to develop a guideline-based clinical decision support system for routine surgical practice: case study in thyroid nodules.

Abstract

The study sought to develop a clinical decision support system (CDSS) for the treatment of thyroid nodules, using a mind map and iterative decision tree (IDT) approach to the integration of clinical practice guidelines (CPGs). Thyroid nodule CPGs of the American Thyroid Association and Korean Thyroid Association were analyzed by endocrine surgeons (domain experts) and computer scientists. Clinical knowledge from the CPGs was expressed using mind maps. The mind maps were analyzed and converted into IDTs. The final IDT was implemented as a set of candidate rules (3700) for a knowledge-based CDSS. The system was evaluated via a retrospective review of the medical records of 483 patients who had undergone thyroidectomy between January and December 2015 at a single tertiary center (Seoul National University Hospital Bundang, Korea). Concordance between CDSS recommendations and treatment in routine clinical practice was 78.9%. In the 21.1% discordant cases, deviation from the CDSS treatment recommendation was mainly attributable to (1) refusal of the patient to undergo total thyroidectomy and (2) conversion from lobectomy to total thyroidectomy following an unexpected histological finding during intraoperative frozen biopsy lymph node analysis. The present study demonstrated that a knowledge-based CDSS is feasible in the treatment of thyroid nodules. A high-quality knowledge-based CDSS was developed, and medical domain and computer scientists collaborated effectively in an integrated development environment. The mind map and IDT approach represents a pioneering method of integrating knowledge from CPGs.