The Fuzzy System as a Promising Tool for Drugs Selection in Medical Practice

The aim of this paper was to demonstrate the potential of the fuzzy system approach to the analysis of healthcare databases for clinicians in their routine daily practice. The healthcare data about 50000 medical prescription items for 38990 individual patients and 2601 various codes of diagnoses categorized according to Slovak version of the tenth revision of the International Statistical Classification of Diseases and Related Health Problems were used for the retrospective study. The fuzzy system approach was applied to the analysis of medical prescription items for I10.90 and E11.90 comorbid patients as the most frequently identified cardiovascular and endocrine codes of diagnoses. Nearly 64% of co-identified I10.90 and E11.90 patients were associated with other additional diagnose. According to the fuzzy system approach, the metformin or glimepiride in combination with moxonidine, metoprolol, or amlodipine was identified as the mainstream drug preferences and/or individual “know-how” of clinicians in pharmacotherapy of mentioned polymorbid patients from 21 various active substances. The results of this paper suggest that the fuzzy system approach to healthcare data obtained from insurance companies may be a helpful way of generating information useful for final decision process in the drugs selection for similar polymorbid patients in medical practice. The obtained data can be used as recommendations for other and/or for less experienced clinicians in drugs selection for patients with similar (or unusual) combinations of diagnoses as well as in clinical situations where the “golden” pharmacotherapeutic standards have not been precisely specified or are totally absent for multi-comorbid patients.