Prescription Pattern Analysis of Type 2 Diabetes Mellitus: A Cross-Sectional Study in Isfahan, Iran

Abstract

Abstract Background Patients with Type 2 Diabetes Mellitus (T2DM) are at a higher risk of polypharmacy and more susceptible to irrational prescriptions; therefore, pharmacological therapy patterns are important to be monitored. The primary objective of this study was to highlight the current prescription patterns in TD2M patients and compare them with the existing standards of medical care in diabetes. The second objective was to analyze whether age and gender affect prescription patterns. Methods This cross-sectional study was conducted using Iran Health Insurance Organization (IHIO) prescription database. It was mined by an Association Rule Mining (ARM) technique, named FP-Growth, in order to find co-prescribed drugs with anti-diabetic medications. The algorithm was implemented on different levels of Anatomical Therapeutic Chemical (ATC) classification system, which assigns different codes to drugs based on their anatomy, pharmacological, therapeutics and chemical properties, to provide in-depth analysis of co-prescription patterns. Results Altogether the prescriptions of 914,652 patients, out of which 91,505 were diabetic, were analyzed. According to our results, prescribing Lipid Modifying Agents (C10) (56.3%), Agents Acting on The Renin-Angiotensin System (C09) (48.9%), Antithrombotic Agents (B01) (35.7%), and Beta Blocking Agents (C07) (30.1%) were meaningfully associated with the prescription of Drugs Used in Diabetes. Our study also revealed that female diabetic patients have a higher chance of taking Antithyroid agents, and the older the patients were, the more they were prone to take neuropathy-related medications. Conclusions Almost all of the association rules found in this research were clinically meaningful, proving the potential of ARM for co-prescription pattern discovery. Moreover, implementing level-based ARM was effective for detecting difficult-to-spot rules. Additionally, the majority of drugs prescribed by physicians were consistent with the Standards of Medical Care in Diabetes.