Characterization of SOAP data on medication history in Japan using text mining

Abstract

Textual information on medication history, specifically the SOAP data created by pharmacists, accumulates subjective (S), objective (O), pharmacological assessment (A), and planning (P) data for patients with various diseases. Subjective data are crucial for evaluating drug safety, and SOAP data may be helpful for this evaluation; however, to the best of our knowledge, the characteristics of these data have not been studied systematically. After obtaining approval from the Teikyo University Medical Research Ethics Committee (approval number: 21-138-3), we analyzed 86,809 SOAP entries from 7,472 patients who visited Sundrug Co. Pharmacies and used the KH Coder (Higuchi, official package) to identify the characteristics, commonalities, and relevance of SOAP data on medication history by text mining. Morphological analysis and a co-occurrence network diagram of the frequently occurring words extracted revealed distinct connections and patterns across SOAP constituents: S data described patient symptoms and behavior, forming a network centered on symptoms and the physical condition of the patients; O data focused on prescriptions, drug names, and dosages, forming a network between these items and persons involved in administering the medication; A data indicated drug effects and side effects, forming a network with connections to pharmacists’ actions and evaluations; and P data formed a network between words describing patient guidance, side effect monitoring, and collaboration with other professionals. This analysis revealed the unique characteristics and commonalities among the SOAP data components.