Patient Drug Database: 환자 생성 건강 데이터를 활용한 환자 주도적 약물 부작용 탐색을 위한 데이터베이스 구축

Abstract

Objectives: This study focuses on building a database for patient-led search on drug side effects using basic drug information, drug analysis results information, patient information, and patient-generated health data (PGHD). Methods: After collecting data from the Health Insurance Review and Assessment Institute, the Korean Pharmaceutical Information Center, the Ministry of Food and Drug Safety, and the Korean Pharmaceutical Association, basic drug information was created. By utilizing the Korea Average Event Reporting System (KAERS) side effect report data provided by the Korea Drug Safety Administration and MetaLAB, a drug side effect detection algorithm applied on the Konyang university hospital’s real data, we designed and built a database using Oracle DB, which contains a table of patient information and PGHD. For drug information, a total of 49,553 drugs were mapped, and drug analysis results used KAERS and MetaLAB. Results: Based on the collected drug information, a total of 15 tables containing basic drug information (7 tables), drug analysis results (2 tables), patient information (1 table), and patient generation information (5 tables) were created using EDI codes, fol lowing mapping and normalization. Basic drug information included 49,553 EDI and 2,099 ATC codes. Drug analysis results included 2,046 KAERS ATC codes, 1,701 WHOART-ARRN (PT) that the result of 33 WHOART-SEQ (IT), 15,861 MetaLABEDI codes, and 101ATC codes. TheADR results were constructed using 62 DRUG_IDs and 73 MedDRA_PTI_IDs. Conclusions: The Patient Drug Database (PD2B) in this study was employed to allow patients to volun tarily report on their perception and drug side effects through application tools, which can provide quick measures against drug side effects and assist in the discovery of new ones.