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Creation of Drug Information Database for Nonprescription Drugs

一般用医薬品医薬情報データベースの構築
Authors: Taeyuki Oshima; Masanori Takei; Chieko Maida; Etsuko Miyamoto;

Creation of Drug Information Database for Nonprescription Drugs

Abstract

To help ensure the proper use of nonprescription drugs, we developed a drug information database with a drug interaction checking function. The database was set up by using Microsoft® Access 2002 for Windows. There are a total of eight tables in the database : drug information for nonprescription and prescription drugs, ingredients of nonprescription and prescription drugs, product information for nonprescription drugs, drug interactions, contraindications, and therapeutic categories. All tables have links to each other using the Japanese Article Number (JAN) Code and generic names. The data used for the database were taken from resources such as “Japan Self-Medication Database Center”, “The Medical Information System Development Center”, “Japan Pharmaceutical Information Center”, and “Hansten and Horn's Drug Interactions (Facts and Comparisons)”. Three different levels are assigned to drug interactions : avoid combination (level 1), avoid combination unless benefit outweighs risk (level 2), and monitor (level 3).The database contains data on 14, 496 nonprescription drugs and 18, 159 prescription drugs. A total of 2, 094 drug interactions are recorded, 14 of them assigned level 1, 165 level 2 and 1915 level 3. Five hundred sixty-three ingredients were used for both prescription and nonprescription drugs, 218 ingredients of them having contraindications when used as prescription drugs. The database efficiently retrieves general drug information, information on drug interactions and contraindications for nonprescription drugs when enquiries are made using brand names, generic names, or JAN codes. We consider our database to be a useful tool for ensuring the proper use of drugs and for promoting self-medication.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Top 10%
Average
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