The Use of Computerized Prescription Data in Hospitals and Community Pharmacies to Identify the Drug User Cohort for Comparative Observational Studies
10.3820/jjpe.13.1
- VernacularTitle:病院および保険薬局のコンピュータを利用したコホートの特定:薬剤疫学研究への応用可能性
- Author:
Nobuhiro OOBA
;
Tsugumichi SATO
;
Takao ORII
;
Keizou ISHIMOTO
;
Yoshihiro SHIMODOZONO
;
Teruo TANAKA
;
KUBOTA Kiyoshi
- Publication Type:Journal Article
- Keywords:
comparative observational studies;
selection bias;
databases;
E2E
- From:Japanese Journal of Pharmacoepidemiology
2008;13(1):1-10
- CountryJapan
- Language:Japanese
-
Abstract:
Background :There have been only a few comparative observational studies on the safety and effectiveness of drugs in Japan. Comparative observational studies would provide important information to address these issues and thus we need to establish a means to facilitate such studies. In comparative studies, it is important to prevent the distortion of results due to selection bias. Though we do not yet have a claims database for use in pharmacoepidemiological studies, recently many hospitals and pharmacies have computerized prescription data which may be used to minimize selection bias. Good standardized procedures for the identification of patients prescribed one of two or more drugs to compare in a study using computerized prescription data would serve as a basis for a variety of pharmacoepidemiological studies in Japan.
Methods :We carried out a questionnaire survey in 2753 hospitals and 909 community pharmacies to estimate the fraction of hospitals where computerized data can be used to identify all eligible patients who used a specific drug.
Results :Questionnaires were returned by 1942 (71%) of 2753 hospitals and 632 (70%) of 909 pharmacies. From among those which responded, patients were identified, the patient list was printed, and the electronic file of the patient list was generated in 75%, 64% and 36% of the 1942 hospitals and in 100%, 93% and 49% of the 632 pharmacies respectively.
Conclusion :With procedures using computerized prescription data, the cohort for observational comparative studies may be identified with a minimal selection bias in a majority of hospitals and pharmacies.
