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.

Although the recent revision of the ministerial ordinance on Good Post-marketing Study Practice (GPSP) included the utilization of medical information databases for post-marketing surveillance, there has been limited research on the validity of diagnosis codes and other outcome definitions in Japanese databases such as administrative claims (“receipt”) database. This task force proposed how to conduct good validations studies, based on the narrative review on around 100 published papers around the world. The established check list consists of ： (ⅰ) understanding the type of the database (e.g. administrative claims data, electronic health records, disease registry) ； (ii) understanding the setting of the validation study (e.g. “population-based” or not) ； (iii) defining the study outcome ； (iv) determining the way of linkage between databases ； (v) defining the gold standard ； (vi) selecting the sampling method (e.g. using the information of all patients in the database or a hospital, random sampling from all patients, random sampling from patients satisfying the outcome definition, random sampling from patients satisfying and not satisfying the outcome definition, “all possible cases” method) and sample size ； (vii) calculating the measures of validity (e.g. sensitivity, specificity, positive predictive value, negative predictive value) ； and (viii) discussing how to use the result for future studies. In current Japan, where the linkage between databases is logistically and legally difficult, most validation studies would to be conducted on a hospital basis. In such a situation, detailed description of hospital and patient characteristics is important to discuss the generalizability of the validation study result to the entire database. This report is expected to encourage and help to conduct appropriate validation studies.