title: Development of a database and processing method for detecting hematotoxicity adverse drug events.
abstract: Adverse events are detected by monitoring the patient's status, including blood test results. However, it is difficult to identify all adverse events based on recognition by individual doctors. We developed a system that can be used to detect hematotoxicity adverse events according to blood test results recorded in an electronic medical record system. The blood test results were graded based on Common Terminology Criteria for Adverse Events (CTCAE) and changes in the blood test results (Up, Down, Flat) were assessed according to the variation in the grade. The changes in the blood test and injection data were stored in a database. By comparing the date of injection and start and end dates of the change in the blood test results, adverse events related to a designated drug were detected. Using this method, we searched for the occurrence of serious adverse events (CTCAE Grades 3 or 4) concerning WBC, ALT and creatinine related to paclitaxel at Osaka University Hospital. The rate of occurrence of a decreased WBC count, increased ALT level and increased creatinine level was 36.0%, 0.6% and 0.4%, respectively. This method is useful for detecting and estimating the rate of occurrence of hematotoxicity adverse drug events.
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Yoshie
authors.initials: Y
authors.lastname: Shimai
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Toshihiro
authors.initials: T
authors.lastname: Takeda
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Shirou
authors.initials: S
authors.lastname: Manabe
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Kei
authors.initials: K
authors.lastname: Teramoto
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Naoki
authors.initials: N
authors.lastname: Mihara
authors.affiliation: Medical Informatics, Osaka University Graduate School of Medicine, Osaka, Japan.
authors.forename: Yasushi
authors.initials: Y
authors.lastname: Matsumura
mesh_terms: D016907:Adverse Drug Reaction Reporting Systems / Q000458:organization & administration*; D015415:Biomarkers / Q000097:blood; D003628:Database Management Systems; D062313:Databases, Pharmaceutical; D020000:Decision Support Systems, Clinical / Q000458:organization & administration; D064420:Drug-Related Side Effects and Adverse Reactions / Q000097:blood* / Q000175:diagnosis* / Q000453:epidemiology; D057286:Electronic Health Records / Q000458:organization & administration*; D006801:Humans; D016247:Information Storage and Retrieval / Q000379:methods*; D007564:Japan; D015995:Prevalence; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D015415:Biomarkers