Abstract
Background
Computerized detection is a promising method for monitoring adverse drug events (ADEs); however, this method is currently in its infancy and is a new area of exploration in China. This study aimed to develop a computerized ADE alarm and assessment system to help pharmacists effectively detect, assess, and analyze possible ADEs in patients in China.
Methods
Based on the clinical characteristics of these adverse drug events, we designed combined multiparameters as ADE alert rules to be assembled into detection configurations. We also developed system function modules by extracting data from the People’s Liberation Army (PLA) general hospital information system (electronic medical records). Positive predictive values were calculated for the alert.
Results
Five function modules were created in this platform: automatic screening, assisted evaluation, risk characteristic analysis, report generation into SRS (spontaneous reporting system), and a dictionary database. Four ADE alert configurations were set in our ADE alarm and assessment system: drug-related thrombocytopenia, anemia, liver injury, and kidney injury. The positive predictive values of the 4 monitored ADEs were approximately 44.4% to 95.8%.
Conclusions
An automatic ADE screening system was established for hospitalized patients in Chinese medical institutions. Compared with previous studies, combined drug-event alerts and a system-assisted assessment interface performed better than alerts based only on laboratory values. Furthermore, this platform’s assisted-layered evaluation and risk factor analysis functions could save considerable time for professionals and improve early prevention of potentially serious ADEs. To date, this system has been applied in 10 large-scale medical institutions.
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Chen, C., Jia, W., Guo, D. et al. Development of a Computer-Assisted Adverse Drug Events Alarm and Assessment System for Hospital Inpatients in China. Ther Innov Regul Sci 54, 32–41 (2020). https://doi.org/10.1007/s43441-019-00027-z
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DOI: https://doi.org/10.1007/s43441-019-00027-z