Establishment,optimization and practice of an automatic central nervous system adverse reactions monitoring module based on hospital information system data
10.12173/j.issn.1005-0698.202401024
- VernacularTitle:基于医院信息系统数据的中枢神经系统不良反应自动监测模块构建优化与实践
- Author:
Haiyan LI
1
,
2
;
Daihong GUO
;
Man ZHU
;
Ao GAO
;
Jingchuan LU
;
An FU
;
Chao LI
;
Peng LI
;
Anqi ZHAO
Author Information
1. 中国人民解放军总医院医疗保障中心药剂科(北京 100853)
2. 重庆医科大学药学院(重庆 400016)
- Keywords:
Central nervous system;
Adverse drug reaction;
Imipenem/cilastatin;
Text classification technology;
Real world study
- From:
Chinese Journal of Pharmacoepidemiology
2024;33(9):971-977
- CountryChina
- Language:Chinese
-
Abstract:
Objective To construct a module for drug-induced central nervous system adverse reactions(CNS-ADR)within the Clinical Adverse Drug Event Active Monitoring and Intelligent Assessment Alert System-Ⅱ(ADE-ASAS-Ⅱ),and to conduct a large-scale,real-world active monitoring and evaluation of CNS-ADR specifically related to imipenem/cilastatin.Methods Based on literature review,spontaneous report evaluation,and initial word set of CNS-ADR related descriptions in electronic medical records,text recognition technology was used to construct and optimize the condition settings of the CNS-ADR automatic monitoring module.Hospitalized patients using imipenem/cilastatin were retrospectively monitored from 2017 to 2021,and the positive patients which had CNS-ADR were statistically described in terms of the demographic characteristics,CNS symptoms,and hospital departments.Results Based on a repeated testing optimization using 1 185 manually monitored results,the best setting for the determined module includes 62 sets of keywords,with a positive predictive value(PPV)of 13.63％and a recall rate of 100％.Expanding the monitoring to 8 222 medication users using this module,281 cases of positive causality were identified,with an incidence rate of 3.42％.Among them,patients over 60 years old accounted for 50.17％,and the main manifestations of CNS-ADR were epileptic seizures,headaches,mania,and delirium.Conclusion The CNS-ADR automatic monitoring module established based on ADE-ASAS-Ⅱ provides fast and reliable text data mining support for conducting real-world research on CNS-ADR.
