Pilot study of detecting adverse drug events with Global Trigger Tool
10.3760/cma.j.issn.1008-5734.1014.04.003
- VernacularTitle:全面触发工具在药品不良事件检测中的应用初探
- Author:
Jiaming LIU
1
;
Suying YAN
1
;
Chen LIU
1
;
Ning LIU
1
;
Xiaoling LI
1
;
Xiangrong BAI
1
;
Yawei WANG
1
;
Xingwei LI
1
;
Hongqin CHENG
1
;
Jing TANG
1
;
Yanqi CHU
1
;
Yuqin WANG
1
Author Information
1. 首都医科大学宣武医院药剂科, 北京,100053
- Publication Type:Journal Article
- Keywords:
Drug-related side effects and adverse reactions;
Medical records systems,computerized;
Global Trigger Tool
- From:
Adverse Drug Reactions Journal
2014;(4):198-204
- CountryChina
- Language:Chinese
-
Abstract:
Objective To investigate the feasibility of detecting adverse drug event( ADE)using Global Trigger Tool( GTT)in Chinese medical institutions. Methods Discharged patients' records of the Xuanwu Hospital of Capital Medical University from January 1st to December 31st 1013 were collected. After sorting by discharged date,30 cases were selected in a half month period by a random sampling tool of Microsoft Excell1007 software. Unqualified cases were eliminated according to the inclusion criteria( patients aged 18 and over,one time admission in 1013,and hospitalization for more than 1 day)and exclusion criteria( patients in the Department of Obstetrics,Family Planning,Rehabilitation,Oncology,Pediatrics, and day-care ward). The 10 cases were reviewed every half a month in sequence of random sampling using 35 triggers,including laboratory indexes,antidotes,clinical symptoms,and treatment measures,that were identified by GTT recommendation,relevant foreign researches,and self-experience of Xuanwu Hospital of Capital Medical University. All cases were enrolled if the number of cases which met the inclusion criteria was less than 10. The cases in whom triggers could be detected were marked as the cases with positive triggers. The cases with positive triggers-related situations were further reviewed in order to identify or exclude ADE and then the identified ADEs were classified. The positive triggers and ADEs were analyzed by Microsoft Excell1007 software and the positive predictive values of positive triggers were calculated. Results Totally 465 cases were reviewed. Of them,156 were male and 109 female with the mean age of 57(19~91)years. The time of hospital stay was 1 to 37 days with the mean hospital stay of 10 days. Of the 465 patients,in 108 patients(44. 7%)positive triggers could be detected. Of all the 35 triggers,11 triggers(61. 9%)were positive referring to 341 times. There were 18 ADEs identified involving 16 patients and the detectable rate was 3. 4%(16/465). Of the 18 ADEs,13 ADEs had their corresponding triggers containing 8 triggers. The overall positive predictive value of 11 positive triggers was 3. 8%. The 18 ADEs included pneumonia (1 ADEs),liver injury(1 ADEs),chill(1 ADEs),skin rash(1 ADEs),antibiotic-associated diarrhea (1 ADE),headache(1 ADE),dizziness(1 ADE),nausea and vomiting(1 ADE),hypoglycemia (1 ADE),over-sedation(1 ADE),delirium(1 ADE),bleeding(1 ADE),leucopenia(1 ADE),and excitation(1 ADE). There were 14 ADEs of class E and 4 ADEs of class F in the 18 ADEs which referred to 11 drugs including 5 kinds of antibacterial agents, 3 kinds of blood system drugs, 3 kinds of psychotherapeutic agents,1 kinds of cardiovascular drugs,1 kinds of hormone drugs,1 kinds of Chinese patent medicines,1 kind of lipid drug,1 kind of drug acting bone metabolism,1 kind of antipyretic analgesic,and 1 kind of anesthetic. Conclusions GTT could help to early detect the signals of ADEs and provide the reference evidence of preventing drug risk. It is valuable that GTT is popularized and used in Chinese medical institutions.
