论著
Liu Jiaming;Yan Suying;Liu Chen;Liu Ning;Li Xiaoling;Bai Xiangrong;Wang Yawei;Li Xingwei;Cheng Hongqin;Tang Jing;Chu Yanqi;Wang Yuqin
2014, 16(4): 198-7.
ObjectiveTo investigate the feasibility of detecting adverse drug event (ADE) using Global Trigger Tool (GTT) in Chinese medical institutions.MethodsDischarged patients′ records of the Xuanwu Hospital of Capital Medical University from January 1st to December 31st 2013 were collected. After sorting by discharged date, 30 cases were selected in a half month period by a random sampling tool of Microsoft Excel 2007 software. Unqualified cases were eliminated according to the inclusion criteria (patients aged 18 and over, one time admission in 2013, 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 20 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 20. 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 Excel 2007 software and the positive predictive values of positive triggers were calculated.ResultsTotally 465 cases were reviewed. Of them, 256 were male and 209 female with the mean age of 57 (19~92) years. The time of hospital stay was 2 to 37 days with the mean hospital stay of 10 days. Of the 465 patients, in 208 patients(44.7%)positive triggers could be detected. Of all the 35 triggers, 22 triggers (62.9%) were positive referring to 342 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 22 positive triggers was 3.8%. The 18 ADEs included pneumonia (2 ADEs), liver injury (2 ADEs), chill (2 ADEs), skin rash (2 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 21 drugs including 5 kinds of antibacterial agents, 3 kinds of blood system drugs, 3 kinds of psychotherapeutic agents, 2 kinds of cardiovascular drugs, 2 kinds of hormone drugs, 2 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.ConclusionsGTT 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.
