scholarly journals PDG31 ESTIMATING COSTS OF CLUSTERED OUTPATIENT ADVERSE DRUG REACTIONS WITHIN THE VETERANS HEALTH ADMINISTRATION USING THE VA ADVERSE DRUG EVENT REPORTING SYSTEM

2019 ◽  
Vol 22 ◽  
pp. S167-S168
Author(s):  
M. Vu ◽  
V. Moore ◽  
A. Au ◽  
M. Bounthavong ◽  
S.L. Aspinall ◽  
...  
2021 ◽  
pp. 106002802110324
Author(s):  
Whitley J. Whitehead ◽  
Jennifer Meyer Reid

Background: Lisinopril-induced angioedema (LIA) is a rare but serious adverse drug event (ADE) with a published incidence of 0.1% to 0.7%. It is well known that ADEs are widely underreported; however, LIA is one of the most reported ADEs within the Veterans Health Administration (VHA). Objective: To estimate the effect of underreporting on the risk of LIA within VHA. Methods: The reported risk of LIA was calculated from reports submitted to the Veterans Affairs (VA) Adverse Drug Event Reporting System (VA ADERS) and the number of veterans prescribed lisinopril. To estimate underreporting, local chart review identified cases of LIA that were compared to reports submitted. The underreporting rate was then applied to the national reported risk. Results: Locally, 68 reports of LIA were submitted of the 21 262 patients prescribed lisinopril, for a reported risk of 0.32%. Nationwide, 14 289 reports of LIA were submitted of the 3 109 661 patients prescribed lisinopril, for a crude reported risk of 0.46%. Of the 324 patients identified for chart review, 240 patients were diagnosed with LIA, suggesting that at least 71.7% of cases were unreported. When this underreporting rate is extrapolated to the national reported risk, a better estimate of the risk of LIA within VHA could increase to 1.6%. Conclusion and Relevance: When estimating the effect of underreporting, the risk of LIA increases to approximately 1.6% or 1 in 63 patients. Because this ADE may affect more patients than previously understood, providers may wish to take LIA into consideration when prescribing lisinopril.


2021 ◽  
Vol 27 (3) ◽  
pp. 146045822110330
Author(s):  
Hyunah Shin ◽  
Jaehun Cha ◽  
Youngho Lee ◽  
Jong-Yeup Kim ◽  
Suehyun Lee

Pharmacovigilance involves monitoring of drugs and their adverse drug reactions (ADRs) and is essential for their safety post-marketing. Because of the different types and structures of medical databases, several previous surveillance studies have analyzed only one database. In the present study, we extracted potential drug–ADR pairs from electronic health record (EHR) data using the MetaNurse algorithm and analyzed them using the Korean Adverse Event Reporting System (KAERS) database for systematic validation. The Medical Dictionary for Regulatory Activities (MedDRA) and World Health Organization (WHO) Adverse Reactions Terminology (WHO-ART) were mapped for signal detection. We used the Side Effect Resource (SIDER) database to select 2663 drug-ADR pairs to investigate unknown drug-induced ADRs. The reporting odds ratio (ROR) value was calculated for the drug-exposed and non-exposed groups of drug–ADR pairs, and 19 potential pairs showed significant signals. Appropriate terminology systems and criteria are needed to handle diverse medical databases.


2015 ◽  
Vol 36 (7) ◽  
pp. 821-828 ◽  
Author(s):  
Thamir Alshammari, ◽  
Wa’ad Al-Kathiri ◽  
Hervé Le Louet ◽  
Hisham Aljadhey

2016 ◽  
Vol 136 (3) ◽  
pp. 499-505 ◽  
Author(s):  
Takamasa Sakai ◽  
Fumiko Ohtsu ◽  
Yasuaki Sekiya ◽  
Chiyo Mori ◽  
Hiroshi Sakata ◽  
...  

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