Global Trigger Tool: Proficient Adverse Drug Reaction Autodetection Method in Critical Care Patient Units
Amee D Pandya, Kalan Patel, Devang Rana, Sapna D Gupta, Supriya D Malhotra, Pankaj Patel
Adverse drug reactions, Emergency department, Pharmacovigilance, Trigger tool
Citation Information :
Pandya AD, Patel K, Rana D, Gupta SD, Malhotra SD, Patel P. Global Trigger Tool: Proficient Adverse Drug Reaction Autodetection Method in Critical Care Patient Units. Indian J Crit Care Med 2020; 24 (3):172-178.
Background: Emergency department (ED) being the most crucial part of hospital, where adverse drug reactions (ADRs) often go undetected. Trigger tools are proficient ADR detection methods, which have only been applied for retrospective surveillance. We did a prospective analysis to further refine the trigger tool application in healthcare settings. Objective: To estimate the prevalence of ADRs and prospectively evaluate the importance of using trigger tools for their detection. Materials and methods: A prospective study was conducted in the ED for the presence of triggers in patient records to monitor and report ADRs by applying the Institute for Healthcare Improvement (IHI) trigger tool methodology. Results: Four hundred sixty-three medical records were analyzed randomly using 51 trigger tools, where triggers were found in 181 (39.09%) and ADRs in 62 (13.39%) patients. The prevalence of ADR was 13.39%. According to the World Health Organization (WHO)-Uppsala Monitoring Centre (UMC) causality scale, 47 (75.8%) were classified as probable and 15 (24.2%) as possible, wherein 39 (62.9%) were predictable and 8 (12.9%) were definitely preventable. Most common triggers were abrupt medication stoppage (34.98%), antiemetic use (25.91%), and time in ED >6 hours (17.49%). The positive predictive values (PPVs) of triggers such as international normalized ratio (INR) > 4 (p = 0.0384), vitamin K administration (p = 0.002), steroid use (p = 0.0001), abrupt medication stoppage (p = 0.0077), transfusion of blood or blood products (p = 0.004), and rash (p = 0.0042) showed statistically significant results, which make the event detection process more structured when these triggers are positive. Presence of five or more triggers has statistically significant chances of developing an ADR (p < 0.05). Conclusion: Trigger tool could be a viable method to identify ADRs when compared to the traditional ADR identification methods, but there is insufficient data on IHI tool and its use to identify ADRs in the general outpatient setting. Healthcare providers may benefit from better trigger tools to help them detect ADRs.
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