Confounding Variables and the Performance of Triggers in Detecting Unreported Adverse Drug Reactions

Abstract

Purpose This study explored the performance of trigger in detecting adverse drug reactions (ADRs), the confounding variables impairing the causal association of the ADRs, and the underreporting rate by hospital health professionals. Methods A 6-month cross-sectional study was conducted in a public general hospital. Data collection was conducted in 2 stages: (1) screening of patient hospitalizations to identify suspected ADRs with 9 triggers developed by the Institute of Healthcare Improvement; and (2) chart review to perform the causality assessment of the suspected ADRs identified, to describe the confounding variables associated with detection of suspected ADRs that were not drug induced, and to analyze the positive predictive value of triggers in recognizing ADRs. To estimate the underreporting rate, ADRs detected by using the tool were compared with ADRs reported by health professionals during the same period. Findings During the study period, 3318 hospitalizations were analyzed. A total of 837 suspected ADRs were identified. However, after causality assessment, 356 were definite ADRs. Confounding variables associated with the detection-suspected ADRs were related to the clinical conditions of inpatients. The use of triggers contributed to increased ADR detection by 10.5%. The performance ranged from 0.00 to 0.75, with an overall positive predictive value of 0.43. Six ADRs were spontaneously reported, of which just 1 was also detected by using the trigger tool. Only 1 of 356 potential ADRs was reported by health professionals. Implications Findings show that the use of triggers contributes to detecting ADRs underreported by health professionals. However, confounding variables impaired the performance of the tool because they underestimated the causal association. Furthermore, both methods are complementary to early recognition of drug-induced harm and should be applied together in health institutions to contribute to policies of risk management, drug safety, and optimization of pharmacotherapy.