# Application and evaluation of the global trigger tool approach to adverse drug event monitoring in the high-risk elderly inpatients with multiple chronic diseases

## TL;DR

This study developed and tested a method to detect adverse drug events in elderly patients with multiple chronic diseases, showing it is effective and reliable.

## Contribution

A tailored Global Trigger Tool for ADE monitoring in high-risk elderly inpatients with multiple chronic diseases is proposed and validated.

## Key findings

- The GTT method achieved 78.46% sensitivity and 82.65% specificity in detecting ADEs.
- Cardiovascular drugs caused the most ADEs, and metabolic/nutritional disorders were the most affected organ-system.
- Age and number of positive triggers were significant predictors of ADE occurrence.

## Abstract

To establish a Global Trigger Tool (GTT) method suitable for monitoring adverse drug events (ADEs) in the high-risk elderly inpatients with multiple chronic diseases, and to evaluate its sensitivity, specificity and feasibility.

A total of 38 triggers were established by searching the literature and combining the characteristics of elderly hospitalized patients with multiple chronic diseases in Taizhou People’s Hospital. A total of 480 elderly patients with multiple chronic diseases were sampled from January to December 2023, and the cases were reviewed. Adverse event grades were determined, and drug classes and organ-systems involved were analyzed; binary logistic regression and Receiver Operating Characteristic curves were adopted for analysis.

Among the 480 cases, 123 cases were detected as having one or more positive triggers. ADEs occurred in 65 patients, with a total of 93 occurrences of ADEs; the highest number of ADE cases was observed in the administration of cardiovascular drugs, with 36 cases (38.71%). The highest organ-system involved in ADE was metabolic and nutritional disorders, with 47 cases (50.54%). The number of ADEs occurring in 1,000 patient-days was 22.90. The number of ADEs occurring in 100 patients was 19.38. Using binary logistic regression analysis, the risk factors were age and number of positive trigger detections for predicting the occurrence of ADEs. The GTT method had a sensitivity of 78.46%; specificity of 82.65%; compliance rate of 82.00%; Kappa value of 44.40%; and the Positive Predictive Value (PPV) was 41.46%.

The GTT method has high sensitivity and specificity and is feasible; it has a relatively high PPV and is suitable for detecting ADEs in the high-risk elderly inpatients with multiple chronic diseases.