To implement an automated system that will identify impending and latent adverse drug events (ADEs) in hospitalized patients and to (1) assess the effectiveness of the system at identifying true‐positive ADEs and (2) assess the time it takes physicians to address the episodes of true‐positive ADEs. Specifically, our study will focus on ADEs that result in severe hypokalemia.
The targeted intervention and detection system (TIDS) project (funded by the Agency for Healthcare Research and Quality) is a computerized system that interfaces with our hospital's pharmacy and laboratory systems and allows us to identify a variety of potential ADEs in hospitalized patients. For the purposes of this study, we looked at the use of algorithms to detect severe hypokalemia caused by potential ADEs in patients on our hospitalist service over a12‐week period. The system triggers an alert under the following circumstances: a patient is on a potassium (K+)‐reducing medication (for example, furosemide) and serum K+ ≤ 3.0 mmol/L and decreases 0.8 mmol/L over 72 hours or serum K+ ≤ 2.5 mmol/L and decreases 0.5 mmol/L over 72 hours. Using explicit criteria, for each alert triggered, a hospitalist physician and/or a clinical pharmacist reviewed the medical record in order to determine if the alert was a true‐positive ADE.
We observed 40 incident cases of hypokalemia‐triggered alerts potentially caused by ADEs during the 12‐week period. The alerts were found to have a positive predictive value of 50%. Loop diuretics were found to be the most common inciting drug for the episodes of hypokalemia. Of the true‐positive alerts, we assessed the time it took physicians to treat patients for the episodes of hypokalemia with potassium chloride, KCl (see Fig. 1). For 4 episodes of hypokalemia, no treatment was given, or treatment was not given for over 8 hours.
Our study found that the TIDS system is effective at detecting potential ADEs caused by hypokalemia with reasonable positive predictive value. Our next step is to evaluate the system's effectiveness at detecting other types of ADEs and then using the system to automatically alert hospital physicians about potential ADEs in their patients.
M. Wilson, none; C. Moore, none; J. Downs, none.
To cite this abstract:Wilson M, Moore C, Downs J. A Targeted Intervention and Detection System to Detect Adverse Drug Events in Hospitalized Patients. Abstract published at Hospital Medicine 2008, April 3-5, San Diego, Calif. Abstract 86. Journal of Hospital Medicine. 2008; 3 (suppl 1). https://www.shmabstracts.com/abstract/a-targeted-intervention-and-detection-system-to-detect-adverse-drug-events-in-hospitalized-patients/. Accessed January 17, 2020.