The effect of ICU-tailored drug-drug interaction alerts on medication prescribing and monitoring: protocol for a cluster randomized stepped-wedge trial

Abstract

Background Drug-drug interactions (DDIs) can cause patient harm. Between 46 and 90% of patients admitted to the Intensive Care Unit (ICU) are exposed to potential DDIs (pDDIs). This rate is twice as high as patients on general wards. Clinical decision support systems (CDSSs) have shown their potential to prevent pDDIs. However, the literature shows that there is considerable room for improvement of CDSSs, in particular by increasing the clinical relevance of the pDDI alerts they generate and thereby reducing alert fatigue. However, consensus on which pDDIs are clinically relevant in the ICU setting is lacking. The primary aim of this study is to evaluate the effect of alerts based on only clinically relevant interactions for the ICU setting on the prevention of pDDIs among Dutch ICUs. Methods To define the clinically relevant pDDIs, we will follow a rigorous two-step Delphi procedure in which a national expert panel will assess which pDDIs are perceived clinically relevant for the Dutch ICU setting. The intervention is the CDSS that generates alerts based on the clinically relevant pDDIs. The intervention will be evaluated in a stepped-wedge trial. A total of 12 Dutch adult ICUs using the same patient data management system, in which the CDSS will operate, were invited to participate in the trial. Of the 12 ICUs, 9 agreed to participate and will be enrolled in the trial. Our primary outcome measure is the incidence of clinically relevant pDDIs per 1000 medication administrations. Discussion This study will identify pDDIs relevant for the ICU setting. It will also enhance our understanding of the effectiveness of alerts confined to clinically relevant pDDIs. Both of these contributions can facilitate the successful implementation of CDSSs in the ICU and in other domains as well. Trial registration Nederlands Trial register Identifier: NL6762 . Registered November 26, 2018.

Clinical Decision Support and Implications for the Clinician Burnout Crisis

“…The alert firing rate (n=12) 43 55 62 69 70 71 72 73 74 75 76 77 and alert acceptance rate (n=15) 27 29 43 58 61 62 69 74 78 79 80 81 82 83 84 were also common metrics used to understand alarm fatigue and acceptability. Although metrics of relevance such as sensitivity, specificity, and positive predictive value (PPV) were referenced several times 77 84 85 86 87 88 , only one study evaluated these metrics as pre-specified outcomes 49 . Tools for capturing clinician burnout, stress, or satisfaction after using a CDS tool were used in nine studies 26 44 78 80 82 89 90 91 92 .…”

“…Similar to Bubp et al, expert panels were used in several studies to improve the relevance of CDS [62,71,88]. Expert panels can be advantageous over stock alerts.…”

A Study on Design, Development, Implementation, and Evaluation of Severe Drug-Drug Interaction Alert System in ICU

“…However, most physicians actions over the overridden recommendations were appropriate (39). Even though a small fraction of serious DDIAs were overridden in this study, some overriding of DDIAs are acceptable in the ICU because patients are closely observed (13,44). The signi cance of these ndings is that the serious DDIAs and actionable recommendations contribute to reduce the overridden rate of DDIA in the ICU (14,45).…”

Computational pharmacology: New avenues for COVID-19 therapeutics search and better preparedness for future pandemic crises

“…Understanding drug combination use is also integral in the intensive care settings where patients are treated with many pharmaceuticals at once. It has been reported that between 46 and 90% of patients admitted to the intensive care unit (ICU) are exposed to potential drug-drug interactions [ 138 ]⁠.…”