Tailoring Drug Interaction Alerts to the ICU Reduced Number of High-Risk Combos

Derick Alison
Derick Alison
7 Min Read

PHOENIX — Tailoring potential drug-drug interaction (DDI) alerts to the intensive care unit (ICU) setting significantly reduced the number of administered high-risk drug combinations, a cluster randomized stepped-wedge trial showed.

Among nearly 10,000 patients admitted to the ICU, the use of potential DDI alerts tailored to the ICU led to a 12% decrease (95% CI 5-18, P=0.0008) in the number of administered high-risk drug combinations per 1,000 drug administrations per patient, reported Joanna Klopotowska, PhD, PharmD, of Amsterdam University Medical Center in the Netherlands, at the Society of Critical Care Medicine Critical Care Congress.

The mean number of administered high-risk drug combinations per 1,000 drug administrations per patient was 26.2 in the intervention group compared with 35.6 in the control group, according to the findings, which were simultaneously published in The Lancet.

The intervention group also had a reduced length of ICU stay compared with the control group (P=0.0021), as well as a 9% higher proportion of appropriately monitored high-risk drug combinations (44% vs 35.5%, P<0.0001).

Klopotowska explained that while there are clinical decision support systems (CDSSs) available to assist providers and limit or prevent DDIs, real-world application, particularly in the ICU, has its challenges.

“Clinical decision support systems help to prevent drug interactions by providing alerts when two drugs, known to interact, are prescribed,” Klopotowska said. “However, this system seems to not work well in the ICU, and this is because the ICU environment differs from non-ICU wards.”

“There is a lot of monitoring going on, and also it is often not possible to refrain from prescribing interacting drugs,” she added. “Therefore, we see very high override rates of potential drug-drug interaction alerts in the ICU, up to 80%.”

In an accompanying comment, Andre Carlos Kajdacsy-Balla Amaral, MD, and Brian H. Cuthbertson, MBChB, MD, both of Sunnybrook Health Sciences Centre in Toronto, wrote that “these frustrating results from such promising technology can be explained by several factors, such as interface, workflow, acceptability, relevance, and timeliness of intervention, among others.”

“Chief among these factors is alert fatigue, when clinicians ignore alerts because of their excessive and intrusive nature,” they continued. “In one study, clinicians had to review 123 alerts to prevent a single adverse event. Several solutions exist for decreasing alert fatigue, such as streamlining the list of drug interactions, learning from past overridden alerts, and focusing such alerts on medications less commonly used.”

The commentators noted that the trial confirms “what the literature had already identified: that yes, alerts work, but in the current era of increasing computing power and artificial intelligence, the challenge is not to show that simplistic CDSSs work, but to create systems that are smarter, more user friendly, more interactive, and that have a higher positive predictive value for alerts in terms of clinically relevant outcomes.”

Klopotowska expressed hope that these findings can prove useful on a larger global scale, noting that she and her team “believe that our list of high-risk drug combinations is transferable to other systems, and also to other ICUs outside Netherlands — because the frequencies of DDIs is more or less comparable between countries.”

A total of nine ICUs in the Netherlands were included in the study, which supported approximately 11,000 admissions combined each year. Five ICUs already used potential DDI alerts.

In total, 9,887 patients admitted to the ICU between September 2018 and September 2019 were included. Mean age was 63, and 61-62% were men. The most common admission type was medical, followed by elective surgical admissions and emergency surgical admissions.

For the intervention, the researchers used a “restricted version” of the Medication Interaction Module (MiM) CDSS, which was changed to provide alerts to users only for potential DDIs considered clinically relevant to the ICU. The intervention CDSS was designated “MiM+.”

The four ICUs not already using MiM were provided access to MiM+, which was configured to provide DDI alerts for drug combinations that were high risk, while combinations that were low yield were turned off. The remaining five ICUs already using MiM were introduced to MiM+ under a similar configuration.

Intervention measures began being implemented in November 2018 through a stepped-wedge design. The first site was introduced to MiM+ in November, the second in December, and so on, until July 2019, when the CDSS was available at all sites.

The researchers noted that the small number of ICUs included in the trial may potentially limit its findings. Other possible limitations included factors impacting the effectiveness of CDSS implementation, like alert timing and design, which were not assessed in the study. Possible patient harm resulting from high-risk drug combinations was also not measured.

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    Elizabeth Short is a staff writer for MedPage Today. She often covers pulmonology and allergy & immunology. Follow


This study was funded by ZonMw.

Klopotowska reported no disclosures. Two co-authors reported being members of the NICE Registry Board.

Kajdacsy-Balla Amaral and Cuthbertson reported no disclosures.

Primary Source

The Lancet

Source Reference: Bakker T, et al “The effect of computerised decision support alerts tailored to intensive care on the administration of high-risk drug combinations, and their monitoring: a cluster randomised stepped-wedge trial” Lancet 2024; DOI: 10.1016/S0140-6736(23)02465-0.

Secondary Source

The Lancet

Source Reference: Kajdacsy-Balla Amaral AC, Cuthbertson BH “The efficiency of computerised clinical decision support systems” Lancet 2024; DOI: 10.1016/S0140-6736(23)02839-8.

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