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Background Through targeted medication alerts, clinical decision support systems (CDSS) help users to identify medication errors such as disregarded drug–drug interactions (DDIs). Override rates of such alerts are high; however, they can be mitigated by alert tailoring or workflow-interrupting display of severe alerts that need active user acceptance or overriding. Yet, the extent to which the displayed alert interferes with the prescribers' workflow showed inconclusive impact on alert acceptance. Objectives We aimed to assess whether and how often prescriptions were changed as a potential result of interruptive alerts on different (contraindicated) prescription constellations with particularly high risks for adverse drug events (ADEs). Methods We retrospectively collected data of all interruptive alerts issued between March 2016 and August 2020 in the local CDSS (AiDKlinik) at Heidelberg University Hospital. The alert battery consisted of 31 distinct alerts for contraindicated DDI with simvastatin, potentially inappropriate medication for patients > 65 years (PIM, N = 14 drugs and 36 drug combinations), and contraindicated drugs in hyperkalemia (N = 5) that could be accepted or overridden giving a reason in free-text form. Results In 935 prescribing sessions of 500 274 total sessions, at least one interruptive alert was fired. Of all interruptive alerts, about half of the sessions were evaluable whereof in total 57.5% (269 of 468 sessions) were accepted while 42.5% were overridden. The acceptance rate of interruptive alerts differed significantly depending on the alert type (p <0.0001), reaching 85.7% for DDI alerts (N = 185), 65.3% for contraindicated drugs in hyperkalemia (N = 98), and 25.1% for PIM alerts (N = 185). Conclusion A total of 57.5% of the interruptive medication alerts with particularly high risks for ADE in our setting were accepted while the acceptance rate differed according to the alert type with contraindicated simvastatin DDI alerts being accepted most frequently.

Objectives Clinical decision support systems (CDSSs) use alerts to enhance medication safety and reduce medication error rates. A major challenge of medication alerts is their low acceptance rate, limiting their potential benefit. A structured overview about modulators influencing alert acceptance is lacking. Therefore, we aimed to review and compile qualitative and quantitative modulators of alert acceptance and organize them in a comprehensive model. Methods In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline, a literature search in PubMed was started in February 2018 and continued until October 2021. From all included articles, qualitative and quantitative parameters and their impact on alert acceptance were extracted. Related parameters were then grouped into factors, allocated to superordinate determinants, and subsequently further allocated into five categories that were already known to influence alert acceptance. Results Out of 539 articles, 60 were included. A total of 391 single parameters were extracted (e.g., patients' comorbidity) and grouped into 75 factors (e.g., comorbidity), and 25 determinants (e.g., complexity) were consequently assigned to the predefined five categories, i.e., CDSS, care provider, patient, setting, and involved drug. More than half of all factors were qualitatively assessed (n = 21) or quantitatively inconclusive (n = 19). Furthermore, 33 quantitative factors clearly influenced alert acceptance (positive correlation: e.g., alert type, patients' comorbidity; negative correlation: e.g., number of alerts per care provider, moment of alert display in the workflow). Two factors (alert frequency, laboratory value) showed contradictory effects, meaning that acceptance was significantly influenced both positively and negatively by these factors, depending on the study. Interventional studies have been performed for only 12 factors while all other factors were evaluated descriptively. Conclusion This review compiles modulators of alert acceptance distinguished by being studied quantitatively or qualitatively and indicates their effect magnitude whenever possible. Additionally, it describes how further research should be designed to comprehensively quantify the effect of alert modulators.