Modulators Influencing Medication Alert Acceptance: An Explorative Review

Abstract

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.

Evaluation of Triple Whammy Prescriptions After the Implementation of a Drug Safety Algorithm

“…The acceptance rate differed between the alerts and was highest within patients with a kidney function below 30 ml/min/1.73m2. This is line with other findings that alert acceptance correlates with the assessment of alert relevance by care providers [ 38 ]. A further comparison to the aforementioned primary care TW CDSSs is difficult, firstly, because not all details of the algorithms were published and secondly, because the interpretation of the performance parameters relies heavily on the setting in which the algorithms are used.…”

Interprofessional Evaluation of a Medication Clinical Decision Support System Prior to Implementation

“… 19 20 48 Considering overalerting as a risk for nonacceptance, several concepts have been developed and published to prevent alert fatigue and optimize overridden rates of reported alerts (e.g., tailoring the displayed alerts for selected wards or specific end-users). 43 49 50 51 Since customizing specific alerts in Meona (e.g., switch off a defined drug–drug interaction) is not possible for an individual site, we developed the configuration option “only-PULL” to prevent alert fatigue. Further, we added the possibility to filter severe alerts in the display of the check button (see Fig.…”

“…Nevertheless, interruptive alerts are generally considered more effective in terms of clinical outcomes (e.g., higher acceptance rates). 10 49 Therefore, the risk of overalerting by interruptive alerts on the one hand and potentially less effective clinical outcomes by passive alerts on the other hand must be weighed out. 51 53 Irrespective of the final decision of activation or deactivation of a Medication-Safety-Validator, every health care professional needs to be regularly informed and educated about the selected configuration and developed improvements.…”