Added language to rationale: "The approach this IG suggests could be effective at reducing the number of alerts and increasing their relevance. For example, a recent study developed, validated, and tested 8 contextualized drug-drug interaction alert algorithms that used data from electronic health records data to fine-tune the alerts to a given patient. The interactions were chosen based on monthly override rates from a single large care facility. Testing on retrospective real-world data showed the potential for the eight algorithms to reduce alerts that interrupt clinician workflow by more than 50% from baseline.^{[4] (#references)}" 4. Chou, E., Boyce, RD., Balkan, B., Rosko, S., Subbian, V., Romero, A., Hansten, P., Horn, J., Gephart, S., Malone, DC. Designing and Evaluating Contextualized Drug-Drug Interaction Algorithms. Accepted to JAMIA Open 02/26/2021. JAMIO-2020-0010.R3. PubMed ID: in process. PubMedCentral ID: In process.