Draper, Evan W

Abstract Objectives Since the 1970s, a plethora of tools have been introduced to support the medication use process. However, automation initiatives to assist pharmacists in prospectively reviewing medication orders are lacking. The review of many medications may be protocolized and implemented in an algorithmic fashion utilizing discrete data from the electronic health record (EHR). This research serves as a proof of concept to evaluate the capability and effectiveness of an electronic prospective medication order review (EPMOR) system compared to pharmacists’ review. Materials and methods A subset of the most frequently verified medication orders were identified for inclusion. A team of clinical pharmacist experts developed best-practice EPMOR criteria. The established criteria were incorporated into conditional logic built within the EHR. Verification outcomes from the pharmacist (human) and EPMOR (automation) were compared. Results Overall, 13 404 medication orders were included. Of those orders, 13 133 passed pharmacist review, 7388 of which passed EPMOR. A total of 271 medication orders failed pharmacist review due to order modification or discontinuation, 105 of which passed EPMOR. Of the 105 orders, 19 were duplicate orders correctly caught by both EPMOR and pharmacists, but the opposite duplicate order was rejected, 51 orders failed due to scheduling changes. Discussion This simulation was capable of effectively discriminating and triaging orders. Protocolization and automation of the prospective medication order review process in the EHR appear possible using clinically driven algorithms. Conclusion Further research is necessary to refine such algorithms to maximize value, improve efficiency, and minimize safety risks in preparation for the implementation of fully automated systems.

Abstract Introduction During the early phase of the coronavirus disease 2019 (COVID‐19), remdesivir was only approved for hospitalized patients. Our institution developed hospital‐based, outpatient infusion centers for selected hospitalized patients with COVID‐19 who had clinical improvement to allow for early dismissal. The outcomes of patients who transitioned to complete remdesivir in the outpatient setting were examined. Methods Retrospective study of all hospitalized adult patients with COVID‐19 who received at least one dose of remdesivir from November 6, 2020, to November 5, 2021, at one of the Mayo Clinic hospitals. Results Among 3029 hospitalized patients who received treatment with remdesivir for COVID‐19, the majority (89.5%) completed the recommended 5‐day course. Among them, 2169 (80%) patients completed treatment during hospitalization, whereas 542 (20.0%) patients were dismissed to complete remdesivir in outpatient infusion centers. Patients who completed the treatment in the outpatient setting had lower odds of death within 28 days (aOR 0.14, 95% CI 0.06–0.32, p < 0.001). However, their rate of subsequent hospital encounters within 30 days was higher (aHR 1.88, 95% CI 1.27–2.79, p = 0.002). Among patients treated with remdesivir only in the inpatient setting, the adjusted odds of death within 28 days were significantly higher among those who did not complete the 5‐day course of remdesivir (aOR 2.07, 95% CI 1.45–2.95, p < 0.001). Conclusions This study describes the clinical outcomes of a strategy of transitioning remdesivir therapy from inpatient to outpatient among selected patients. Mortality was lower among patients who completed the 5‐day course of remdesivir.

Abstract Purpose The intravenous (IV) medication compounding workflow has long been associated with preventable medication errors. This has led to the development of technologies designed to enhance the safety of IV compounding workflows. Digital image capture is a component of this technology about which there is relatively limited published literature. This study evaluates image capture implemented within an electronic health record’s existing first-party IV workflow solution. Methods A retrospective case-control study was conducted to measure IV preparation times before and after digital imaging implementation. Preparations during 3 periods (preimplementation, ≤1 month post implementation, and &gt;1 month post implementation) were matched for 5 variables. A less stringent analysis with matching for 2 variables, as well as an unmatched analysis, were performed post hoc. An employee survey assessed satisfaction with the digital imaging workflow, and revised orders were reviewed to identify new problems introduced by image capture. Results A total of 134,969 IV dispenses were available for analysis. Median preparation time in the preimplementation and &gt;1 month post implementation cohorts was unchanged in the 5-variable matched analysis (6.87 minutes vs 6.58 minutes, P = 0.14) and increased in the 2-variable matched analysis (6.98 minutes vs 7.35 minutes, P &lt; 0.001) and unmatched analysis (6.55 minutes vs 8.02 minutes, P &lt; 0.001). A large majority of survey respondents (92%) felt that image capture improved patient safety. Of the 105 postimplementation preparations identified as requiring revisions by the checking pharmacist, 24 (22.9%) required revisions directly related to camera functionality. Conclusion Implementation of digital image capture likely increased preparation times. Most IV room staff felt that image capture increased preparation times and were satisfied with how the technology improved patient safety. Image capture introduced camera-specific issues that led to preparations requiring revisions.