ABSTRACT
Background: Tolvaptan is the only US Food and Drug Administration-approved drug to slow the progression of autosomal dominant polycystic kidney disease (ADPKD), but it requires strict clinical monitoring due to potential serious adverse events. Objective: We aimed to share our experience in developing and implementing an electronic health record (EHR)-based application to monitor patients with ADPKD who were initiated on tolvaptan. Methods: The application was developed in collaboration with clinical informatics professionals based on our clinical protocol with frequent laboratory test monitoring to detect early drug-related toxicity. The application streamlined the clinical workflow and enabled our nursing team to take appropriate actions in real time to prevent drug-related serious adverse events. We retrospectively analyzed the characteristics of the enrolled patients. Results: As of September 2022, a total of 214 patients were enrolled in the tolvaptan program across all Mayo Clinic sites. Of these, 126 were enrolled in the Tolvaptan Monitoring Registry application and 88 in the Past Tolvaptan Patients application. The mean age at enrollment was 43.1 (SD 9.9) years. A total of 20 (9.3%) patients developed liver toxicity, but only 5 (2.3%) had to discontinue the drug. The 2 EHR-based applications allowed consolidation of all necessary patient information and real-time data management at the individual or population level. This approach facilitated efficient staff workflow, monitoring of drug-related adverse events, and timely prescription renewal. Conclusions: Our study highlights the feasibility of integrating digital applications into the EHR workflow to facilitate efficient and safe care delivery for patients enrolled in a tolvaptan program. This workflow needs further validation but could be extended to other health care systems managing chronic diseases requiring drug monitoring.
ABSTRACT
BACKGROUND AND AIMS: Nearly all routine endoscopy procedures are performed using moderate sedation (MS) or monitored anesthesia care (MAC). In this article, we describe how we improved decision-making and decreased practitioners' cognitive burden for choosing between MAC and MS by using patient data in an automated application within the electronic health record (EHR). METHODS: In our practice, we choose between MS or MAC for routine GI procedures according to written anesthesia-use guidelines and practitioner preferences. To expedite our decision-making for MS versus MAC, we developed an Excel (Microsoft Corp, Redmond, Wash, USA)-based tool from patient demographic characteristics, comorbid conditions, and medication use extracted from the EHR. The data points from Excel were then implemented in the automated application in the EHR to predict the type of sedation for GI procedures. RESULTS: Before use of the new application, nurses spent an average of 4 minutes and gastroenterology practitioners spent 5 minutes reviewing the EHR to determine the appropriate sedation (MS or MAC). After the application was implemented, the use of MS substantially increased. Time spent reviewing the EHR was reduced to 2 minutes. The rate of adverse events for MS (.5%) versus MAC (.6%) was comparable and low overall. CONCLUSIONS: The EHR-based application, which automates and standardizes determination of sedation type, is a highly beneficial tool that eliminates subjectivity in decision-making, thus allowing for appropriate use of MAC. Adverse event rates and sedation failure did not increase with use of the application. With the increased use of MS over MAC, healthcare costs for the more-expensive MAC sedation should also decrease.
