Johnsen, Paul J.

Prolonged QT interval is an independent risk factor for all-cause mortality. However, evaluation of mortality associated to the implementation of a clinical decision support system to increase awareness and provide management recommendations has been challenging. Here we present our attempt to develop a model using only electronic data and different control groups.

Familial Hypercholesterolemia (FH) is underdiagnosed in the United States. Clinical decision support (CDS) could increase FH detection once implemented in clinical workflows. We deployed CDS for FH at an academic medical center and sought clinician insights using an implementation survey. In November 2020, the FH CDS was deployed in the electronic health record at all Mayo Clinic sites in two formats: a best practice advisory (BPA) and an in-basket alert. Over three months, 104 clinicians participated in the survey (response rate 11.1%). Most clinicians (81%) agreed that CDS implementation was a good option for identifying FH patients; 78% recognized the importance of implementing the tool in practice, and 72% agreed it would improve early diagnosis of FH. In comparing the two alert formats, clinicians found the in-basket alert more acceptable (p = 0.036) and more feasible (p = 0.042) than the BPA. Overall, clinicians favored implementing the FH CDS in clinical practice and provided feedback that led to iterative refinement of the tool. Such a tool can potentially increase FH detection and optimize patient management.

Introduction: The main goal of Clinical Decision Support (CDS) is to provide timely and useful information for providers to deliver high-quality and safe care. Issues, like alert fatigue and provider burnout are commonly cited as unintended consequences of the CDS systems. Herein, we describe leveraging electronic health record (EHR) self-service reporting tools to gain insights on a CDS rule designed to avoid providers from ordering QT-prolonging medication in patients with history of QT-prolongation. Methods: Our EHR (Epic) SlicerDicer reporting tool was used to identify the frequency of QT-prolongation Best Practice Advisory (BPA) triggerings from 1/1/2020 to 12/31/2020 across Mayo Clinic sites. Additionally, associated patient encounter and BPA-specific data were queried. Text from acknowledgement comments to the BPA were reviewed and central themes and comments were categorized. Epic Clarity Data Warehouse was queried to identify the BPA-triggering medications and frequencies. Comparisons of percent action taken on the BPA were compared internally to Mayo Clinic’s BPA benchmark, and with national benchmarks using Epic BestPractice Pulse dashboard. Results: A total of 17,538 BPAs of interest were triggered across the Mayo Clinic sites in 2020, of which 3,696 (20.1%) were acted upon through either monitoring or medication discontinuation. This is below Mayo Clinic’s median of 29.2% for inpatient BPAs and 45.6% BPAs for outpatient, but above the national median of 10% (IQR 6.1-13.1%) for inpatient and 10% (IQR 4.3-19.5%) for outpatient BPAs actioned upon. A total of 30 different medications triggered the BPA, with the most common being ondansetron (41.5%), amiodarone (11.3%), and haloperidol (10.1%). User comments were left on 2,382 orders (13.5%) that acknowledged the BPA, but provided argument to prescribe drug. Three most common themes identified from comments on overridden BPAs: patient previously tolerated medication (19.0%), QT interval not prolonged on recent ECG (14.2%), and patient on hospice care (5.2%). Conclusion: Analysis of free text comments of CDS can be and should be performed to reveal opportunities for further improvement of CDS. Providers should be encouraged to provide comments when encountering CDS interventions.