Introduction & Objective: Though clinical guidelines recommend diabetes distress (DD) screening, real-world screening is hindered by the burden of implementing screening regimens into clinical workflow. Our objective was to automate DD screening for people with type 1 diabetes (T1D) at a university-affiliated outpatient endocrinology clinic by building it into the EHR system.
Methods: We undertook an EPIC build to screen patients with T1D using the T1-DDAS Core Distress Scale (“screener”) and equip providers with the language to address DD. We developed and iterated the (1) eligibility criteria for distribution; (2) the patient-view of the screener; (3) scoring and storing of results; and (4) infrastructure for providers to be notified and research personnel to receive lists of patients with elevated DD.
Results: Our EHR now supports delivery of a DD screener with built-in scoring in MyChart (Figure 1); a Flowsheet showing current and past results; a front desk view to identify patients who had not yet completed the screener; a BPA (Best Practice Advisory) for the provider to address DD; and a research view.
Conclusion: This project provides proof of concept that DD screening can be integrated into the EHR to promote guidelines-aligned screening and increased clinical attention to DD. Future work involves clinic-level implementation and evaluation with patients, providers, and staff feedback.
A. Fruik: None. L.A. Young: Research Support; Novo Nordisk, Eli Lilly and Company, vTv Therapeutics, Beta Bionics, Inc., Corcept Therapeutics, Rhythm Pharmaceuticals, Inc., Bayer Inc., Jaeb Center for Health Research. K.K. Goeke-Austin: None. L.R. Beezley: None. A. Thomas: None. A. Kahkoska: None.
American Diabetes Association (12-22-ACE-18)
