Browsing by Author "Reining, Lauren"

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    Involving patients as key stakeholders in the design of cardiovascular implantable electronic device data dashboards: Implications for patient care
    (Elsevier, 2020-05-11) Daley, Carly; Ghahari, Romisa Rohani; Drouin, Michelle; Ahmed, Ryan; Wagner, Shauna; Reining, Lauren; Coupe, Amanda; Toscos, Tammy; Mirro, Michael; BioHealth Informatics, School of Informatics and Computing
    Background: Data from remote monitoring (RM) of cardiovascular implantable electronic devices (CIEDs) currently are not accessible to patients despite demand. The typical RM report contains multiple pages of data for trained technicians to read and interpret and requires a patient-centered approach to be curated to meet individual user needs. Objective: The purpose of this study was to understand which RM data elements are important to patients and to gain design insights for displaying meaningful data in a digital dashboard. Methods: Adults with implantable cardioverter-defibrillators (ICDs) and pacemakers (PMs) participated in this 2-phase, user-centered design study. Phase 1 included a card-sorting activity to prioritize device data elements. Phase 2 included one-on-one design sessions to gather insights and feedback about a visual display (labels and icons). Results: Twenty-nine adults (mean age 71.8 ± 11.6 years; 51.7% female; 89.7% white) participated. Priority data elements for both ICD and PM groups in phase 1 (n = 19) were related to cardiac episodes, device activity, and impedance values. Recommended replacement time for battery was high priority for the PM group but not the ICD group. Phase 2 (n = 10) revealed that patients would like descriptive, nontechnical terms to depict the data and icons that are intuitive and informative. Conclusion: This user-centered design study demonstrated that patients with ICDs and PMs were able to prioritize specific data from a comprehensive list of data elements that they had never seen before. This work contributes to the goal of sharing RM data with patients in a way that optimizes the RM feature of CIEDs for improving patient outcomes and clinical care.