Accepted for/Published in: Journal of Participatory Medicine
Date Submitted: Nov 5, 2021
Date Accepted: Feb 8, 2022
Date Submitted to PubMed: Feb 8, 2022
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Co-Design of an Electronic Dashboard to Support Coproduction of Care in Pediatric Rheumatic Disease
ABSTRACT
Background:
Coproduction of care involves patients and families partnering with their clinicians and care teams, with the premise that each brings their own perspective, knowledge, and expertise, as well as their own values, goals, and preferences to the partnership. Dashboards can display meaningful patient and clinical data to assess how a patient is doing and inform shared decision making. Increasing communication between patients and care teams is particularly important for children with chronic conditions, such as juvenile idiopathic arthritis (JIA), which is the most common, chronic rheumatic condition of childhood, and is associated with increased pain, decreased function, and decreased quality of life.
Objective:
We aimed to design a dashboard prototype for use in coproducing care for JIA patients. We evaluated the context use and needs of end users, obtained consensus on the necessary dashboard data elements, and constructed display prototypes to inform meaningful discussions for coproduction.
Methods:
A human-centered design approach involving parents, patients, clinicians, and care team members was used to develop a dashboard to support coproduction of care in four diverse ambulatory pediatric rheumatology clinics across the United States. We engaged a multidisciplinary team (n=18) of patients/parents, clinicians, nurses, and staff during an in-person kick-off meeting, followed by bi-weekly meetings. We also leveraged advisory panels. Teams mapped workflows and patient journeys, created personas, and developed dashboard sketches. Final necessary dashboard components were determined using Delphi consensus voting. Low-tech dashboard testing was completed during clinic visits, and visual display prototypes were iterated using PDSA methodology. Patients and providers were surveyed about their experiences.
Results:
Teams achieved consensus on what data matters most at point-of-care to support JIA patients, families, and clinicians partnering together to make the best possible decisions for better health. Notable themes included: the right data, in the right place, at the right time; data in once for multiple purposes; patient and family self-management components; and opportunity for education and increased transparency. A final set of 11 dashboard data elements were identified which include patient-reported outcomes, clinical data, and medications. Important design considerations include incorporation of real-time data, clearly labeled graphs, and vertical orientation to facilitate review and discussion. Prototype paper testing with 36 patients/families yielded positive feedback about the dashboard’s usefulness during clinic discussions, helped to talk about what mattered most, and informed healthcare decision making.
Conclusions:
Our study developed a dashboard prototype that displays patient-reported and clinical data over time, along with medications, that can be used during a clinic visit to support meaningful conversations and shared decision making between JIA patients/families and their clinicians and care teams. Clinical Trial: N/A
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