1033-P: An Interactive Capacity Planning Dashboard for Algorithm-Enabled Telemedicine-Based Diabetes Care

We previously showed that the use of a tool for remote analysis of continuous glucose monitor data, Timely Interventions for Diabetes Excellence (TIDE) , was associated with improved glucose management for patients with type 1 diabetes. To facilitate the deployment of TIDE at two partner institution...

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Veröffentlicht in:Diabetes (New York, N.Y.) N.Y.), 2022-06, Vol.71 (Supplement_1)
Hauptverfasser: CHANG, ANNETTE, GAO, MICHAEL Z., FERSTAD, JOHANNES, MAAHS, DAVID M., PRAHALAD, PRIYA, JOHARI, RAMESH, SCHEINKER, DAVID
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Sprache:eng
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Zusammenfassung:We previously showed that the use of a tool for remote analysis of continuous glucose monitor data, Timely Interventions for Diabetes Excellence (TIDE) , was associated with improved glucose management for patients with type 1 diabetes. To facilitate the deployment of TIDE at two partner institutions, we developed an operational planning tool. We designed an interactive dashboard to match capacity and demand with a variety of operational, population, and workforce parameters. To improve the dashboard’s accessibility, simplicity, and interpretability, we performed iterative design based on feedback from users and two partner institutions. We set parameter values based on the first deployment of TIDE and conducted sensitivity analyses of the capacity-demand match. The dashboard (Figure 1) contains seven modifiable parameters; generates a table illustrating the match between capacity and demand; displays a timeseries plot of capacity and demand; and calculates three alternative capacity plans that satisfy annual patient demand. It is available online (www.bit.ly/surf-tide) . Small absolute reductions in per-patient review time produced the most significant changes in clinic capacity. We developed an interactive dashboard that facilitates data-driven operational planning for clinics seeking to deploy algorithm-enabled telemedicine-based diabetes care. Figure 1. Capacity Planning Dashboard
ISSN:0012-1797
1939-327X
DOI:10.2337/db22-1033-P