Interactive visualization tool to understand and monitor health disparities in diabetes care and outcomes

Jashalynn C German; Andrew Stirling; Patti Gorgone; Amanda R Brucker; Angel Huang; Shwetha Dash; David J Halpern; Nrupen A Bhavsar; Eugenia R McPeek Hinz; Richard P Shannon; Susan E Spratt; Benjamin A Goldstein

doi:10.1017/cts.2024.542

Interactive visualization tool to understand and monitor health disparities in diabetes care and outcomes

J Clin Transl Sci. 2024 May 17;8(1):e102. doi: 10.1017/cts.2024.542. eCollection 2024.

Authors

Jashalynn C German¹, Andrew Stirling², Patti Gorgone², Amanda R Brucker³, Angel Huang³, Shwetha Dash², David J Halpern^{4

5}, Nrupen A Bhavsar^{3

4}, Eugenia R McPeek Hinz^{2

6}, Richard P Shannon^{6

7}, Susan E Spratt^{1

8}, Benjamin A Goldstein³

Affiliations

¹ Department of Medicine, Division of Endocrinology, Metabolism, and Nutrition, Duke University School of Medicine, Durham, NC, USA.
² Duke Health Technology Solutions, Duke University Health System, Durham, NC, USA.
³ Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
⁴ Department of Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, NC, USA.
⁵ Duke Primary Care, Duke University Medical Center, Durham, NC, USA.
⁶ Duke University Health System, Durham, NC, USA.
⁷ Department of Medicine, Division of Cardiology, Duke University School of Medicine, Durham, NC, USA.
⁸ Duke Population Health Management Office, Duke Health System, Durham, NC, USA.

Abstract

Objective: Type 2 diabetes (T2DM) poses a significant public health challenge, with pronounced disparities in control and outcomes. Social determinants of health (SDoH) significantly contribute to these disparities, affecting healthcare access, neighborhood environments, and social context. We discuss the design, development, and use of an innovative web-based application integrating real-world data (electronic health record and geospatial files), to enhance comprehension of the impact of SDoH on T2 DM health disparities.

Methods: We identified a patient cohort with diabetes from the institutional Diabetes Registry (N = 67,699) within the Duke University Health System. Patient-level information (demographics, comorbidities, service utilization, laboratory results, and medications) was extracted to Tableau. Neighborhood-level socioeconomic status was assessed via the Area Deprivation Index (ADI), and geospatial files incorporated additional data related to points of interest (i.e., parks/green space). Interactive Tableau dashboards were developed to understand risk and contextual factors affecting diabetes management at the individual, group, neighborhood, and population levels.

Results: The Tableau-powered digital health tool offers dynamic visualizations, identifying T2DM-related disparities. The dashboard allows for the exploration of contextual factors affecting diabetes management (e.g., food insecurity, built environment) and possesses capabilities to generate targeted patient lists for personalized diabetes care planning.

Conclusion: As part of a broader health equity initiative, this application meets the needs of a diverse range of users. The interactive dashboard, incorporating clinical, sociodemographic, and environmental factors, enhances understanding at various levels and facilitates targeted interventions to address disparities in diabetes care and outcomes. Ultimately, this transformative approach aims to manage SDoH and improve patient care.

Keywords: Health disparities; real-world data; social determinants of health; type 2 diabetes; visualization.