Building a geo-analytic public health dashboard for tracking cancer drug deserts in U.S. counties

Access to life-saving cancer medications remains a significant challenge in many underserved U.S. counties, resulting in the emergence of “cancer drug deserts”—geographic areas with limited availability of essential oncology drugs. This review explores the design, implementation, and policy implications of a geo-analytic public health dashboard aimed at tracking and visualizing these disparities at the county level. By integrating spatial epidemiology, prescription databases, and demographic health indicators, the proposed dashboard leverages geospatial analysis to identify hotspots of pharmaceutical deprivation. The study examines key methodological approaches including spatial autocorrelation metrics (e.g., Moran’s I), hotspot analysis (e.g., Getis-Ord Gi), and multi-indicator access indices to generate actionable insights. A critical analysis of existing dashboards and healthcare GIS platforms is presented to inform best practices in user interface design, data interoperability, and real-time analytics. The review underscores the role of interactive dashboards in supporting evidence-based policy decisions, improving health equity, and guiding resource allocation for oncology care in vulnerable regions. Recommendations for integrating predictive modeling, stakeholder engagement, and national policy frameworks are proposed to enhance the system’s utility and sustainability. Keywords: Building, Geo-Analytic, Public Health, Dashboard, Tracking, Cancer Drug Deserts, U.S. Counties.

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Publication Details

Journal
International Medical Science Research Journal
Published
2024-11-30
DOI
https://doi.org/10.51594/imsrj.v4i11.1932
Citations
10
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
3.87
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article

Building a geo-analytic public health dashboard for tracking cancer drug deserts in U.S. counties

Salvation Ifechukwude Atalor
10 citations
International Medical Science Research Journal
Data-Driven Disease Surveillance
3.87
article

Building a geo-analytic public health dashboard for tracking cancer drug deserts in U.S. counties

Salvation Ifechukwude Atalor
article en
10 citations

Abstract

Access to life-saving cancer medications remains a significant challenge in many underserved U.S. counties, resulting in the emergence of “cancer drug deserts”—geographic areas with limited availability of essential oncology drugs. This review explores the design, implementation, and policy implications of a geo-analytic public health dashboard aimed at tracking and visualizing these disparities at the county level. By integrating spatial epidemiology, prescription databases, and demographic health indicators, the proposed dashboard leverages geospatial analysis to identify hotspots of pharmaceutical deprivation. The study examines key methodological approaches including spatial autocorrelation metrics (e.g., Moran’s I), hotspot analysis (e.g., Getis-Ord Gi), and multi-indicator access indices to generate actionable insights. A critical analysis of existing dashboards and healthcare GIS platforms is presented to inform best practices in user interface design, data interoperability, and real-time analytics. The review underscores the role of interactive dashboards in supporting evidence-based policy decisions, improving health equity, and guiding resource allocation for oncology care in vulnerable regions. Recommendations for integrating predictive modeling, stakeholder engagement, and national policy frameworks are proposed to enhance the system’s utility and sustainability. Keywords: Building, Geo-Analytic, Public Health, Dashboard, Tracking, Cancer Drug Deserts, U.S. Counties.

International Medical Science Research JournalVol. 4(11)
Prairie View A&M University (US)
Openalex Percentile: Top 6%
Data-Driven Disease Surveillance
3.87
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Building a geo-analytic public health dashboard for tracking cancer drug deserts in U.S. counties — Salvation Ifechukwude Atalor · International Medical Science Research Journal (2024) | TGRS Research Map | TGRS