A GIS software-based method to identify public health data belonging to address-defined communities

Area of Science:

• Public Health Informatics
• Geographic Information Systems (GIS)
• Epidemiology

Background:

• Accurate definition of tribal health jurisdictions is crucial for equitable public health data access.
• Traditional methods relying solely on tribal affiliation (TA) may undercount cases and vaccination records within tribal communities.

Purpose of the Study:

• To present a novel methodology for defining tribal health jurisdictions by combining tribal affiliation and patient address data.
• To evaluate the effectiveness of this combined approach in identifying tribal populations within public health datasets.

Main Methods:

• Utilized Geographic Information System (GIS) software and custom code in a county-tribal partnership.
• Extracted tribal data from county COVID-19 case and vaccination records by identifying reservation addresses.
• Analyzed COVID-19 case records (Dec 2019–Dec 2022) and vaccination records (Dec 2020–Apr 2023).

Main Results:

• The combined method identified 1.91 times more COVID-19 case records compared to using tribal affiliation alone.
• The methodology identified 3.76 times more COVID-19 vaccination records than tribal affiliation alone.
• Demonstrated a substantial increase in identified records for tribal populations.

Conclusions:

• Combining patient address data with tribal affiliation and enrollment enhances the definition of tribal health jurisdictions.
• This approach facilitates equitable access to public health data for tribal health organizations through data sharing agreements.
• The methodology holds potential for improving data representation for other underrepresented populations in research.