Machine Evaluation of Catchment Area Relevance through Text Mining

Area of Science:

• Oncology
• Health Services Research
• Clinical Trial Management

Background:

• South Florida is a highly diverse region with significant cancer burden and disparities.
• The University of Miami Sylvester Comprehensive Cancer Center serves this complex population.
• There is a need to align clinical trials with the specific health needs of the local community.

Purpose of the Study:

• To develop a tool for identifying cancer clinical trials relevant to Sylvester Comprehensive Cancer Center's catchment area.
• To prioritize trials that address prevalent cancers and health disparities in South Florida.
• To improve access to locally relevant cancer research for diverse patient populations.

Main Methods:

• Development of a specialized algorithm by the Community Outreach and Engagement Office.
• Focus on South Florida as the catchment area, recognizing its demographic and geographic diversity.
• Prioritization strategy based on local tumor burden and cancer prevalence.

Main Results:

• An algorithm designed to identify relevant clinical trials has been successfully developed.
• The tool facilitates the targeting of trials for cancers that are locally prevalent in South Florida.
• This approach aids in addressing the specific needs of the population served by Sylvester Comprehensive Cancer Center.

Conclusions:

• The developed algorithm is a key resource for aligning cancer clinical trials with community needs in diverse regions.
• Prioritizing locally relevant trials is crucial for addressing significant cancer burden and disparities.
• This initiative enhances the center's ability to serve its catchment area effectively through targeted research.