An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology

Area of Science:

• Genomic research
• Health informatics
• Public health

Background:

• Current tumor registries offer limited longitudinal data, hindering policy development for long-term care and health economics.
• Underrepresented minority (URM) populations face participation gaps in clinical research, exacerbating health and economic disparities.
• Skepticism towards clinical research institutions among URM populations impedes data collection and representation.

Purpose of the Study:

• To explore how emerging technologies can enhance longitudinal patient engagement in clinical research.
• To address participation barriers for underrepresented minority (URM) populations in clinical research.
• To propose an idealized clinical genomic registry model leveraging advanced technologies.

Main Methods:

• Review of current tumor registry limitations and challenges in longitudinal data collection.
• Exploration of cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence (AI) for patient engagement.
• Focus on distributed ledger technologies (blockchain) for enhancing trust and data agency among participants.
• Conceptualization of a clinical genomic registry integrating these technologies.

Main Results:

• Emerging technologies offer potential for enhanced longitudinal patient engagement and data collection across disease trajectories.
• Blockchain technology can foster trust and agency, potentially increasing participation among URM populations.
• Integrating these tools can create robust datasets for AI training and public health initiatives.
• An idealized clinical genomic registry model is presented, outlining parameters for comprehensive data capture.

Conclusions:

• Advanced technologies, particularly blockchain, can overcome limitations of current registries and improve clinical research inclusivity.
• Enhanced patient engagement and data agency are critical for addressing health disparities and improving public health outcomes.
• A well-designed clinical genomic registry utilizing these tools is essential for future AI-driven public health advancements.