Clinical Report: A Blockchain-Enhanced Dynamic Consent Model for LDCT Lung Cancer Screening
Overview
This report outlines the development of a blockchain-based dynamic consent framework for Low-Dose Computed Tomography (LDCT) lung cancer screening in Taoyuan, Taiwan. The model aims to enhance participant autonomy, privacy, and ethical data handling while integrating artificial intelligence for improved screening outcomes.
Background
Lung cancer remains a leading cause of cancer mortality globally, with early detection being crucial for improving survival rates. Low-Dose Computed Tomography (LDCT) has shown promise in reducing mortality through early diagnosis, yet challenges such as false positives and data privacy hinder its widespread implementation. A blockchain-enhanced consent model could address these issues by allowing participants to manage their consent preferences securely and transparently.
Data Highlights
The proposed blockchain-based dynamic consent system is currently being piloted with 15,000 participants in the Taoyuan Expanded Lung Cancer Screening Program.
Key Findings
The dynamic consent platform allows real-time modification of consent preferences.
Blockchain hash registration enhances data traceability and security.
AI-assisted risk assessment improves compliance with Taiwan's Personal Data Protection Act.
The framework supports precision health initiatives by integrating biobank data.
Implementation of this model addresses ethical and governance challenges in lung cancer screening.
Clinical Implications
Healthcare providers can leverage this blockchain-based consent model to enhance patient engagement and trust in lung cancer screening programs. By ensuring data privacy and autonomy, clinicians can improve participation rates and the ethical handling of sensitive health information.
Conclusion
The integration of a blockchain-enabled dynamic consent system in LDCT lung cancer screening programs represents a significant advancement in addressing privacy and ethical concerns, ultimately supporting better health outcomes.
