Silva Patrick, Dahlke Deborah Vollmer, Smith Matthew Lee, Charles Wendy, Gomez Jorge, Ory Marcia G, Ramos Kenneth S
Health Science Center, Texas A&M University, 8441 Riverside Pkwy, Bryan, TX 77807, USA.
School of Public Health, Texas A&M Health Science Center, 212 Adriance Lab Rd., College Station, TX 77843, USA.
J Pers Med. 2022 Apr 29;12(5):713. doi: 10.3390/jpm12050713.
Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes. These challenges are amplified for underrepresented minority (URM) and other disadvantaged populations, who tend to view the institution of clinical research with skepticism. Participation gaps leave such populations underrepresented in clinical research and, importantly, in policy decisions about treatment choices and reimbursement, thus further augmenting health, social, and economic disparities. Cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence technologies are powerful tools that promise to enhance longitudinal patient engagement across the natural history of disease. These tools also promise to enhance engagement by giving participants agency over their data and addressing a major impediment to research participation. This will only occur if these tools are available for use with all patients. Distributed ledger technologies (specifically blockchain) converge these tools and offer a significant element of trust that can be used to engage URM populations more substantively in clinical research. This is a crucial step toward linking composite cohorts for training and optimization of the artificial intelligence tools for enhancing public health in the future. The parameters of an idealized clinical genomic registry are presented.
肿瘤登记处的当前最佳实践提供了对疾病自然史有限时间段的一瞥，通常是围绕诊断和活检的一个狭窄窗口。这给满足公共卫生和医疗保健报销政策带来了挑战，这些政策越来越需要对长期临床轨迹、生活质量和健康经济学结果进行有力记录。对于代表性不足的少数群体（URM）和其他弱势群体来说，这些挑战更加突出，他们往往对临床研究机构持怀疑态度。参与差距使得这些人群在临床研究中，以及在关于治疗选择和报销的政策决策中代表性不足，从而进一步加剧了健康、社会和经济差距。云计算、移动计算、数字账本、代币化和人工智能技术是强大的工具，有望在疾病自然史中增强患者的长期参与度。这些工具还承诺通过赋予参与者对其数据的控制权并解决研究参与的一个主要障碍来提高参与度。只有当这些工具可供所有患者使用时，这一点才会实现。分布式账本技术（特别是区块链）融合了这些工具，并提供了一个重要的信任元素，可用于使URM人群更实质性地参与临床研究。这是朝着将复合队列联系起来以训练和优化人工智能工具以在未来增强公共卫生迈出的关键一步。本文介绍了理想化临床基因组登记处的参数。
