University of Toronto, Genomics Health Services Research Program, St. Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
All of Us Research Program, National Institutes of Health, Bethesda, MD 20892, USA.
Am J Hum Genet. 2022 Jul 7;109(7):1190-1198. doi: 10.1016/j.ajhg.2022.05.001.
Digital health solutions, with apps, virtual care, and electronic medical records, are gaining momentum across all medical disciplines, and their adoption has been accelerated, in part, by the COVID-19 pandemic. Personal wearables, sensors, and mobile technologies are increasingly being used to identify health risks and assist in diagnosis, treatment, and monitoring of health and disease. Genomics is a vanguard of digital healthcare as we witness a convergence of the fields of genomic and digital medicine. Spurred by the acute need to increase health literacy, empower patients' preference-sensitive decisions, or integrate vast amounts of complex genomic data into the clinical workflow, there has been an emergence of digital support tools in genomics-enabled care. We present three use cases that demonstrate the application of these converging technologies: digital genomics decision support tools, conversational chatbots to scale the genetic counseling process, and the digital delivery of comprehensive genetic services. These digital solutions are important to facilitate patient-centered care delivery, improve patient outcomes, and increase healthcare efficiencies in genomic medicine. Yet the development of these innovative digital genomic technologies also reveals strategic challenges that need to be addressed before genomic digital health can be broadly adopted. Alongside key evidentiary gaps in clinical and cost-effectiveness, there is a paucity of clinical guidelines, policy, and regulatory frameworks that incorporate digital health. We propose a research agenda, guided by learning healthcare systems, to realize the vision of digital health-enabled genomics to ensure its sustainable and equitable deployment in clinical care.
数字健康解决方案，包括应用程序、虚拟护理和电子病历，正在所有医学学科中迅速普及，部分原因是 COVID-19 大流行加速了它们的采用。个人可穿戴设备、传感器和移动技术越来越多地被用于识别健康风险，并协助诊断、治疗和监测健康和疾病。基因组学是数字医疗的先锋，因为我们见证了基因组学和数字医学领域的融合。由于迫切需要提高健康素养、增强患者偏好敏感决策的能力，或将大量复杂的基因组数据整合到临床工作流程中，基因组学支持护理领域出现了数字支持工具。我们提出了三个用例，展示了这些融合技术的应用：数字基因组决策支持工具、用于扩展遗传咨询过程的对话式聊天机器人，以及综合遗传服务的数字交付。这些数字解决方案对于促进以患者为中心的护理提供、改善患者结果和提高基因组医学中的医疗效率非常重要。然而，这些创新的数字基因组技术的发展也揭示了一些战略挑战，这些挑战需要在基因组数字健康得到广泛采用之前得到解决。除了临床和成本效益方面的关键证据空白外，数字健康的临床指南、政策和监管框架也很少。我们提出了一个研究议程，以学习型医疗系统为指导，实现数字健康支持基因组学的愿景，以确保其在临床护理中的可持续和公平部署。
