Mapping the sociotechnical ecosystem of precision medicine

《21世纪治疗法案》等激励下的对精准医疗的大规模投资 奥里恩和阿波罗等网络的数据网络迅速增长，将医疗系统、工业 合作伙伴和研究人员提供基因组、生理、诊断、治疗、研究和移动健康数据 数以百万计的人。精准医学是一种社会技术学习健康系统，由动态的、 复杂环境中人员、流程、政策和技术之间的协作关系。在……里面 社会技术系统，技术和社会环境相互共同构建，所以当 技术往往是构成医疗保健复杂系统的关键组件，同样重要 是将标准和使用融入实践的社会承诺。例如，学术医学 中心正在采用精准医疗的方法和技术，并根据 他们的目标是提高快速高效的临床管理、研究试验的能力，还是 大规模基础研究。局部目标决定了关于要对什么进行排序的后续选择(整个基因组， 靶向面板或整个外显子)，如何测序(文库制备方法，平台，制造商)，以及 物流(速度、流量)。这些选择反过来又会对在这一领域工作的人产生影响， 他们参与的合作过程、他们遵循的政策以及下游技术开发。 推动精确医学的尖端科学需要学习卫生系统的基础设施 多个规模(个人、诊所/实验室、组织和社会)，将大数据转变为知识(例如 BD2K)，将新知识付诸实践，并评估随后的健康结果。 近80%的精准医疗项目专注于癌症，35%的精准医疗项目 在学术医疗中心运行。拟议的研究将通过检查 五个学术医学中心在精确肿瘤学项目中学习的社会技术生态系统 公立大学支持网络网络、跨系统分析以确定可能存在的差距 通过政策或实践来解决的。拟议的项目将绘制学习的社会技术图谱 通过确定参与者(人员、组织)、技术、流程、 以及在整个学习周期内运行的策略(数据收集、分析、知识生成、 结果评估)和多个级别的功能(个人、团体(诊所/实验室)、组织和 社会)在全国五个精准卫生实践地点(目标1)。然后，我们将进行迭代设计 为精确肿瘤学开发社会技术成熟度模型的过程，适应信息学 描述系统的进展和发展里程碑以包括社会方面的方法 这通常被认为是与技术(目标2)分开的。我们的综合方法将使 这是一种无形的作用，并澄清了监管现代化和数据知情治理的机会。

Large-scale investment in precision medicine incentivized by the 21st Century Cures Act, as well as other rapidly growing data networks of networks such as ORIEN and APOLLO connect health systems, industry partners, and researchers to the genomic, physiologic, diagnostic, treatment, research, and mobile health data of millions of individuals. Precision medicine is a sociotechnical learning health system, defined by dynamic, collaborative relationships between people, processes, policy and technology in complex environments. In sociotechnical systems, both technology and social settings mutually co-construct one another, so while technology is often a critical component of what constitutes a complex system in healthcare, just as important are the social commitments to integrate standards and usage into practice. For example, academic medical centers are adopting precision medicine methods and technologies and are making decisions based on whether their goal is to increase capacity for quick and efficient clinical management, investigational trials, or large-scale basic research. Local goals shape subsequent choices about what to sequence (whole genome, targeted panels, or whole exome), how to sequence (library preparation methods, platform, manufacturer), and logistics (speed, volume). These choices, in turn, have implications for people working in the field, the cooperative processes they engage, the policies they follow, and downstream technological developments. The cutting-edge science driving precision medicine requires infrastructure of learning health systems at multiple scales (individual, clinic/lab, organization, and societal) to transform big data to knowledge (e.g. BD2K), move new knowledge into practice and evaluate subsequent health outcomes. Nearly 80% of precision medicine programs are focused on cancer, with 35% of precision medicine programs being run at academic medical centers. The proposed research will capture this experience by examining the sociotechnical ecosystem of learning in precision oncology programs at five academic medical centers at public universities enabling a network of networks, cross-systems analysis to identify gaps that can be addressed by policies or practices. The proposed project will map the sociotechnical of learning ecosystem for precision oncology by identifying the actors (people, organizations), technologies, processes, and policies that are operating across the learning cycle (data collection, analysis, knowledge generation, outcome evaluation) and functioning at multiple scales (individual, group (clinic/lab), organizational, and societal) in five precision health practice sites nationwide (Aim 1). We will then conduct an iterative design process to develop a sociotechnical maturity model for precision oncology, adapting an informatics approach to describing the progression and developmental milestones of systems to include the social aspects that are often considered separate from the technical (Aim 2). Our comprehensive approach will make invisible roles visible, and clarify opportunities for regulatory modernization and data-informed governance.