Mapping the sociotechnical ecosystem of precision medicine

绘制精准医疗的社会技术生态系统

• 批准号: 9892643
• 负责人: Jodyn Elizabeth Platt
• 金额: $ 42.54万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-21 至 2023-09-20
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9892643
• 关键词: Academic Medical Centers; Address; Adopted; Adoption; Arizona; Automobile Driving; Awareness; Back; Basic Science; Big Data; Big Data to Knowledge; Biopsy; California; Caregivers; Caring; Case Manager; Characteristics; Clinic; Clinical Data; Clinical Management; Complex; Contracts; Data; Data Analyses; Data Collection; Decision Making; Development; Diagnostic; Dimensions; Ecosystem; Environment; Evaluation; Evolution; Generations; Genomics; Goals; Health; Health system; Healthcare; Incentives; Individual; Informatics; Infrastructure; Institutional Review Boards; Instruction; Interview; Investigation; Investments; Knowledge; Laboratories; Leadership; Learning; Libraries; Logistics; Malignant Neoplasms; Manufacturer Name; Maps; Measures; Mediation; Medicine; Methods; Michigan; Modeling; Modernization; Molecular; Names; Nurses; Office Visits; Oncologist; Operative Surgical Procedures; Outcome; Patients; Phase; Physiological; Policies; Precision Health; Preparation; Process; Research; Research Personnel; Role; Running; Sampling; Science; Shapes; Site; Speed; Surgeon; System; Systems Analysis; Technology; Testing; Time; Universities; base; chemotherapy; clinical care; comparative; exome; experience; genomic data; health data; health practice; individualized medicine; industry partner; innovation; iterative design; mHealth; meetings; member; oncology program; precision medicine; precision oncology; programs; social; tailored health care; targeted treatment; tumor; whole genome

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.

通过《 21世纪治疗法》和其他 Orien和Apollo等网络的快速增长的数据网络，行业 合作伙伴和研究人员的基因组，生理，诊断，治疗，研究和移动健康数据 数百万个人。精密医学是一种由动态定义的社会技术学习卫生系统 在复杂环境中，人，过程，政策和技术之间的协作关系。在 技术和社会环境相互共同建设的社会技术系统，因此 技术通常是构成医疗保健中复杂系统的关键组成部分，同样重要 是将标准和用法纳入实践的社会承诺。例如，学术医学 中心正在采用精确的医学方法和技术，并根据 他们的目标是提高快速有效的临床管理，研究试验还是 大规模基础研究。本地目标塑造了关于序列的后续选择（整个基因组， 有针对性的面板或整个外显子组），如何顺序（图书馆准备方法，平台，制造商）和 物流（速度，音量）。这些选择反过来对在该领域工作的人们有影响 他们参与的合作过程，遵循的政策以及下游技术发展。 尖端的科学驾驶精确医学需要学习卫生系统的基础设施 多个量表（个人，诊所/实验室，组织和社会）将大数据转换为知识（例如 BD2K），将新知识转移到实践中，并评估随后的健康结果。 近80％的精密医学计划集中于癌症，其中35％ 在学术医疗中心经营。拟议的研究将通过检查 精确肿瘤课程的社会技术生态系统在五个学术医学中心 公立大学启用网络网络，跨系统分析以识别可以是 通过政策或实践解决。拟议的项目将绘制学习的社会技术 通过识别参与者（人，组织），技术，过程， 以及在整个学习周期中运行的政策（数据收集，分析，知识产生， 结果评估）并在多个尺度（个人，组（诊所/实验室），组织和组织和 社会）在全国五个精确的健康实践站点中（AIM 1）。然后，我们将进行迭代设计 开发社会技术成熟度模型以进行精确肿瘤学的过程，适应信息学 描述系统的进步和发展里程碑的方法，包括社会方面 通常被认为与技术分开（AIM 2）。我们的全面方法将成为 无形的角色可见，并阐明了监管现代化和数据信息的治理的机会。