Platt Alyssa, Truong Tracy, Boulos Mary, Carlson Nichole E, Desai Manisha, Elam Monica M, Slade Emily, Hanlon Alexandra L, Hurst Jillian H, Olsen Maren K, Poisson Laila M, Rende Lacey, Pomann Gina-Maria
Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina, USA.
Quantitative Sciences Unit, Department of Medicine, Stanford University School of Medicine, Palo Alto, California, USA.
Stat (Int Stat Inst). 2024 Jun;13(2). doi: 10.1002/sta4.674. Epub 2024 May 8.
Data-intensive research continues to expand with the goal of improving healthcare delivery, clinical decision-making, and patient outcomes. Quantitative scientists, such as biostatisticians, epidemiologists, and informaticists, are tasked with turning data into health knowledge. In academic health centres, quantitative scientists are critical to the missions of biomedical discovery and improvement of health. Many academic health centres have developed centralized Quantitative Science Units which foster dual goals of professional development of quantitative scientists and producing high quality, reproducible domain research. Such units then develop teams of quantitative scientists who can collaborate with researchers. However, existing literature does not provide guidance on how such teams are formed or how to manage and sustain them. Leaders of Quantitative Science Units across six institutions formed a working group to examine common practices and tools that can serve as best practices for Quantitative Science Units that wish to achieve these dual goals through building long-term partnerships with researchers. The results of this working group are presented to provide tools and guidance for Quantitative Science Units challenged with developing, managing, and evaluating Quantitative Science Teams. This guidance aims to help Quantitative Science Units effectively participate in and enhance the research that is conducted throughout the academic health centre-shaping their resources to fit evolving research needs.
数据密集型研究持续扩展，目标是改善医疗服务、临床决策和患者预后。定量科学家，如生物统计学家、流行病学家和信息学家，负责将数据转化为健康知识。在学术健康中心，定量科学家对生物医学发现和健康改善的使命至关重要。许多学术健康中心已设立集中的定量科学部门，这些部门促进定量科学家的专业发展以及开展高质量、可重复的领域研究这两个双重目标。此类部门随后组建能够与研究人员合作的定量科学家团队。然而，现有文献并未就如何组建这样的团队以及如何管理和维持这些团队提供指导。来自六个机构的定量科学部门负责人成立了一个工作组，以研究可作为那些希望通过与研究人员建立长期合作关系来实现这些双重目标的定量科学部门最佳实践的常见做法和工具。现将该工作组的结果呈现出来，为在发展、管理和评估定量科学团队方面面临挑战的定量科学部门提供工具和指导。本指导旨在帮助定量科学部门有效参与并加强在整个学术健康中心开展的研究——调整其资源以适应不断变化的研究需求。
