{"title":"IA21:将证据转化为行动:Yourdiseaserisk.wustl.edu","authors":"G. Colditz","doi":"10.1158/1538-7755.CARISK16-IA21","DOIUrl":null,"url":null,"abstract":"Not very long ago scientific publication was viewed as the primary dissemination goal of scientific discovery. This viewpoint, however, has evolved substantially over the past 10 - 20 years. While scientific discovery and publication remain key to dissemination of findings, it is now often viewed as a single stage in the spectrum from discovery to the application of research results. The view of effective dissemination must now also include the practical world of policy makers, clinicians, health care organizations, and the public – groups that need good data and good tools to make informed decisions that drive individual, national, and global health. The development of health risk assessment and prevention tools can play a key role in doing this. And such development moves through three general translation stages – with each subsequent stage marked by greater difficulty to achieve. 1) Creation of accurate risk prediction calculation(s) from current evidence base. 2) Development of a practical, usable tool that incorporates the calculation(s) and provides actionable messages – for clinical, public policy, or public use. 3) Integration of risk prediction tools with the social, structural, and financial support for translating recommended action messages into actual action – whether we9re talking about doctors counseling patients, government representatives making health policy, or the public working to improve their own health. This process by necessity requires a multi-disciplinary approach – drawing on expertise from epidemiology, biostatistics, communication theory, coding, and design – among others. With the addition of precision medicine and big data to long-established data analysis techniques, the field of risk prediction is set to expand in coming years. Along with that expansion, it is important to assure that our efforts are valid, useful, reliable, and applicable. Citation Format: Graham A. Colditz. Translating evidence to action: Yourdiseaserisk.wustl.edu. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. 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With the addition of precision medicine and big data to long-established data analysis techniques, the field of risk prediction is set to expand in coming years. Along with that expansion, it is important to assure that our efforts are valid, useful, reliable, and applicable. Citation Format: Graham A. Colditz. Translating evidence to action: Yourdiseaserisk.wustl.edu. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. 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引用次数: 0
摘要
不久以前,科学出版物被视为科学发现的主要传播目标。然而,这种观点在过去的10 - 20年里发生了很大的变化。虽然科学发现和发表仍然是传播发现的关键,但现在往往被视为从发现到研究成果应用这一过程中的一个阶段。有效传播的观点现在还必须包括决策者、临床医生、卫生保健组织和公众的实际世界,这些群体需要良好的数据和良好的工具来做出明智的决定,推动个人、国家和全球健康。制定健康风险评估和预防工具可在这方面发挥关键作用。这种发展经历了三个一般的翻译阶段,每个阶段的难度都更大。1)根据现有证据基础建立准确的风险预测计算。2)开发一种实用的、可用的工具,该工具包含计算并提供可操作的信息-供临床、公共政策或公众使用。3)将风险预测工具与社会、结构和财政支持相结合,将建议的行动信息转化为实际行动——无论是医生为患者提供咨询,政府代表制定卫生政策,还是公众努力改善自己的健康。这一过程必然需要一种多学科的方法——利用流行病学、生物统计学、传播理论、编码和设计等方面的专业知识。随着精准医疗和大数据的加入,长期建立的数据分析技术,风险预测领域将在未来几年扩大。随着这种扩大,重要的是要确保我们的努力是有效的、有用的、可靠的和适用的。引文格式:Graham A. Colditz。将证据转化为行动:Yourdiseaserisk.wustl.edu。[摘要]。摘自:AACR特别会议论文集:改进癌症风险预测以预防和早期发现;2016年11月16日至19日;费城(PA): AACR;Cancer epidemiology Biomarkers pre2017;26(5增刊):摘要/ Abstract
Abstract IA21: Translating evidence to action: Yourdiseaserisk.wustl.edu
Not very long ago scientific publication was viewed as the primary dissemination goal of scientific discovery. This viewpoint, however, has evolved substantially over the past 10 - 20 years. While scientific discovery and publication remain key to dissemination of findings, it is now often viewed as a single stage in the spectrum from discovery to the application of research results. The view of effective dissemination must now also include the practical world of policy makers, clinicians, health care organizations, and the public – groups that need good data and good tools to make informed decisions that drive individual, national, and global health. The development of health risk assessment and prevention tools can play a key role in doing this. And such development moves through three general translation stages – with each subsequent stage marked by greater difficulty to achieve. 1) Creation of accurate risk prediction calculation(s) from current evidence base. 2) Development of a practical, usable tool that incorporates the calculation(s) and provides actionable messages – for clinical, public policy, or public use. 3) Integration of risk prediction tools with the social, structural, and financial support for translating recommended action messages into actual action – whether we9re talking about doctors counseling patients, government representatives making health policy, or the public working to improve their own health. This process by necessity requires a multi-disciplinary approach – drawing on expertise from epidemiology, biostatistics, communication theory, coding, and design – among others. With the addition of precision medicine and big data to long-established data analysis techniques, the field of risk prediction is set to expand in coming years. Along with that expansion, it is important to assure that our efforts are valid, useful, reliable, and applicable. Citation Format: Graham A. Colditz. Translating evidence to action: Yourdiseaserisk.wustl.edu. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA21.