4D PICTURE: Design-based Data-Driven Decision-support Tools: Producing Improved Cancer Outcomes Through User- Centred Research

4D 图片：基于设计的数据驱动决策支持工具：通过以用户为中心的研究改善癌症结果

• 批准号: 10041120
• 金额: $ 105.56万
• 依托单位: LANCASTER UNIVERSITY
• 依托单位国家: 英国
• 项目类别: EU-Funded
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=10041120
• 关键词: 4D; PICTURE; Design; based; Data

Patients with cancer often have to make complex decisions about treatment, with the options varying in risk profiles and effects on survival and quality of life. Data-driven decision-support tools (DSTs) have the potential to empower patients, support personalized care, improve health outcomes, and promote health equity (optimal decisions also for underserved groups). However, DSTs currently seldom consider quality of life or individual preferences, and their use in clinical practice remains limited. To address these challenges, the 4D PICTURE consortium will further develop a promising methodology, MetroMapping, to redesign care paths that include novel DSTs. We will better predict treatment outcomes by developing innovative algorithms and incorporating patient experiences, values and preferences, using AI-based models. In co-creation with patients and other stakeholders, we will develop data-driven DSTs for patients with breast cancer, prostate cancer and melanoma. We will evaluate these DSTs as part of MetroMapping as well as stand-alone, to ensure their sustainability as well as addressing social and ethical issues. We will explore the generalizability of MetroMapping and the DSTs to other types of cancer and across other EU member states. Improved care paths integrating comprehensive DSTs will empower patients, their significant others and health care providers in decision making, and strengthen care at the system level by improving resilience and efficiency. Whereas the 4D PICTURE consortium includes leaders in modelling, AI, decision making, citizen science, service design, ethics, risk communication, and policy making, this project will impact clinical practice and science across Europe and beyond.

癌症患者通常必须就治疗做出复杂的决定，而这些选择的风险特征和对生存和生活质量的影响有所不同。数据驱动的决策支持工具（DSTS）有可能增强患者能力，支持个性化的护理，改善健康成果并促进健康公平（对于服务不足的群体也是最佳决策）。但是，目前，DSTS很少考虑生活质量或个人偏好，并且它们在临床实践中的使用仍然有限。为了应对这些挑战，4D图片联盟将进一步发展有希望的方法论，地铁，重新设计包括新型DST的护理路径。我们将通过开发创新算法并使用基于AI的模型来预测治疗结果，并结合患者的体验，价值和偏好。在与患者和其他利益相关者共同创建中，我们将为乳腺癌，前列腺癌和黑色素瘤患者开发数据驱动的DST。我们将评估这些DST作为地铁和独立的一部分，以确保它们的可持续性以及解决社会和道德问题。我们将探讨地铁和DST对其他类型的癌症以及其他欧盟成员国的普遍性。整合全面DST的改进护理路径将使患者，重要的其他人和医疗保健提供者在决策中赋予能力，并通过提高弹性和效率来加强系统水平的护理。 4D图片联盟包括建模，AI，决策，公民科学，服务设计，道德，风险沟通和政策制定领域的领导者，但该项目将影响欧洲及其他地区的临床实践和科学。