Co-operative Models for Evidence-based Healthcare Redistribution (CoMEHeRe)

循证医疗保健再分配合作模式 (CoMEHeRe)

• 批准号: EP/P03196X/1
• 负责人: Alan Brown
• 金额: $ 53.52万
• 依托单位: University of Surrey
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2017
• 资助国家: 英国
• 起止时间: 2017 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FP03196X%2F1
• 关键词: Co; operative; Models; Evidence; based

CoMEHeRe aims to transform personal healthcare for the benefit of individuals through the use and management of biometric information created by wearable devices.To do this it will combine data from an individual's wearables with DLT (blockchains) and machine learning to securely store and access data to enable the individual to share and benefit from their generated information. Sharing will be with state and private healthcare providers to enable more targeted, personalised patterns of treatment. Other benefits may arise from the individual participating materially in new markets created through the monetisation of this data. Recent interest in cryptocurrencies such as Bitcoin has ignited interest in DLTs and the role they play in how shared agreements are defined, managed, and evolved for a variety of ecosystems and information sources typical of today's digital economy. Indeed, the focus of attention has shifted from DLT as a technological phenomena supporting new types of currency e.g., bitcoin to their likely impact in changing business and society. DLTs have the potential for rewriting conventional notions of how business transactions relate with customers, enhance transparency and trust, and create fresh opportunities for value creation and capture. In domains such as healthcare, the potential of DLTs to disrupt the status quo is clear. However, a critical research need must be addressed: how to expose the opportunities and threats, such as privacy and security from emerging business models enabled by this technological revolution.CoMEHeRe aspires to build and assess the feasibility of the first publicly available software demonstrator to interface with insurers (AXA/PPP and its Seed Factory labs will be a partner) and the general public, using distributed ledger technologies to allow for data to be curated, hosted, and used as tradeable value by the individual's' choice. To achieve this CoMEHeRe will address a number of research challenges by utilising a novel combination of technologies, including the blockchain - a form of secure DLT - to store health evidence derived from multi-modal signals extracted from users' wearables and the Internet of Things (IoT) sensors they interact with in the environment. In addition, the project will examine the potential use of Smart Contracts (simple programs) in healthcare management at the research, public policy, and individual levels. Such a use will be challenged by many kinds of contractual, ethical and moral issues: for example if ownership is taken away from the individual, smart contracts could be made partially or fully self-executing, self-enforcing, or both, by authorities or businesses seeking to optimise for cost instead of health benefit to the individual. The CoMEHeRe project is an 18 month research project designed to create value in an innovative application domain for DLT in healthcare. To undertake this exciting, ambitious project we build on a strategic multi-disciplinary partnership at the University of Surrey that unites world-leading research groups focused on examining the business and societal impact of applications of digital technology (CoDE), multi-modal signal processing (CVSSP), and IoT and sensor-based communications infrastructures (ICS and 5GIC). This partnership is contained within a broader delivery consortium. This includes Axa/PPP offering the application context and a basis for assessing practical impact, Guardtime providing a DLT foundation for the research work, and BioBeats delivering machine learning platform expertise. To govern this work there will be an experienced Advisory Board bringing governance and guidance to ensure the project delivers meaningful results from which new research and practice can emerge. This experienced partnership has a practical record of previous work in these areas, and a broad network of relationships bringing deep support, and rapid promotion of research results.

CoMEHeRe旨在通过使用和管理可穿戴设备创建的生物识别信息来改变个人医疗保健，以造福个人。为此，它将联合收割机与DLT（区块链）和机器学习结合起来，以安全地存储和访问数据，使个人能够分享并受益于其生成的信息。将与国家和私人医疗保健提供者共享，以实现更有针对性的个性化治疗模式。其他好处可能来自个人实质性地参与通过这些数据的货币化而创造的新市场。最近对比特币等加密货币的兴趣引发了人们对DLT的兴趣，以及它们在如何为当今数字经济典型的各种生态系统和信息源定义、管理和发展共享协议方面所发挥的作用。事实上，注意力的焦点已经从DLT转移到支持新型货币的技术现象，例如，比特币对改变商业和社会可能产生的影响。DLT有可能改写商业交易如何与客户联系的传统概念，增强透明度和信任，并为价值创造和捕获创造新的机会。在医疗保健等领域，DLT颠覆现状的潜力是显而易见的。然而，必须解决一个关键的研究需求：如何暴露机会和威胁，例如由这场技术革命带来的新兴商业模式的隐私和安全。CoMEHeRe渴望建立和评估第一个公开可用的软件演示器与保险公司接口的可行性（AXA/PPP及其种子工厂实验室将成为合作伙伴）和公众，使用分布式账本技术来管理，托管数据，并由个人选择作为可交易价值使用。 为了实现这一目标，CoMEHeRe将通过利用一种新的技术组合来解决一些研究挑战，包括区块链-一种安全DLT的形式-来存储从用户可穿戴设备和物联网（IoT）传感器中提取的多模态信号中获得的健康证据。此外，该项目还将研究智能合约（简单程序）在研究、公共政策和个人层面的医疗保健管理中的潜在用途。这种使用将受到许多合同、伦理和道德问题的挑战：例如，如果所有权从个人手中被剥夺，智能合约可以部分或完全自动执行、自动执行或两者兼而有之，由寻求优化成本而不是个人健康利益的当局或企业来实现。 CoMEHeRe项目是一个为期18个月的研究项目，旨在为DLT在医疗保健领域的创新应用领域创造价值。为了开展这个令人兴奋的雄心勃勃的项目，我们建立在萨里大学的战略多学科合作伙伴关系的基础上，该合作伙伴关系联合了世界领先的研究小组，专注于研究数字技术（CodeE），多模态信号处理（CVSSP），物联网和基于传感器的通信基础设施（ICS和5GIC）应用的商业和社会影响。这一伙伴关系包含在一个更广泛的交付财团中。这包括Axa/PPP提供应用环境和评估实际影响的基础，Guardtime为研究工作提供DLT基础，BioBeats提供机器学习平台专业知识。为了管理这项工作，将有一个经验丰富的咨询委员会带来治理和指导，以确保项目提供有意义的结果，从中可以出现新的研究和实践。这种经验丰富的合作伙伴关系在这些领域有着实际的工作记录，以及广泛的关系网络，带来了深入的支持，并迅速推广研究成果。

项目成果

Euro-Par 2018: Parallel Processing Workshops - Euro-Par 2018 International Workshops, Turin, Italy, August 27-28, 2018, Revised Selected Papers

Euro-Par 2018：并行处理研讨会 - Euro-Par 2018 国际研讨会，意大利都灵，2018 年 8 月 27-28 日，修订后的精选论文

• DOI: 10.1007/978-3-030-10549-5_46
• 发表时间: 2019
• 作者: Franceschi M

Deep learning with wearable based heart rate variability for prediction of mental and general health

• DOI: 10.1016/j.jbi.2020.103610
• 发表时间: 2020-12-01
• 期刊: JOURNAL OF BIOMEDICAL INFORMATICS
• 影响因子: 4.5
• 作者: Coutts, Louise V.;Plans, David;Collomosse, John
• 通讯作者: Collomosse, John

Use of a Biofeedback Breathing App to Augment Poststress Physiological Recovery: Randomized Pilot Study.

使用生物反馈呼吸应用程序增强应激后生理恢复：随机试点研究。

• DOI: 10.2196/12227
• 发表时间: 2019
• 期刊: JMIR formative research
• 影响因子: 2.2
• 作者: Plans D

Delivering Digital Transformation: A Manager's Guide to the Digital Revolution

实现数字化转型：数字革命管理者指南

• 发表时间: 2019
• 作者: Brown Alan W.

Developing opportunities in digital health: The case of BioBeats Ltd

• DOI: 10.1016/j.jbvi.2019.e00110
• 发表时间: 2019-06
• 期刊: Journal of Business Venturing Insights
• 作者: David López;Alan W. Brown;D. Plans