Healtex: UK Healthcare Text Analytics Research Network

医疗保健是“大数据科学”的一个主要例子，在这些挑战和成功案例中，从数据中提取的可操作信息改善并拯救了生命[1]。大多数的协调努力集中在实时处理和集成来自临床编码、诊断测试、传感器测量、问卷等的结构化数据流，以支持及时的临床干预和促进患者的自我管理。尽管如此，自然语言仍然是医疗保健内部沟通的主要手段，其书面记录越来越多地以电子形式提供，从而产生了大文本数据。突出的例子包括电子健康记录中嵌入的文本数据(例如转介信、病例说明、病理报告、出院摘要等)、患者报告的结果衡量标准(例如问卷、日记等)。或在Web2.0上公开分享的未经请求的非正式反馈(例如，社交媒体、论坛等)。不幸的是，大规模有效利用非结构化文本数据信息的能力落后于结构化文本数据。医疗保健中的大多数可操作信息都包含在文本数据中(一些估计显示高达85%)，这一事实清楚地表明，通过实时处理和集成此类信息的能力，有可能极大地改变社区卫生保健和护理。然而，由于各种医疗保健亚语言的动态性、特殊性、模糊性和变异性，对它们的自动化和大规模“理解”在很大程度上仍然是一个尚未解决的研究挑战。该提议的目的是建立一个覆盖英国的多学科研究网络，以探索有效利用医疗保健叙事性文本数据、路线图研究努力以及在学术界、NHS和产业界之间共享文本数据和文本分析方法的原则所面临的障碍。该网络将通过支持将医疗叙事部署为实时传感器并将其与结构化数据流集成到以患者为中心的协作生态系统中的研究，直接应对“转变社区健康和护理”的重大挑战，该生态系统将涉及医疗专业人员、患者、护理人员和研究人员。这种系统的医疗保健活动网络将促进知情的决策、及时的干预、更深入的临床流行病学数字表型分析和基于人口的建模。另一方面，通过处理患者生成的叙述，这通常是提供患者回复(例如短信)的首选和可能的手段，以补充结构化的医疗数据(例如来自可穿戴设备的信号)，我们将“使用实时信息来支持健康和福祉的自我管理”。该网络的主要成果将是一个强大、可持续的社区，在最初的3年支持后将继续其使命。其他成果将包括：(1)描述在利用文本叙述和理解它们方面的最新进展和关键障碍的挑战的报告；(2)医疗保健文本分析的研究路线图；(3)扩大成员和扩大网络内的合作，特别是与早期职业研究人员和国际合作；(4)一系列有重点的试点/可行性项目，将为进一步的发展提供信息并启动合作项目；(5)在会议和期刊上收集研究论文，提高英国在这一不断增长的领域的竞争力；(6)在项目期间提出几个项目提案，并准备提交；(7)跨学科个人奖学金的建议，以及(8)医疗保健文本分析专业知识、资源和工具的交互式注册，以便用户和合作者可以确定现有资源并启动新的协作。

Healthcare is a prime example of "big data science" with a number of challenges and successful stories where actionable information extracted from data has improved and saved lives [1]. The majority of concerted efforts focused on real-time processing and integration of structured data streams coming from clinical coding, diagnostic tests, sensor measurements, questionnaires, etc. to support timely clinical interventions and facilitate patients' self-management. Nonetheless, natural language remains the main means of communication within healthcare with its written accounts becoming increasingly available in an electronic form, thus giving rise to big text data. Prominent examples include text data embedded within electronic health records (e.g. referral letters, case notes, pathology reports, hospital discharge summaries, etc.), patient-reported outcome measures (e.g. questionnaires, diaries, etc.) or unsolicited informal feedback shared openly on the Web 2.0 (e.g. social media, fora, etc.). Unfortunately, the capacity to effectively utilise information from unstructured text data on a big scale is lagging behind its structured counterpart. The fact that the majority of actionable information in healthcare is contained within text data (some estimates shows as much as 85%) clearly indicates a potential to dramatically transform community health and care by the ability to process and integrate such information in real time. However, automated and large-scale "understanding" of diverse healthcare sublanguages is still largely unsolved research challenge due to their dynamics, idiosyncrasy, ambiguity and variability.The aim of this proposal is to build a UK-wide multi-disciplinary research network in order to explore the barriers to effectively utilising healthcare narrative text data, road-map research efforts and principles for sharing text data and text analytics methods between academia, NHS and industry. The network will directly address the "Transforming Community Health and Care" grand challenge by enabling research that will deploy healthcare narratives as real-time sensors and integrate them with the structured data streams into a patient-focused collaborative ecosystem, which will involve healthcare professionals, patients, carers and researchers. Such systemic network of healthcare activities will facilitate informed decision making, timely interventions, deeper digital phenotyping for clinical epidemiology and population-based modelling. On the other hand, by processing patient-generated narratives, which are often a preferred and likely means to provide patient responses (e.g. text messages) to complement structured healthcare data (e.g. signals from wearable devices), we will "use real-time information to support self-management of health and wellbeing".The main outcome of the network will be a strong, sustainable community that will continue its mission after the initial 3 years of support. Other outcomes will include (1) reports describing the state-of-the-art and challenges for key barriers in harnessing text narratives and making sense from them; (2) a research roadmap for healthcare text analytics; (3) an enlarged membership and expanded collaborations within the network, in particular with early career researchers and internationally; (4) a series of focused pilot/feasibility projects that will inform further developments and kick-start collaborative projects; (5) a collection of research papers at conferences and journals, improving the UK competitiveness in this growing area; (6) several project proposals scoped during the project and prepared for submission; (7) proposals for discipline-bridging personal fellowships, and (8) an interactive registry of healthcare text analytics expertise, resources and tools so that the users and collaborators can identify existing resources and initiate new collaboration.