Schera Fatima, Schäfer Michael, Bucur Anca, van Leeuwen Jasper, Ngantchjon Eric Herve, Graf Norbert, Kondylakis Haridimos, Koumakis Lefteris, Marias Kostas, Kiefer Stephan
Fraunhofer Institute Biomedical Engineering, 66280 Sulzbach, Germany.
Philips Research, High Tech Campus 34, 5656 AE Eindhoven, The Netherlands.
Ecancermedicalscience. 2018 Jul 11;12:848. doi: 10.3332/ecancer.2018.848. eCollection 2018.
Clinical decision support systems can play a crucial role in healthcare delivery as they promise to improve health outcomes and patient safety, reduce medical errors and costs and contribute to patient satisfaction. Used in an optimal way, they increase the quality of healthcare by proposing the right information and intervention to the right person at the right time in the healthcare delivery process. This paper reports on a specific approach to integrated clinical decision support and patient guidance in the cancer domain as proposed by the H2020 iManageCancer project. This project aims at facilitating efficient self-management and management of cancer according to the latest available clinical knowledge and the local healthcare delivery model, supporting patients and their healthcare providers in making informed decisions on treatment choices and in managing the side effects of their therapy. The iManageCancer platform is a comprehensive platform of interconnected mobile tools to empower cancer patients and to support them in the management of their disease in collaboration with their doctors. The backbone of the iManageCancer platform comprises a personal health record and the central decision support unit (CDSU). The latter offers dedicated services to the end users in combination with the apps iManageMyHealth and iSupportMyPatients. The CDSU itself is composed of the so-called Care Flow Engine (CFE) and the model repository framework (MRF). The CFE executes personalised and workflow oriented formal disease management diagrams (Care Flows). In decision points of such a Care Flow, rules that operate on actual health information of the patient decide on the treatment path that the system follows. Alternatively, the system can also invoke a predictive model of the MRF to proceed with the best treatment path in the diagram. Care Flow diagrams are designed by clinical experts with a specific graphical tool that also deploys these diagrams as executable workflows in the CFE following the Business Process Model and Notation (BPMN) standard. They are exposed as services that patients or their doctors can use in their apps in order to manage certain aspects of the cancer disease like pain, fatigue or the monitoring of chemotherapies at home. The mHealth platform for cancer patients is currently being assessed in clinical pilots in Italy and Germany and in several end-user workshops.
临床决策支持系统在医疗服务中可发挥关键作用,因为它们有望改善健康结果和患者安全,减少医疗差错和成本,并提高患者满意度。以最佳方式使用时,它们通过在医疗服务过程中的正确时间向正确的人提供正确的信息和干预措施,从而提高医疗质量。本文报告了H2020 iManageCancer项目提出的癌症领域综合临床决策支持和患者指导的一种具体方法。该项目旨在根据最新的临床知识和当地医疗服务模式,促进癌症的高效自我管理和管理,支持患者及其医疗服务提供者就治疗选择做出明智决策,并管理其治疗的副作用。iManageCancer平台是一个由相互连接的移动工具组成的综合平台,旨在增强癌症患者的能力,并支持他们与医生合作管理疾病。iManageCancer平台的核心包括个人健康记录和中央决策支持单元(CDSU)。后者与iManageMyHealth和iSupportMyPatients应用程序相结合,为最终用户提供专门服务。CDSU本身由所谓的护理流程引擎(CFE)和模型存储库框架(MRF)组成。CFE执行个性化且面向工作流程的正式疾病管理图(护理流程)。在这样的护理流程的决策点上,根据患者的实际健康信息运行的规则决定系统遵循的治疗路径。或者,系统也可以调用MRF的预测模型,以在图中继续最佳治疗路径。护理流程图由临床专家使用特定的图形工具设计,该工具还根据业务流程模型和符号(BPMN)标准将这些图作为可执行工作流程部署在CFE中。它们作为服务公开,患者或其医生可以在其应用程序中使用这些服务来管理癌症疾病的某些方面,如疼痛、疲劳或在家中监测化疗。用于癌症患者的移动健康平台目前正在意大利和德国的临床试点以及几个最终用户研讨会上进行评估。