PACS INFRASTRUCTURE TO SUPPORT-BASED MEDICAL PRACTICE

该计划项目赠款的广泛长期目标是开发一个有效的基于成像的信息和医疗保健提供系统，以支持临床实践，研究和教育。赠款的具体目的是：（1）将PACS发展成促进主观患者临床症状客观化的有效基础设施，（2）开发用于通过结构化数据收集、医学报告的自然语言处理（NLP）和医学图像的参数化摘要来改进医学数据的表征的方法，（3）提供灵活的，医学图像、时间线和结构化医学数据的患者特定呈现方法。医学数据的客观化、智能化访问和灵活呈现提供了更好的信息，这将促进循证医学实践，加强研究和评价。五个综合项目采用新的技术来处理系统的具体内容。智能选择的成像协议用于客观化患者症状。定义良好的信息单元捕获和结构化各种形式的数据，无论是直接还是间接通过NP用于文本还是图像的参数摘要。患者病历与医学文献的内容相关。时间轴将数据组织成一种格式，使医疗事件、其依赖关系和条件趋势易于可视化（项目3）。基于场景的代理提供对相关医疗信息的最新访问。软件工具包和用户模型支持针对特定用户、特定领域和特定任务的定制。独立于硬件的架构将便于跨不同平台和软件子系统访问系统。它们共同构成了一个独特的基础设施，提供了对定义明确的结构化数据和最新文献的广泛和智能定制的访问。除了患者特定的相关数据，专家意见和已知结果的类似病例外，这将促进循证医学实践。五个综合项目采用新的技术来处理系统的具体内容。智能秘密成像协议用于客观化患者症状。定义良好的信息单元可以捕获和构建各种形式的数据，无论是直接还是间接通过NLP（文本）还是参数化摘要（图像）。患者病历与医学文献的内容相关。时间轴将数据组织成一种格式，使医疗事件、其依赖关系和条件趋势易于可视化（项目3）。基于场景的代理提供对相关医疗信息的最新访问。软件工具包和用户模型支持针对特定用户、特定领域和特定任务的定制。独立于硬件的架构将便于跨不同平台和软件子系统访问系统。它们共同构成了一个独特的基础设施，提供了对定义明确的结构化数据和最新文献的广泛和智能定制的访问。除了患者特定的相关数据，专家意见和已知结果的类似病例外，这将促进循证医学实践。对拟议系统影响的评价将侧重于技术措施、护理过程以及患者和医生的满意度。评价还将探讨过程变化与具体结果之间的关系，特别是与短期健康有关的生活质量。虽然没有提出正式的成本效益研究，但当这些PAC技术成熟时，为这些测量奠定了基础。这些测量将通过记录资源利用、确定基于成像的护理事件以及与主诉相关的计数器特定信息来促进。

The broad, tong-term objective of this Program Project Grant is to develop an effective imaging-based information and health care delivery system to support clinical practice, research, and education. The specific aims of the grant are to: (1) evolve PACS into an effective infrastructure that promotes the objectification of subjective patient clinical symptoms, (2) develop methods for improving the characterization of medical data through structured data collection, natural language processing of medical reports (NLP) and parametric summarization for medical images, (3) provide flexible, patient -specific presentation methods of medical images, timelines, and structured medical data. The objectification, intelligent access, and flexible presentation of medical data provide better information, which will facilitate the evidence-based practice of medicine and enhance research and evaluation. Five integrated projects employ novel techniques to address specific elements of the system. Intelligently selected imaging protocols are used to objectify patient symptoms. Well-defined information units capture and structure diverse forms of data, whether directly or indirectly through NP for text of parametric summarization for images. Patient medical records are correlated with medical literature by content. Timelines organize the data into a format that allow medical events, their dependencies, and conditional trends to be easily visualized (Project 3). Scenario-based proxies provide up-to-date access to relevant medical information. Relaxation broadens queries to medical information when exact matches are not found. Software toolkits and user models enable user-, and domain-, and task-specific customizations. The hardware independent architecture will facilitate access to the system across different platforms and software subsystems. Together, they form a unique infrastructure that provides broad and intelligently customized access to well-defined structured data and up-to-date literature. This, in addition to patient-specific relevant data, expert opinion, and similar cases with known outcome, will promote the evidence-based practice of medicine. Five integrated projects employ novel techniques to address specific elements of the system. Intelligently secreted imaging protocols are used to objectify patient symptoms. Well-defined information units capture and structure diverse forms of data, whether directly or indirectly through NLP for text or parametric summarization for images. Patient medical records are correlated with medical literature by content. Timelines organize the data into a format that allow medical events, their dependencies, and conditional trends to be easily visualized (Project 3). Scenario-based proxies provide up-to-date access to relevant medical information. Relaxation broadens queries to medical information when exact matches are not found. Software toolkits and user models enable user-, and domain-, and task-specific customizations. The hardware independent architecture will facilitate access to the system across different platforms and software subsystems. Together, they form a unique infrastructure that provides broad and intelligently customized access to well-defined structured data and up-to-date literature. This, in addition to patient-specific relevant data, expert opinion, and similar cases with known outcome, will promote the evidence-based practice of medicine. Evaluation of the impact of the proposed system will focus on technical measures; process of care; and patient and physician satisfaction. The evaluation will also explore the relationship between process changes and specific outcomes, particularly short-term health related quality of life. Although a formal cost-effectiveness study is not proposed, the foundation is laid for these measurements when these PACs technologies mature. These measurements will be facilitated by recording resource utilization, determining of imaging-based episodes of care, and counter- specific information related to a chief complaint.