Automatic Acquisition of Knowledge for Senior Care Planning

自动获取老年护理规划知识

• 批准号: 7999587
• 负责人: Eric Christopher Tinsley
• 金额: $ 13.91万
• 依托单位: MY HEALTH CARE
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2011-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7999587
• 关键词: Algorithms; Assisted Living Facilities; Belief; Breeding; Caregivers; Caring; Case Manager; Categories; Collaborations; Comprehensive Health Care; Data; Decision Modeling; Decision Support Systems; Development; Dictionary; Effectiveness; Elderly; Exclusion; Face; Family; Goals; Growth; Health; Health system; Healthcare; Independent Living; Indiana; Informatics; Instruction; Intervention; Knowledge; Knowledge Extraction; Knowledge acquisition; Learning; Libraries; Life; Literature; Management Decision Support Systems; Manuals; Marketing; Measures; Methodology; Methods; Metric; Natural Language Processing; Nature; Navigation System; Ontology; Performance; Phase; Population; Probability; Problem Solving; Process; Productivity; Publishing; Quality of life; Readiness; Registered nurse; Research; Review Literature; Sales; Sampling; Schools; Screening procedure; Services; Side; Small Business Innovation Research Grant; Social Workers; Solutions; Speech; System; Techniques; Technology; Testing; Time; Training; Universities; Update; Work; commercial application; commercialization; cost; data mining; design; falls; improved; innovative technologies; knowledge base; meetings; member; network models; phase 2 study; public health relevance; research and development; scale up; software development; success; text searching; tool

DESCRIPTION (provided by applicant): Dramatic growth of the senior population in the U.S. is widely expected to challenge the capacity of this segment of the U.S. health system. Alternative strategies to support seniors living independently will be critical in meeting the short fall. My Health Care Manager (MHCM) has developed the Senior Care Navigation System (SCANSTM) to provide decision support to Geriatric Care Managers (GCMs), registered nurses and social workers, in the construction of consumer-side care plans for seniors and their caregivers. SCANSTM provides interventions and practical, real-world tools to extend the healthy and active years of life and assist families with critical decisions. Automatic acquisition of knowledge will help to augment MHCM's research staff in order to keep the SCANSTM knowledge base up to date for providing effective and efficient senior care plans. The overall goal for this Fast-Track SBIR research will be for MHCM in collaboration with the Indiana University's School of Informatics to develop an automated knowledge acquisition system that will acquire knowledge from health literature pertinent to senior care. This knowledge in the form of "best practices" will be used as part of the SCANSTM decision support system. The automatic acquisition of knowledge will greatly increase the overall productivity of the SCANS Research Team. The improvements in quality, timeliness, breadth, depth, and volume of research will be a marketable feature of the SCANSTM product. During Phase I, MHCM will validate the feasibility of automatically acquiring knowledge in literature for senior care planning. MHCM will develop knowledge extraction methodologies for geriatric care in Phase I and will implement 3 of 40 MHCM defined care categories. Phase II will expand on the algorithm(s) developed during Phase I to include an additional 30-37 care categories. MCHM will also develop geriatric care intervention discovery algorithms to be used in finding, updating, and evaluating new knowledge to be included in the SCANSTM knowledgebase. MHCM will verify and validate the feasibility of the knowledge acquisition methods by comparing the current manual research process with an automated acquisition process using literature. MHCM will then augment the knowledge discovered through text mining with an existing Bayesian Reasoning Network model to make the SCANS TM an efficient decision support system for geriatric care. With the completion of Phases I and II, commercialization of the knowledge acquisition system for SCANSTM can then proceed in Phase III of the project. PUBLIC HEALTH RELEVANCE: The goal of this Fast-Track research application is to improve the quality, depth and breadth of research reference material held in the Senior Care Navigation System, SCANS, knowledgebase used by our Geriatric Care Managers. The knowledgebase helps our GCM's to prepare comprehensive care plans for elders and their care givers covering 40 care categories. The intent is to expand the knowledge of and coordinate the services available to seniors and their families for improving their quality of life and for extending independent living.

描述（由申请人提供）：美国老年人口的急剧增长被广泛认为将挑战美国卫生系统这一部分的能力。支持老年人独立生活的替代战略对于弥补这一缺口至关重要。My Health Care Manager（MHCM）开发了老年护理导航系统（SCANSTM），为老年护理经理（GCM）、注册护士和社会工作者提供决策支持，为老年人及其护理人员制定消费者侧护理计划。SCANSTM提供干预措施和实用的现实世界工具，以延长健康和积极的生命年数，并协助家庭做出关键决定。知识的自动获取将有助于增强MHCM的研究人员，以保持SCANSTM知识库最新，以提供有效和高效的高级护理计划。这一快速SBIR研究的总体目标将是MHCM与印第安纳州大学信息学院合作开发一个自动化知识获取系统，该系统将从与高级护理相关的健康文献中获取知识。这种知识以“最佳做法”的形式将被用作SCANSTM决策支持系统的一部分。知识的自动获取将大大提高SCANS研究团队的整体生产力。在质量、及时性、广度、深度和研究量方面的改进将成为SCANSTM产品的一个市场特征。在第一阶段，MHCM将验证自动获取文献中的知识用于高级护理规划的可行性。MHCM将在第一阶段为老年护理开发知识提取方法，并将实施MHCM定义的40个护理类别中的3个。第二阶段将在第一阶段开发的算法基础上进行扩展，增加30-37个护理类别。MCHM还将开发老年护理干预发现算法，用于查找、更新和评估SCANSTM知识库中包含的新知识。MHCM将通过比较目前的手动研究过程与使用文献的自动获取过程来验证和确认知识获取方法的可行性。然后，MHCM将通过现有的贝叶斯推理网络模型来增强通过文本挖掘发现的知识，以使SCANSTM成为老年护理的有效决策支持系统。在第一和第二阶段完成后，SCANSTM知识获取系统的商业化可以在项目的第三阶段进行。 公共卫生关系：这个快速通道研究应用程序的目标是提高质量，深度和广度的研究参考资料中持有的高级护理导航系统，SCANS，知识库使用我们的老年护理经理。该知识库可帮助我们的社区护理员为长者及其照顾者制定涵盖40个护理类别的全面护理计划。其目的是扩大对老年人及其家庭可获得的服务的了解，并协调这些服务，以提高他们的生活质量，并延长独立生活的时间。