Automatic Acquisition of Knowledge for Senior Care Planning

自动获取老年护理规划知识

• 批准号: 8232390
• 负责人: Eric Christopher Tinsley
• 金额: $ 19.67万
• 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 2011-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8232390
• 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 effective; 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预期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将是弥补这一缺口的关键。我的健康护理经理(MHCM)开发了高级护理导航系统(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，为老年人及其照顾者构建消费者侧护理计划。SCANSTM提供干预措施和实用的现实世界工具，以延长健康和活跃的生命年限，并帮助家庭做出关键决定。知识的自动获取将有助于增加妇幼保健中心的研究人员，以便使SCANSTM知识库保持最新，以提供有效和高效的老年护理计划。这项快速通道SBIR研究的总体目标将是MHCM与印第安纳大学信息学学院合作开发一种自动化知识获取系统，该系统将从与老年护理相关的健康文献中获取知识。这种“最佳做法”形式的知识将被用作SCANSTM决策支持系统的一部分。知识的自动获取将极大地提高扫描研究团队的整体工作效率。研究的质量、及时性、广度、深度和数量的改进将是SCANSTM产品的一个适销对路的特点。在第一阶段，MHCM将验证自动获取文献中的知识用于老年护理规划的可行性。MHCM将在第一阶段为老年护理开发知识提取方法，并将实施40个MHCM定义的护理类别中的3个。第二阶段将在第一阶段开发的算法(S)的基础上扩展，以包括额外的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、更新和评估将包括在SCANSTM知识库中的新知识。MHCM将通过比较目前的人工研究过程和使用文献的自动获取过程来验证和验证知识获取方法的可行性。然后，MHCM将使用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，使SCANS TM成为老年护理的有效决策支持系统。随着第一和第二阶段的完成，SCANSTM知识获取系统的商业化可以在该项目的第三阶段进行。 公共卫生相关性：这一快速通道研究应用程序的目标是提高老年护理导航系统、扫描和知识库中保存的研究参考材料的质量、深度和广度，供我们的老年护理经理使用。该知识库帮助我们的GCM为老年人及其照顾者准备涵盖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人可获得的服务的了解和协调，以提高他们的生活质量和延长他们的独立生活。