EAGER: Mutual Understanding Theory of Health Care Quality Frontiers

EAGER：医疗保健质量前沿的相互理解理论

• 批准号: 1020553
• 负责人: John Fontanesi
• 金额: $ 12.4万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-05-01 至 2012-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1020553&HistoricalAwards=false
• 关键词: EAGER; Mutual; Understanding; Theory; Health

This EArly Grant for Exploratory Research (EAGER) award provides funding for the development of a science of health care quality that can provide an explanatory theory of the determinants of quality, provide a contextualized framework for health service research to understand what works, generate a mathematical model of critical inputs/output interactions, and generate metrics that provide institutional guidance rather than report cards. As with any science, the structure includes a theory that explains observable phenomena, Axioms, or First Principles that generate testable hypotheses and models, identification of relevant ontology, and methodologies, and above all, be useful. Beside the rather substantial impact of potentially transforming health care quality from an art to a science, the use of Unified Component Modeling to develop mathematical models of the principle components of our Mutual Understanding Theory of Health Care Quality, will impact data mining techniques, predictive modeling, characterization of stochastic and deterministic systems, Bayesian learning and data-user interface methodologies.If successful, the results of this research will impact health care quality and cost, improve patient outcomes, and contribute to the broader field of service science. The increasing contribution of service industries to the American economy has opened interest in organizational structures that support service innovation, how to measure service productivity, the relationship between client satisfaction, including, marketing and objective outcome measures and appropriate methodologies for predicting service demand, service capacity, and inventorying employee skill-sets. This work will contribute to each of these areas.

这项探索性研究早期拨款（EAGER）奖为卫生保健质量科学的发展提供资金，该科学可以提供质量决定因素的解释性理论，为卫生服务研究提供一个情境化框架，以了解什么是有效的，生成关键投入/产出相互作用的数学模型，并生成提供制度指导而不是成绩单的指标。与任何科学一样，该结构包括解释可观察现象的理论、公理或产生可测试假设和模型的第一原理、相关本体的识别和方法，最重要的是，它是有用的。除了潜在地将医疗保健质量从一门艺术转变为一门科学的重大影响之外，使用统一组件建模来开发我们的医疗保健质量相互理解理论的主要组件的数学模型，将影响数据挖掘技术，预测建模，随机和确定性系统的表征，贝叶斯学习和数据用户界面方法。如果成功，这项研究的结果将影响医疗保健的质量和成本，改善患者的治疗效果，并为更广泛的服务科学领域做出贡献。服务业对美国经济的贡献越来越大，这使得人们对支持服务创新的组织结构、如何衡量服务生产力、客户满意度之间的关系（包括营销和客观结果测量）以及预测服务需求、服务能力和员工技能组合的适当方法产生了兴趣。这项工作将有助于这些领域中的每一个。