STTR Phase II: Self-Health Management Informatics Platform: Improving Patient Engagement in Care Delivery

STTR 第二阶段：自我健康管理信息学平台：提高患者在护理服务中的参与度

• 批准号: 1831214
• 负责人: Michael Wassil
• 金额: $ 71.12万
• 依托单位: SIPPA Solutions LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831214&HistoricalAwards=false
• 关键词: STTR; Phase; II; Self; Health

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase II project is a patient-centric engagement process that offers the best chance for enabling a scalable approach towards achieving the triple aim of improving care quality and outcomes, controlling health care costs and utilization, and increasing patient satisfaction. Currently the national healthcare cost is estimated at $3.2 trillion. Until patients could be engaged to take ownership of their health, advancement in pharmacological interventions through medications will not be able to achieve optimal care outcomes, and the healthcare cost and utilization will remain high. Engaging patients in self-management activities that are in alignment with the motivation indicators not only improves patient experience and satisfaction, but contributes to collecting big data for linking motivation to behavioral therapy --- resulting in an effect essential to improving population health and advancing personalized precision. This Small Business Technology Transfer (STTR) Phase II project is a patient-centric engagement process MISA (Measure-Integrate-Share-Act). While well-established behavior models such as the Theory of Planned Behavior (TPB) and Information-Motivation-Behavioral Skill (IMB) have been reported to show clinical efficacy, the novelty of this research is the application of Structure Equation Modeling to develop a quantitative behavior model. Quantitative behavior modeling is significant because it allows a rigorous assessment of the model in terms of goodness of fit and statistical power. Furthermore, such model provides the patented SIPPA analytic engine a basis to predict the software services that are in alignment with the motivation indicators of a patient users in order to effectively engage them in self-health management of chronic conditions, and to promote behavioral change for healthy lifestyle.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这一小型企业技术转移（STTR）II期项目的更广泛的影响/商业潜力是一个以患者为中心的参与过程，为实现改善护理质量和结果，控制医疗保健成本和利用和提高患者满意度的三重目标提供了可扩展方法的最佳机会。目前，国家医疗保健费用估计为3.2万亿美元。除非能够聘请患者拥有健康状况，否则通过药物进行药理学干预的进步将无法实现最佳的护理结果，并且医疗保健成本和利用率将保持很高。让患者参与与动机指标保持一致的自我管理活动不仅可以改善患者的经验和满意度，而且有助于收集大数据将动机与行为疗法联系起来，从而对改善人口健康和推进个性化的精度至关重要。 这个小型企业技术转移（STTR）II期项目是一个以患者为中心的参与过程Misa（MEATURE-CONTEMERATE-SHARE-ACT）。据报道，诸如计划行为理论（TPB）和信息动机 - 行为技能（IMB）等良好的行为模型已据报道显示出临床疗效，但这项研究的新颖性是结构方程模型的应用来开发定量行为模型。定量行为建模很重要，因为它可以根据拟合和统计能力对模型进行严格的评估。此外，这种模型为专利的SIPPA分析引擎提供了一种基础，以预测与患者用户的动机指标保持一致的软件服务，以便有效地使他们参与慢性病的自保健管理，并促进健康生活方式的行为改变。该奖项反映了NSF的法定任务，反映了通过评估的构成构成的依据和构成的依据。

项目成果

Incorporating Association Patterns into Manifold Clustering for Enabling Predictive Analytics

将关联模式合并到流形聚类中以实现预测分析

• DOI: 10.1109/csc149370.2019.00243
• 发表时间: 2019
• 期刊: Title: 2019 International Conference on Computational Science and Computational Intelligence (CSCI
• 作者: Bon K. Sy;Jin Chen;Rebecca Horowitz
• 通讯作者: Rebecca Horowitz

Behavioral Predictive Analytics towards Personalization for Self-management

自我管理个性化的行为预测分析

• DOI: 10.5220/0000145600002865
• 发表时间: 2021
• 期刊: Volume 5: HEALTHINF
• 作者: Bon Sy;Magdalen Beiting Parrish;Connor Brown
• 通讯作者: Connor Brown

Linking biometric voice identity with self-monitoring health data as a temporal-spatial event stored in a mobile device

将生物识别语音身份与自我监测健康数据链接起来，作为存储在移动设备中的时空事件

• 发表时间: 2021
• 作者: Bon Sy