STTR Phase II: Self-Health Management Informatics Platform: Improving Patient Engagement in Care Delivery
STTR Phase II: Self-Health Management Informatics Platform: Improving Patient Engagement in Care Delivery
批准号:
1831214
负责人:
Michael Wassil
金额:
$71.12万
依托单位:
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
项目状态:
已结题
起止时间:
2018-09-15 至 2022-07-31
中文摘要
点击翻译按钮获取中文摘要
英文摘要
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.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
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
影响因子:
--
作者:
[Bon K. Sy, Jin Chen, Rebecca Horowitz]
通讯作者:
Rebecca Horowitz
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
DOI:
--
发表时间:
2021
期刊:
2021
影响因子:
--
作者:
[Bon Sy]
通讯作者:
Bon Sy
DOI:
10.5220/0000145600002865
发表时间:
2021
期刊:
Volume 5: HEALTHINF
影响因子:
--
作者:
[Bon Sy, Magdalen Beiting Parrish, Connor Brown]
通讯作者:
Connor Brown
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海外基金
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