STTR Phase I: A Mobile Triage Application for Reducing the Risk of COPD Exacerbations

STTR 第一阶段:用于降低 COPD 恶化风险的移动分诊应用程序

基本信息

  • 批准号:
    1820049
  • 负责人:
  • 金额:
    $ 22.5万
  • 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
  • 起止时间:
    2018-07-15 至 2019-06-30
  • 项目状态:
    已结题

项目摘要

The broader impact/commercial potential of this Small Business Technology Transfer (STTR) project is the reduction of significant disease flare-ups in patients with Chronic Obstructive Pulmonary Disease (COPD), increase in patient quality-of-life, and a reduction of expensive and unnecessary healthcare utilization. Current at-home care support for COPD patients is often completely missing or consists of action plans that fail to provide effective, individualized care. The alternative solution under development in this project is an easy-to use, personalized mobile application that catches disease degeneration early, tracks patient health history, and provides decision support to guide patients to the right medical care at the right time. COPD is one of the leading chronic conditions driving potentially avoidable hospital admissions. Pairing a mobile health management app with a smart triage system that provides instant healthcare guidance has the potential to dramatically reduce unnecessary COPD hospitalization and provide long-term maintenance treatment of COPD symptoms. Moreover, an easily accessible, highly accurate, convenient solution can empower patients to make better health decisions early. This STTR Phase I project proposes to demonstrate positive impact and adoption of a mobile triage application for COPD patients. To date, a set of triage algorithms has been built and validated on simulated patient cases. The algorithms exhibited performance that is comparable to or better than a panel of board-certified pulmonologists. The next vital step is to establish the technical feasibility of a packaged, stand-alone mobile application. This research will focus on developing a fully featured prototype that is optimized for adoption, retention, and efficacy. A mix of user feedback and rigorous usage analysis collected through human testing will provide necessary insights on barriers to use, missing functionality, and consumer value. Standardized markers of health safety, symptom escalations, and patient quality-of-life will be used as metrics of product performance. Moreover, all data and conclusions will be subjected to peer review through publication and public presentations. As an additional objective, the accuracy of the algorithmic triage recommendations will be tested on real patient cases to further validate their accuracy and effectiveness. The anticipated result of the phase I procedure is demonstration that the app is safe (objective 1), operationally sound and optimal (phase 2), and valuable to consumers (objective 3).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.
这种小型企业技术转移(STTR)项目的更广泛的影响/商业潜力是减少慢性阻塞性肺部疾病(COPD)患者的明显疾病爆发,患者生活质量的增加以及降低昂贵且不必要的医疗保健利用率。当前对COPD患者的家庭护理支持通常完全缺失,或者包括无法提供有效的个性化护理的行动计划。该项目中正在开发的替代解决方案是一种易于使用的个性化移动应用程序,该应用程序及早发现疾病变性,跟踪患者的健康病史,并提供决策支持,以指导患者在正确的时间进行正确的医疗服务。 COPD是推动可能避免住院的领先慢性疾病之一。将移动健康管理应用程序与提供即时医疗保健指南的智能分类系统配对,有可能大大减少不必要的COPD住院治疗,并为COPD症状提供长期维护治疗。此外,一种易于获得,高度准确,方便的解决方案可以使患者能够尽早做出更好的健康决定。该STTR I期项目提议展示对COPD患者的移动分流申请的积极影响和采用。迄今为止,已经在模拟的患者病例上构建和验证了一组分类算法。该算法表现出与董事会认证的肺科医生相比或更好的性能。下一个至关重要的步骤是建立包装,独立的移动应用程序的技术可行性。这项研究将着重于开发完整的特色原型,该原型旨在采用,保留和功效。通过人类测试收集的用户反馈和严格的用法分析的结合将提供有关使用障碍,缺少功能和消费者价值的必要见解。健康安全,症状升级和患者生活质量的标准化标记将用作产品性能的指标。此外,所有数据和结论都将通过出版和公开演讲进行同行评审。作为另一个目标,将在实际患者病例上测试算法分类建议的准确性,以进一步验证其准确性和有效性。第一阶段程序的预期结果是证明了该应用程序是安全的(目标1),在操作上是合理的和最佳的(第2阶段),并且对消费者很有价值(目标3)。该奖项反映了NSF的法定任务,并被认为是值得通过基金会的知识分子优点和更广泛的审查标准来通过评估来获得支持的。

项目成果

期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

暂无数据

数据更新时间:2024-06-01

Sumanth Swaminatha...的其他基金

SBIR Phase II: A Therapeutic Machine-Learned Triage Application For Early Detection and Triage of COPD Exacerbations
SBIR 第二阶段:用于早期检测和分诊 COPD 恶化的机器学习分诊治疗应用
  • 批准号:
    1950994
    1950994
  • 财政年份:
    2020
  • 资助金额:
    $ 22.5万
    $ 22.5万
  • 项目类别:
    Standard Grant
    Standard Grant

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