SBIR Phase II: A Therapeutic Machine-Learned Triage Application For Early Detection and Triage of COPD Exacerbations

SBIR二期项目的更广泛/商业影响旨在减少慢性阻塞性肺疾病（COPD）患者的重大疾病突发，提高住院患者的生活质量，并减少昂贵和不必要的医疗保健利用。慢性阻塞性肺病是导致本可避免住院的主要慢性病之一，在2018年的患者护理成本中，估计占250亿美元。目前对慢性阻塞性肺病患者的家庭护理支持往往完全缺失，或者由无法提供有效的个性化护理的行动计划组成。整合健康管理和提供即时医疗保健指导的智能分诊系统有可能减少不必要的慢性阻塞性肺病住院治疗，并为慢性阻塞性肺病症状提供长期维持治疗。拟议的项目将开发一个易于使用的个性化分类应用程序，该应用程序可以早期发现疾病退化，跟踪患者的健康史，并提供决策支持，以适当地指导患者。此外，一个容易获得、高度准确、方便的解决方案可以使患者尽早做出更好的健康决定。这个SBIR II期项目的重点是优化和部署一个分流应用程序，为COPD患者提供个性化的决策支持和治疗效益。拟议的项目将为新人口验证这一应用，并测试综合系统。具体的技术任务包括扩展算法，以包括联合诊断的copd -哮喘患者，这是一个重要的风险人群，以及优化配置的可用性和性能。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader/commercial impact of SBIR Phase II project aims to reduce significant disease flare-ups in patients with Chronic Obstructive Pulmonary Disease (COPD), increase in-patient quality-of-life, and reduce expensive and unnecessary healthcare utilization. COPD is one of the leading chronic conditions driving potentially avoidable hospital admissions, accounting for an estimated $25 B in 2018 patient care costs. Current at-home care support for COPD patients is often completely missing or consists of action plans that fail to provide effective, individualized care. Integrating health management and a smart triage system offering instant healthcare guidance has the potential to reduce unnecessary COPD hospitalization and provide long-term maintenance treatment of COPD symptoms. The proposed project will develop an easy-to use, personalized triage application that catches disease degeneration early, tracks patient health history, and provides decision support to guide patients appropriately. Moreover, an easily accessible, highly accurate, convenient solution can empower patients to make better health decisions early. This SBIR Phase II project focuses on optimizing and deploying a triage application that provides personalized decision support and therapeutic benefit to patients with COPD. The proposed project will validate this application for a new population and test the integrated system. Specific technical tasks include the expansion of algorithms to include jointly diagnosed COPD-asthma patients, an important population at risk, as well as optimization of configurations for usability and performance.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.