Artificial intelligence-enabled, real-time communication software for optimizing clinical decision making during the allocation, procurement, and transplantation of donated organs

HealthTech解决方案项目摘要 肾移植是治疗终末期患者的一种有效且经济实惠的治疗方法。 肾脏疾病(ESRD)和糖尿病。每天有22名患者在等待移植时死亡，占所有患者总数的30% 在美国，器官移植可以防止死亡。尽管明显的临床和成本效益 肾移植的优点，肾脏丢弃率几十年来一直在上升，从#年的5.1% 1988年增长到2015年的19.2%。在成功的第一阶段赠款期间，并解决专用通信的需求 HealthTech系统有助于改善移植患者的预后并实现更大的捐赠器官利用率 解决方案(HTS)，Inc.开发了一款专有的移动应用程序，用于确保团队通信的安全 专门为肾脏移植团队设计的。进一步提高沟通效率，增强关键 HTS将采用机器学习(ML)支持的医疗保健决策，特别是针对外科医生 临床决策支持。临床决策支持(CDS)可以显著增加访问、提高质量和 降低肾移植费用。拟议的项目旨在进一步测试和量化 改善捐赠者管理、协调过程和肾脏利用结果 公司的CDS和用于医疗队通信的通信基础设施。目标是：1)发展 CDS模型是专门为移植专业人员设计的，旨在改善决策时间和决策信心。 开发能够安全、可靠地处理医疗数据和提供见解的CDS基础设施 快速；2)通过与测试小组合作评估可用性，以超过可用性标准，并确保CDS满足 临床医生需要通过用户反馈迭代。来自不同测试组的效用验证(n=10) 它们代表了移植病例中涉及的各种专业人士。3)测量TxP聊天的效果 在现场临床实施后通过CDS增强肾脏报价和采购流程，以获得更多 在365天内与多个合作机构提供3,000多份服务(1,500份CDS和1,500份控制) 3例。TXP Chat和CDS将被临床/技术人员证明是可靠、安全、值得信赖和有用的 社区，增加肾脏接受度，从而增加肾脏移植，减少寒冷 缺血时间，以及从提供到移植的时间减少。最终，这些指标都得到了验证 在改善患者预后、降低昂贵的慢性治疗成本(例如透析)、减少 患者因缺乏肾脏而死亡，并显著改善人类健康和生产力。学习 结果将通过发表在同行评议的期刊上发布。目标1将为下一步 发展，以便在第二阶段B中实现更广泛的CDS。Aim 2将证明医生的支持和稳定的采用趋势 当我们进入商业化的时候。AIM 3将提供多中心先导研究数据，用于证明 该过程在时间、金钱和移植肾脏总数方面的效率。

Project Abstract for HealthTech Solutions Kidney transplantation is a clinically effective and cost-effective treatment for patients suffering from end-stage renal disease (ESRD) and diabetes. Twenty-two patients die each day waiting for a transplant and 30% of all deaths in the US could be prevented by organ transplant. Despite the obvious clinical and cost-effective advantages of kidney transplantation, there has been a decades-long rise in the kidney discard rate from 5.1% in 1988 to 19.2% in 2015. During a successful Phase I grant and to address the need for a dedicated communications system to help improve transplant patient outcomes and achieve greater donated organ utilization, HealthTech Solutions (HTS), Inc. developed a proprietary mobile application for secure team communication tailored specifically for kidney transplant teams. To further improve communication efficiency and augment critical decision making in healthcare, specifically for surgeons, HTS will employ machine learning (ML) powered clinical decision support. Clinical decision support (CDS) may significantly increase access, increase quality, and reduce the cost of kidney transplantation. The proposed project is designed to further test and quantify the improvement of the donor management, coordination process, and kidney utilization outcomes using the company’s CDS and communication infrastructure for medical team communication. The aims are; 1) Develop CDS models specifically for transplant professionals aimed at improving decision times and decision confidence. Develop the CDS infrastructure capable of handling medical data and serving insights safely, securely, and rapidly; 2) Asses usability by working with a test group to exceed usability criteria and ensure that CDS meets clinician needs through user feedback iterations. Verification of utility from a diversified testing group (n=10) that represent every type of professional involved in transplant cases. 3) Measure the effects of TXP Chat enhanced with CDS after live clinical implementation in the kidney offer and procurement processes for more than 3,000 offers (1,500 with CDS and 1,500 control) over a period of 365 days with multiple partner institutions (n=3). TXP Chat and CDS will demonstrate to be reliable, secure, trustworthy and useful by the clinical/technical community, increase kidney acceptance practices resulting in an increase in kidney transplants, reduction in cold ischemic time, and reduction in time from offer to transplant. Ultimately, these metrics have been demonstrated in the literature to improve patient outcomes, reduce expensive chronic treatment costs (e.g. dialysis), reduce patient deaths from lack of kidney availability, and significantly improve human health and productivity. Study results will be disseminated via publication in a peer-reviewed journal. Aim 1 will lay the foundation for further development to enable wider CDS in the Phase IIB. Aim 2 will prove physician support and steady adoption trend as we roll into commercialization. Aim 3 will provide multi-center pilot study data used to prove increased efficiency of the process in terms of time, money, and total number of kidneys transplanted.