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

医疗技术解决方案项目摘要 肾移植是一种临床有效和成本效益的治疗方法， 肾病（ESRD）和糖尿病。每天有22名病人在等待移植时死亡， 在美国，死亡可以通过器官移植来预防。尽管有明显的临床和成本效益 尽管肾移植有许多优点，但几十年来，肾丢弃率一直在上升， 1988年至2015年的19.2%。在成功的第一阶段赠款期间， 系统，以帮助改善移植患者的结果，并实现更大的捐赠器官利用，健康科技 Solutions（HTS），Inc.开发了一个专有的移动的应用程序，用于量身定制的安全团队通信 专门为肾移植团队设计的为了进一步提高沟通效率， 医疗保健决策，特别是外科医生，HTS将采用机器学习（ML）驱动的 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， 降低肾移植的成本。拟议项目旨在进一步测试和量化 使用该系统改善供体管理、协调过程和肾脏利用结果， 公司的CDS和医疗团队通信的通信基础设施。目标是：（1）发展 专门为移植专业人员设计的CDS模型，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并提供见解的CDS基础设施， 快速; 2）通过与测试组合作来评估可用性，以超过可用性标准，并确保CDS符合 临床医生需要通过用户反馈迭代。多样化测试组的效用验证（n=10） 他们代表了参与移植手术的所有专业人员3)测量TXP聊天的效果 在肾脏报价和采购流程中进行实时临床实施后， 在365天内与多个合作伙伴机构提供超过3，000个报价（1，500个CDS和1，500个控制） （n=3）。TXP Chat和CDS将通过临床/技术证明是可靠、安全、值得信赖和有用的 社区，增加肾脏接受的做法，导致增加肾脏移植，减少感冒 缺血时间和从提供到移植时间的减少。最终，这些指标已被证明 在文献中，为了改善患者结局，降低昂贵的慢性治疗成本（例如透析）， 患者因缺乏肾脏可用性而死亡，并显着改善人类健康和生产力。研究 研究结果将通过在同行评审期刊上发表的方式传播。目标1将为今后的发展奠定基础 开发，以便在IIB期实现更广泛的CDS。目标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将提供多中心初步研究数据，用于证明 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.