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

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.Project Narrative Despite the obvious clinical and cost-effectiveness advantages of kidney transplantation for many patients, nearly 1 in 5 kidneys authorized for donation are discarded. This project addresses the need for an efficient communications software technology enhanced with clinical decision support tailored for organ procurement organizations and transplant centers. Combined with enhanced communication efficiency, clinical decision support powered by machine learning may significantly improve donated kidney utilization and increase the number of viable, but currently unused organs that could otherwise be successfully transplanted, reducing waste and saving lives.