SBIR-STTR Award

Organ transplantation is a complex process requiring effective coordination and communication amongst a highly distributed network of providers within a short window of time in order for a successful transplantation to occur. However, Fewer than 40% of authorized donated organs are transplanted successfully and over 120,000 patients in the US are waiting for a transplant, with 22 patients dying every day (Organ Procurement and Transplantation Network (OPTN) 2014 data). Failures to transplant a larger percentage of authorized donated organs result, in part, from a medical professional's lack of access to secure, timely, and accurate information required in order to determine viability of donated organs and coordinate their successful recovery. These discarded organs amount to significant waste and could be used for a variety of impactful applications, dependent on viability. Discarded organs could be used by transplant centers, medical researchers, and pharmaceutical companies to increase life-saving transplants, translational research, drug discovery/testing, and cells for new and innovative therapies. To address the need for an improve communications system to help improve transplant patient outcomes and the number of viable, but unused organs that could be successfully transplanted, Organizer Inc. has developed, ORGANIZER, a mobile application for secure team communication to improve organ transplant outcomes for deceased organ donation cases. The proposed project is designed to test and quantify the improvement of the donor management, coordination process, and patient outcomes proving commercial feasibility using ORGANIZER for medical team communication. If successful, the approach can be extended and disseminated to all organ procurement organizations (OPOs) and Transplant networks. The results of this research will determine whether ORGANIZER can be adopted as the communication "best practice" for organ procurement and transplant organizations during donor management and coordination. Organizer Inc. will partner with Relational Coordination Analytics (RCA) Inc. to introduce and deploy a hybrid relational and process improvement methodology aimed at assessing the impact of Organizer Inc.'s mobile application on outcomes for donor management, coordination for organ procurement, and transplant patients. Develop and deploy beta software prototype. Prove feasibility of the Organizer Inc. communication system through robust validation testing. Successful completion of this SBIR Phase I study will result in a functional, validated communication software system that meets or exceeds preliminary performance and user satisfaction metrics resulting in improved transplant patient outcomes.

Public Health Relevance Statement:
Information asymmetry and poor communication between medical providers/hospital systems and patients has long been identified as barrier to quality health outcomes. This issue is particularly problematic in regards to scaling the efforts of care coordination which has been shown to be effective in multiple studies at reducing cost of care. This project attempts to provide patients with the information they need to make the best choices for themselves utilizing a self service chat software application that also offers the ability for a trained care coordinator to intervene when the software unable to assist the individual patient, thereby scaling care coordinators influence and effectiveness across a broad base of patients.

Project Terms:
Address; Adopted; Area; Asses; base; Caring; Cells; commercialization; Communication; Complex; Computer software; cost; Custom; Data; design; Development; drug discovery; Effectiveness; Employee; Environmental Risk Factor; Event; Failure; Health; Hospitals; Hybrids; improved; individual patient; Industry Standard; Innovative Therapy; interest; Interview; Iowa; Life; Longitudinal Studies; Measures; Medical; Methodology; mobile application; novel therapeutics; Organ; Organ Donations; Organ Donor; Organ Procurements; Organ Transplantation; Outcome; Patient-Focused Outcomes; Patients; Performance; performance tests; Pharmacologic Substance; Phase; phase 1 study; Positioning Attribute; Process; Property; prototype; Provider; Reaction Time; Recovery; Reporting; Research; Research Personnel; satisfaction; Savings; Secure; Series; Services; Shapes; simulation; Small Business Innovation Research Grant; software systems; Solid; Surveys; System; Techniques; Test Result; Testing; Thinness; Time; Training; Translational Research; Transplant Recipients; Transplantation; Validation; wasting; Work

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.

Public Health Relevance Statement:
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.

NIH Spending Category:
Bioengineering; Clinical Research; Kidney Disease; Machine Learning and Artificial Intelligence; Networking and Information Technology R&D (NITRD); Organ Transplantation; Patient Safety; Transplantation

Project Terms:
Address; Adoption; Artificial Intelligence; Asses; burnout; Cessation of life; Chronic; Clinical; clinical decision support; clinical decision-making; Clinical effectiveness; clinical implementation; cohesion; commercial application; commercialization; Communication; Communities; Computer software; cost; cost effective; cost effectiveness; Data; Decision Making; Decision Support Model; design; Development; Dialysis procedure; Direct Costs; effective therapy; End stage renal failure; Enhancement Technology; Ensure; Evaluation; experience; Feedback; Foundations; Goals; Grant; Health; Healthcare; Hour; Human; improved; Infrastructure; insight; Institution; Journals; Kidney; Kidney Transplantation; Life; Literature; Machine Learning; Measures; Medical; mobile application; Multiple Partners; operation; Organ; Organ Procurements; Organ Transplantation; Outcome; Patient-Focused Outcomes; Patients; Peer Review; Performance; Phase; Physicians; Pilot Projects; Positioning Attribute; prevent; Privatization; Process; Productivity; Publications; Renal Glycosuria; Reporting; response; satisfaction; Savings; Secure; Surgeon; Surveys; System; Technology; Telephone; Testing; Time; Tissue Transplantation; transmission process; transplant centers; Transplant Recipients; Transplantation; Transplanted tissue; Treatment Cost; trend; usability; Waiting Lists; wasting; Work