I nnovation at

1. Innovation at

3. UNOS Labs

4. UNOS Labs

5. Post-Labs Life Center-level QI tool to understand acceptance behaviors (SimUNet 1/2/4) ASTS Fellows Symposium training and assessment tool (SimUNet) PHS IR granularity (SimUNet 3) on acceptance behavior Timely Donor Referral Change Refusal Code 830 (SimUNet 2/3/4) Revisit KDPI Calculations: Accommodate HCV+ NAT- risk (SimUNet 3) and include NLP discard predictions for kidney (NLP usability predictor) Predicting travel time (Feasibility phase 1 complete) Image sharing – evaluate national rollout OC Kidney Accelerated Placement (KAP)

6. Organ tracking Transportation planning Cold ischemic time Imaging and Communication

7. Predicting travel time

9. Data Structure COMPLETE

10. Travel time questions • What sources of data are necessary for travel planning? • What inputs are necessary to generate useful travel options? (e.g., number of passengers) • What does the output need to include for users’ decisionmaking? (e.g., time, cost)

11. Cold ischemic time

12. Conceptual Components of CIT (not to scale) Clamp Time Transplant Time Departure Transit Procurement Transplant Offer Acceptance Delivery Time

13. Proof of Concept Data Structure UNOS Structured allocation & transplant data, TransNet Data Cold Ischemic Data OC Courier Data OC case flight data Cold Ischemia Prediction Combination of structured data, TransNet and flight/courier information OPO Courier Data OPO case flight data Projected Travel Develop an understanding of actual CIT, plus validate algorithmic projected travel and identify travel optimization opportunities Ground Couriers Organ delivery data Callback with other travel partners that explores what travel options were possibly available at time of offer Other Travel Partners “Real time” projected travel time, inc. driving and flight info

14. Project Components Begin Summer 2020 Spring 2020 End of 2019

15. Cold time questions • What other data sources should we consider for calculating cold time? • What variables should we examine to determine their impact on cold time (time of day, size of hospital?) • What sources should we use to establish acceptable cold time targets (journals, surveys, don’t set targets and let individual practitioners decide)

16. Organ Tracking

17. Organ Tracking

18. Organ tracking questions • What do you need to know when an organ is in transit? • About the carrier? • About the organ? • About the candidate? • About the OPOs or centers?

19. Imaging

20. Communication Memorial Hospital Anytown, ST Timeliness Completeness of information Flexibility Transparency Professionalism

21. Imaging and communication questions • What non-UNet users might need access to shared images? • Would you use a secure chat within DonorNet instead of your current tools? • If you could rate your interactions with other members, would you? Would you review your own ratings for performance review and improvement?

22. UNOS Labs Projects (08/14/19) Horizon 3 Horizon 2 Horizon 1 • Machine Learning Liver Biopsy Reader (feasibility study) • Natural Language Processing: NLRB Liver Exception Requests • Natural Language Processing: Organ Utilization Predictor, Yield Models • Predicting ColdIschemic Time • Organ perfusion strategy (state of technology report) • Xenotransplantation • Universal Image Sharing • OC Kidney Accelerated Placement Project • OC Speech Recognition (feasibility study) • Projecting Travel Time (feasibility study)

23. Share your ideas UNOS innovation events: AOPO IT Council 2016 AOPO IT Council 2017 NATCO Annual Meeting 2017 NATCO Annual Meeting 2018 ASTS Winter Symposium 2019 AOPO Procurement Council 2019 TMF 2019 NATCO 2019 ASHI Annual Meeting Sep ‘19 AOPO Procurement Council Feb ‘20 TMF May ‘20 NATCO Aug ‘20 ASTS Winter Symposium Jan ‘21

24. Share your ideas UNOS.Labs@unos.org