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I nnovation at 1 2 UNOS Labs I nnovation at 1 2 UNOS Labs

I nnovation at 1 2 UNOS Labs - PowerPoint Presentation

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I nnovation at 1 2 UNOS Labs - PPT Presentation

3 4 UNOS Labs PostLabs Life 5 PHS IR granularity SimUNet 3 on acceptance behavior Timely Donor Referral Centerlevel QI tool to understand acceptance behaviors SimUNet 124 ASTS Fellows Symposium training and assessment tool ID: 801880

data time organ travel time data travel organ cold unos 2019 simunet natco feasibility labs council flight ischemic symposium

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Presentation Transcript

Slide1

Innovation at

1

Slide2

2

Slide3

UNOS Labs3

Slide4

4

UNOS Labs

Slide5

Post-Labs Life

5

PHS IR granularity (SimUNet

3) on acceptance behavior

Timely Donor Referral

Center-level QI tool to understand acceptance behaviors (

SimUNet

1/2/4)

ASTS Fellows Symposium training and assessment tool (

SimUNet

)

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)

Slide6

6

Transportation planning

Cold ischemic time

Organ tracking

Imaging and Communication

Slide7

Predicting travel time7

Slide8

8

Slide9

Data Structure9

COMPLETE

Slide10

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)

Travel time questions10

Slide11

Cold ischemic time11

Slide12

Conceptual Components of CIT (not to scale)12

Procurement

Transit

Transplant

Clamp Time

Departure

Offer

Acceptance

Delivery Time

Transplant Time

Slide13

Proof of Concept Data Structure13

UNOS

OC Courier Data

Ground Couriers

Other Travel Partners

Structured allocation & transplant data,

TransNet

Data

OC case flight data

Organ delivery data

“Real

time”

projected

travel

time,

inc.

driving and flight info

Cold

Ischemic

Data

Projected Travel

Cold Ischemia

Prediction

Combination of structured data,

TransNet

and flight/courier information

Callback

with other travel partners that

explores what travel options were possibly available

at time of offer

Develop an understanding of actual CIT, plus validate algorithmic projected travel and identify travel optimization opportunities

OPO Courier

Data

OPO case flight data

Slide14

Project Components14

End of 2019

Spring 2020

Begin Summer 2020

Slide15

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)

Cold time questions15

Slide16

Organ Tracking16

Slide17

Organ Tracking17

Slide18

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?

Organ tracking questions18

Slide19

Imaging19

Slide20

Communication20

Memorial Hospital

Anytown

, ST

Timeliness

Completeness of information

Flexibility

Transparency

Professionalism

Slide21

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?

Imaging and communication questions

21

Slide22

UNOS Labs Projects (08/14/19)

22

Horizon 1

Horizon 2

Horizon 3

Machine Learning Liver Biopsy

Reader (feasibility study)

Natural

Language Processing: NLRB Liver Exception

Requests

Natural Language Processing: Organ Utilization Predictor, Yield Models

Predicting Cold

Ischemic Time

Universal

Image Sharing

OC Kidney Accelerated Placement Project

OC Speech Recognition (feasibility study)

Projecting Travel Time (feasibility study)

Organ perfusion strategy (state of technology report)

Xenotransplantation

Slide23

UNOS innovation events:

AOPO

IT Council 2016AOPO 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 ‘20TMF May ‘20

NATCO Aug ‘20ASTS Winter Symposium Jan ‘21Share your ideas23

Slide24

UNOS.Labs@unos.org

Share your ideas

24