1. Tackling geographic disparity – Redistribution of livers Ryutaro Hirose, MD Professor, Surgery Vice Chair, UNOS Liver Intestine committee Region 5 Collaborative Las Vegas, NV March 2015

2. History - UNOS 1984 – the US Congress passed NOTA (National Organ Transplant Act) – Established the OPTN (Organ Procurement and Transplantation Network) – To maintain a national list of candidates – To establish a national systems to match organs with candidates – To assist OPOs in the nationwide distribution of organs EQUITABLY among transplant patients

3. Recent history – liver allocation v 2.0 2000 – US Department of Health and Human Services publishes Final Rule for the operation of the OPTN 2002 – Changes made to use the MELD score to allocate liver allografts

4. US Department of HHS Final Rule Allocation of cadaveric organs – the allocation polices: – Shall seek to achieve the best use of donated organs; – Shall be designed to avoid wasting organs, to avoid futile transplants, to promote patient access to transplantation, and to promote the efficient management of organ placement; – Shall not be based on the candidate's place of residence or place of listing

5. Sickest first Setting priority rankings…that shall be ordered from most to least medically urgent. There shall be a sufficient number of categories (if categories are used) to avoid grouping together patients with substantially different medical urgency;

6. Allocation of scarce resources Demand vs. supply Transplantation is one field that rations medical care Selection committees – Dialysis – Transplant candidacy

7. Organ allocation – balancing conflicting principles UTILITY – Maximizing usefulness of scarce resource EFFICIENCY – Cost – Value JUSTICE – Fairness – Equal access

8. Deceased donor organs Allocation scheme – How patients are ordered – LIVER: sickest first – LUNG: ratio of yrs added with transplant/mortality pretxp without txp – Kidney: has largely been based on waiting time

9. MELD – sickest first MELD =(0.957 x LN(creatinine) + 0.378 x LN(bilirubin) +1.12 x LN(INR) +0.643) x 10 Capped at 40 MELD score is relatively accurate in predicting 3 month waitlist mortality in liver transplant recipients

10. Liver – sickest first Status 1 – acute liver failure MELD SCORE – Bilirubin – INR – Cr MELD EXCEPTIONS – Metabolic diseases – HCC

11. Map of OPO boundaries/DSA

12. UNOS regions

13. Organ distribution – SHARE 35 Status 1 – UNOS REGION MELD 35-40 – UNOS REGION MELD 15-34 – local DSA MELD >15 – UNOS REGION Status 1 – National MELD >15 National MELD <15 Local, regional then National

14. Share 35 An extension of regional sharing for status 1 patients Expanding access to livers for the sickest patients Pts with MELD scores have >33% risk of dying in a year

15. Share 35 Has accomplished intended goals More pts with MELD > 35 are getting transplanted So far, no decrease in outcomes No increase in discards Increase in cold ischemia time modest

16. Share 35 BUT some other Increased costs – Transplant centers (sicker pts) – OPOs Increased flyouts Transportation logistics Outside teams, team work (lack thereof) Gaming the system – Accepting multiple offers – Late declines

17. Share 35 – needs exposed Need more cooperation, communication Need more transparency Ability of OPOs to see how many offers a center has accepted for a candidate (put limits) Need more agile allocation system (DonorNET) – More offers than 3 centers at a time Change scheme so that livers don’t cross in the air for a single MELD point ?

18. HHS: Final Rule Neither place of residence or place of listing shall be a major determinant of access to a transplant

19. Metrics of disparity Supply/Demand ratio – Supply – All liver donors? eligible deaths? Potential deaths? All deaths? – Demand – wait listed pts? Pts with ESLD? Variance in transplant rates across DSA/Regions Variance in organ offers across DSA/Regions Variance in drop off rates Variance in waitlist mortality Variance in MELD scores at transplant Variance compared to single national list

20. Measuring Disparity Summative metrics – Over the whole country – On average, 40% of the pts with a MELD score of 38- 39 die within 90 days Disparity metric – Range across the country by OPO/DSA – In some DSA’s 18% of pts with MELD 38-39 die within 90 days – In others 82% die – Variance in death across the country by DSAs

21. Transplant rates by MELD

22. Waitlist deaths by MELD

23. Alternatives Different Districts (super-regions), maintaining OPO boundaries as a guide to redistricting Concentric circles around a donor hospital Compare to single national list – full national sharing (lowest disparity)

24. Comparing designs/maps Alternative maps generated by contraints and algorithm LSAM simulation models of allocation policy changes Limitations of LSAM – Changes in behavior impossible to model – Listing criteria/Organ acceptance patterns – OPO aggressiveness – Hard to predict, not included in models

25. Redistricting objectives Reduce/Minimize total disparity – Difference between the # of organs an area should have (if organ went to highest MELD pt) – organs a region has – Minimize sum of these disparities across all regions Subject to constraints – The minimal disparity is achieved by complete national sharing

26. Redistricting constraints At least 4 and no more than 8 districts Minimum # of centers per district: 6 Maximal travel time between DSAs in same Region: 4-5 hours Summative metric: the total # of waitlist deaths under redistrcting must not be higher than current system

27. Outputs from LSAM - Metrics SUMMATIVE – Total deaths – Waitlist deaths – Avg transport times – % transportable by car – Avg transport distance – % organs to pts with MELD>25 DISPARITY – Variance of MELD score at transplant across DSAs

28. 7 regions, 3 hour transport

29. 4 region

34. Comparison to concentric circles Concentric circle – first allocation within circle of 500 miles Advantage – simple, transparent Disadvantage – not superior to optimized maps for decreasing disparity

35. Existing geographic disparity

36. 4 district map reduces disparity

37. NEXT LSAM request Add 3 or 5 MELD points for local candidates Local defined by a circle around a donor hospital of 150 vs. 250 miles To avoid livers flying for differences of 1-2 MELD points (some local priority) Will examine all metrics of disparity

38. Liver forum – ad hoc subcommittees Metrics of diparity Logistics Finances Increased donation and utilization

39. Potential proposals from subcommittees Increase transparency – allow OPOs to see all offers a specific candidate Limit acceptances to 2 livers per candidate Increase # of offers (from 3) to many more on donorNET Expedited placement – More broad offers immediately for suboptimal donors Track acceptance patterns vs. listing criteria for centers

40. The US - EXTREMES Currently 28% of The US population lives in a DSA where median MELD at transplant is >29 or <20 After redistricting only 6% of the population will live in DSAs where median MELD scores are that extreme

41. Summary Implementation of MELD largely fulfilled ‘sickest first’ Significant geographic disparity exists – policy change is hard to implement – Political forces – Self-interest: fears of transplant centers – Concerns about disparate OPO performance – Concerns about increasing distances, costs