tackling geographic disparity – redistribution of livers ryutaro hirose, md professor, surgery...
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Tackling geographic disparity – Redistribution of livers
Ryutaro Hirose, MDProfessor, Surgery
Vice Chair, UNOS Liver Intestine committee
Region 5 CollaborativeLas Vegas, NV March 2015
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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
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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
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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
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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;
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Allocation of scarce resources
• Demand vs. supply• Transplantation is one field that rations
medical care• Selection committees – Dialysis– Transplant candidacy
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Organ allocation – balancing conflicting principles
• UTILITY– Maximizing usefulness of scarce resource
• EFFICIENCY– Cost– Value
• JUSTICE– Fairness– Equal access
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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
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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
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Liver – sickest first
• Status 1 – acute liver failure• MELD SCORE– Bilirubin– INR– Cr
• MELD EXCEPTIONS– Metabolic diseases– HCC
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Map of OPO boundaries/DSA
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UNOS regions
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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
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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
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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
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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
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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 ?
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HHS: Final Rule
• Neither place of residence or place of listing shall be a major determinant of access to a transplant
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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
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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
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Transplant rates by MELD
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Waitlist deaths by MELD
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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)
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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
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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
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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
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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
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7 regions, 3 hour transport
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4 region
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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
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Existing geographic disparity
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4 district map reduces disparity
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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
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Liver forum – ad hoc subcommittees
• Metrics of diparity• Logistics• Finances
• Increased donation and utilization
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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
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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
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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