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We’ve come together in Omaha … From many different places...

The Importance of Transplant Data Through the Lens of Policy Development , Performance Oversight, and Quality Monitoring. Jon Snyder, PhD Director of Transplant Epidemiology Chronic Disease Research Group Minneapolis Medical Research Foundation.

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We’ve come together in Omaha … From many different places...

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  1. The Importance of Transplant Data Through the Lens of Policy Development, Performance Oversight, and Quality Monitoring Jon Snyder, PhDDirector of Transplant EpidemiologyChronic Disease Research GroupMinneapolis Medical Research Foundation

  2. We’ve come together in Omaha…From many different places... OUI, Omaha, NE, September 2016

  3. A bit about me…How did I arrive here? = OUI, Omaha, NE, September 2016

  4. A bit about me… Director of Transplant Epidemiology OUI, Omaha, NE, September 2016

  5. HRSA Contracts & Contractors in the Field of Transplantation Solid Organ Transplantation Stem Cell Transplantation OUI, Omaha, NE, September 2016

  6. My other activities in the field:Member of the Board of Directors: Associate Journal Editor: OUI, Omaha, NE, September 2016

  7. A bit about you… OUI, Omaha, NE, September 2016

  8. Let’s go through the lens… OUI, Omaha, NE, September 2016

  9. Let’s go through the lens… Data DataUse & Inference Excellent Program #1 DataAnalyses Excellent Program #2 Excellent Program #3 Excellent Program #4 -System -Policy -QAPI -Patients -Research -Oversight Excellent Program #5 Excellent Program #6 Excellent Program #7 Excellent Program #8 Excellent Program #9 Excellent Program #10 Excellent Program #N OUI, Omaha, NE, September 2016

  10. Uses of Data OUI, Omaha, NE, September 2016

  11. The Primary Use of Data:Healing and Saving Lives! UNetSM Transplant Programs Waitlist OPOs TIEDI Match TransplantRecipient Histo-compatibility Labs DonorNet OUI, Omaha, NE, September 2016

  12. Transplants in 2015: 30,969! Data: www.unos.org, accessed 9/10/2016 OUI, Omaha, NE, September 2016

  13. Waiting List as of July 29, 2016: 119,902 Data: www.unos.org, accessed 9/10/2016 OUI, Omaha, NE, September 2016

  14. The Demand-to-Supply Gap Data: www.unos.org, accessed 9/10/2016 OUI, Omaha, NE, September 2016

  15. Uses of Data OUI, Omaha, NE, September 2016

  16. OPTN Committees OUI, Omaha, NE, September 2016

  17. Uses of Transplant Data for Informing Policy OUI, Omaha, NE, September 2016

  18. Policy Development Example:Redesigning Liver Distribution OUI, Omaha, NE, September 2016

  19. Geographic Disparity in MELD at Transplant by DSA OUI, Omaha, NE, September 2016

  20. Liver Redistricting Proposal Currently Out for Public Comment • The primary goal of this proposal is to improve geographic disparity in access to liver transplant. • The Final Rule states that access to transplant “shall not be based on the candidate’s place of residence or place of listing.” • However, among the current OPTN/UNOS regions the difference in median MELD at transplant is as great as 9 points (34 vs 25), the equivalent of a 50 percentage point difference in the estimated risk of 3-month mortality without a liver transplant. Source: https://optn.transplant.hrsa.gov/media/1913/liver_redesigning_liver_distribution_20160815.pdf OUI, Omaha, NE, September 2016

  21. Organ availability • Transport time limitations and geographic boundaries prevent some organs from reaching the highest-priority candidates • If each liver were teleported instantaneously to the highest-priority candidate anywhere in the country, that allocation system would be one where geography has no influence

  22. Balancing supply and demand • Geographic disparities in organ availability are caused by uneven distribution of liver disease, listings, and eligible deaths • Eligible deaths vary 4-fold among DSAs • Listings for liver transplant vary 14-fold among DSAs[Gentry et al. Liver sharing and organ procurement organization performance. Liver Trans 21(3) 2015] • Deaths due to liver disease vary 19-fold among DSAs[Adler et al. Role of patient factors and practice patterns in determining access to liver waitlist. Am J Trans 2015]

  23. OPO performance • OPO performance metrics vary by less than 2-fold across DSAs • Geographic disparities are not correlated with organ procurement organization performance[Gentry et al. Liver sharing and organ procurement organization performance. Liver Transplantation 21(3) 2015] • If all OPOs had 100% conversion rate, huge differences in supply and demand would remain • OPO performance improvements can increase transplants but can not resolve geographic imbalance in supply and demand

  24. Broader sharing is not sufficient to reduce disparity -- actually worse with existing regions • Fully regional sharing is not predicted to reduce disparity in MELD at transplant; paradoxically, fully regional sharing increases disparity [Gentry et al. Am J Trans 2013] • Share-35 is a partial step toward regional sharing in the existing regions. Actual data from Share-35 shows increase in disparity of median MELD at transplant. Disparity with fully regional sharing

  25. Liver Committee’s design constraints • Districts should respect the existing DSA boundaries and should be contiguous. • The number of districts should be at least 4 and no more than 8. • The maximum median transplant-volume-weighted transport time between DSAs is 3 hours. • Each district must contain at least 6 transplant centers. • Districts should be designed to minimize geographic disparity, and must not increase waitlist death.

  26. Optimized 8 District Map

  27. Optimized 4 District Map

  28. Maps of median MELD/PELD at transplant by DSA:Current Policy vs. 8-District Sharing

  29. Projected Impact of Redistricting to the 8 District Solution • The 8 district model is projected to cut the current variance in median MELD or PELD at transplant in half (2.9 vs. 6.2). • Median transport time increases from 1.7 hours to 1.8 hours. • Median transport distance increases from 124 to 200 miles • Percentage of organs flown increases from 54% to 68%. Source: https://optn.transplant.hrsa.gov/media/1913/liver_redesigning_liver_distribution_20160815.pdf OUI, Omaha, NE, September 2016

  30. Uses of Data OUI, Omaha, NE, September 2016

  31. SRTR’s CUSUM charts

  32. Why is SRTR providing CUSUM charts? Consensus Conference Recommendation I.4: Provide transplant centers, the MPSC and CMS with tools such as the cumulative sum (CUSUM) technique and tools to allow subgroup analysis to facilitate quality assessment and performance improvement.

  33. Two-sided (O minus E) CUSUM

  34. Two-sided (O minus E) CUSUM A period of experiencing graft failures at about the expected rate.

  35. Two-sided (O minus E) CUSUM A period of experiencing graft failures at a rate lower than expected.

  36. Two-sided (O minus E) CUSUM A period of experiencing graft failures at a rate higher than expected.

  37. When to be concerned? The one-sided CUSUM The trigger line indicating when to be potentially concerned.

  38. CUSUM production by the SRTR • Available at https://securesrtr.transplant.hrsa.gov • Released the first business day of every month starting 7/1/2013 • For all kidney, heart, liver and lung programs

  39. Uses of Data OUI, Omaha, NE, September 2016

  40. The Final Rule (b) Reporting requirements. (1) The OPTN and the Scientific Registry, as appropriate, shall: … (iv) Make available to the public timely and accurate program-specific information on the performance of transplant programs. This shall include free dissemination over the Internet, and shall be presented, explained, and organized as necessary to understand, interpret, and use the information accurately and efficiently. OPTN Final Rule -Page 21- October 20, 1999 OUI, Omaha, NE, September 2016

  41. Current SRTR Website Presentation OUI, Omaha, NE, September 2016

  42. Outcomes Assessment Example:Graft Failure Outcome at Mayo Clinic, Scottsdale, AZ OUI, Omaha, NE, September 2016

  43. Initiatives in Patient-Friendly Presentation of Data • Completely redesigned SRTR website. • MMRF researchers, Dr. Israni & Dr. Schaffhausen, have an AHRQ-funded grant to develop patient-friendly report cards in partnership with the SRTR. • More to come… OUI, Omaha, NE, September 2016

  44. Uses of Data OUI, Omaha, NE, September 2016

  45. Both OPTN and SRTR make data available to Researchers OUI, Omaha, NE, September 2016

  46. OUI, Omaha, NE, September 2016

  47. OUI, Omaha, NE, September 2016

  48. Uses of Data OUI, Omaha, NE, September 2016

  49. Two Critical Elements Used to Evaluate Post-Transplant Outcomes: O & E OUI, Omaha, NE, September 2016

  50. How O & E Are Used • If you divide O by E (O/E), the resulting ratio describes how much higher or lower the event count is than expected. For example: • O/E = 1.5: 50% higher event count than expected. • O/E = 0.75: 25% lower event count than expected. • O/E = 1.00: event count is exactly as the models expect based on national experience for similar recipients and similar donors. OUI, Omaha, NE, September 2016

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