Increasing Organ Use through Performance Metrics

Performance Metrics

Increasing Organ Use through Performance Metrics

By: Krista Lentine, MD, Ph.D.

The current Fall Regional meetings bring a reminder that re-evaluation of the OPTN/UNOS Strategic Plan has begun. Every 3 years, the OPTN/UNOS articulates a strategic plan to establish priorities for the organization, its mission, and US transplant practice.1 “Increasing transplantation” is the leading goal in the 2015-2018 plan, and will likely continue to be highly prioritized. Notably, the revision to the US Kidney Allocation System (KAS) in December 2014 has been successful in achieving key goals of improved access for highly sensitized candidates and matching of the highest quality kidneys to patients most likely to benefit.2  However, the discard rate of recovered kidneys remains high, and even increased slightly under the new KAS. Currently, 20% of recovered kidneys are discarded, and the discard rate rises sharply with measures of donor “risk”, such that 55% of organs with a kidney donor profile index (KDPI) score>85% are discarded. The primary focus of regulatory organizations on post-transplant outcomes has been recognized as a driver of conservative organ and candidate selection and thus a barrier to full use of potentially transplantable organs.3

A new study by Wey et al. provides perspective on the discard dilemma by examining the impact of offer acceptance behavior on discards, cold ischemia time (CIT), and exports.4 The authors examined kidney offers from donors in the Scientific Registry of Transplant Recipients (SRTR) database from July 2015 to June 2016 and created a logistic regression model to quantify the odds of acceptance for candidates waitlisted in a donation service area (DSA). Key findings include: 1) Association of lower DSA- specific offer acceptance ratio with more discards. For a median donor, DSAs with the highest acceptance ratios place 0.12 more kidneys per donor than DSAs with the lowest ratio. 2) Low offer acceptance ratios are associated with 2.9 hours longer CIT for an average donor compared to DSAs with high acceptance ratios. 3) Low acceptance ratios are associated with 15% higher probability of organ exports.

Isolating the impact of program-specific offer acceptance on allocation efficiency is admittedly challenging because of the complexities of organ allocation. Organs are recovered and allocated by Organ Procurement Organizations (OPOs) that serve DSAs, not individual transplant programs. Because DSAs typically serve multiple programs, the program responsible for eventual organ placement or discard is affected by the decisions of other programs through a sequence of offers and decisions. Nonetheless, the acceptance behavior of kidney transplant programs has an important, modifiable role in allocation efficiency. In their article, Wey et al. discuss the possibility of expanded public reporting as a route to improve offer acceptance. Such reporting could include program-specific offer acceptance ratios for all donors and by key subgroups in the SRTR Program Specific Reports (PSRs), and/or provision of program-specific offer acceptance rates to OPOs to guide expedited placement by directing offers to the programs most likely to accept. Development and enforcement of more robust OPO performance metrics is also a topic of active discussion.5

As the community moves forward in discussions of an updated OPTN/UNOS Strategic Plan and the framework of priorities for our field, it is clear we are shifting from a dominant focus on post-transplant outcomes alone to more comprehensive metrics of transplant access and organ use. Transplant Rate is already available in the SRTR PSRs, and may gain heightened attention – more complex transplant rate risk adjustment methodology was recently posted on the SRTR website.6 On September 18, 2017, the SRTR announced plans to work towards incorporating offer acceptance rates in the PSRs for all organs. Thus, while monitoring patient and graft survival remains critical, it is likely that transplant programs will also need to attend to organ acceptance and transplant rates in their QAPI efforts to maintain good regulatory standing. By tracking and responding to key performance metrics, and collaborating with our OPOs and neighboring centers, together we can work to ensure optimal transplant options for the patients we serve.

 

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References

  1. OPTN/UNOS 2018-2021 Strategic Planning Process. Available at: https://www.transplantpro.org/search-results/?q=strategic%20planning. Accessed: October 3, 2017.
  2. Hart A, Gustafson S, Skeans M, et al. OPTN/SRTR 2015 Annual Data Report: Early effects of the new kidney allocation system. American Journal of Transplantation 2017;17:543-64.
  3. Schold JD, Buccini LD, Poggio ED, Flechner SM, Goldfarb DA. Association of Candidate Removals From the Kidney Transplant Waiting List and Center Performance Oversight. American Journal of transplantation 2016;16:1276-84.
  4. Wey A, Salkowski N, Kasiske BL, Israni AK, Snyder JJ. Influence of kidney offer acceptance behavior on metrics of allocation efficiency. Clin Transplant 2017;31.
  5. Goldberg D, Kallan MJ, Fu L, et al. Changing Metrics of Organ Procurement Organization Performance in Order to Increase Organ Donation Rates in the United States. American Journal of Transplantation 2017 [EPub ahead of print]
  6. SRTR Risk Adjustment Model Documentation. Available at: https://www.srtr.org/reports-tools/risk-adjustment-models-transplant-programs/. Accessed: October 3, 2017.
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