Liver sharing and organ procurement organization performance

Evaluating Spatial Associations in Inpatient Deaths Between Organ Procurement Organizations

To improve the measurement of organ procurement organization (OPO) performance, the Center for Medicare and Medicaid Services recently proposed using inpatient deaths defined as the eligible pool of organ donors within an OPO as patients 75 years or younger that died from any cause that would not preclude donation.

METHODS

To account for the geographic variation in OPO performance and organ availability across the United States, we utilized spatial analysis to appraise the newly proposed metric of inpatient deaths.

RESULTS

Using spatial clustering that accounts for geographic relationships between Organ Procurement Organizations, the top 5 causes of donation-eligible death, and inpatient deaths, we identified 4 unique OPO clusters. Each group had a distinct demographic composition, cause of death, and inpatient death pattern. In multivariate analysis accounting for these geographic relationships, the spatial clusters remained significantly associated with the outcome of inpatient deaths (P < 0.001) and were the best-fitting model compared with models without the spatial clusters; this suggests that further risk adjustment of inpatient deaths should include these geographic considerations.

CONCLUSIONS

This approach provides not only a manner to assess donor potential by improving risk adjustment but also an opportunity to further explore geographic and spatial relationships in the practice of organ transplantation and OPO performance.

Assessment of National Organ Donation Rates and Organ Procurement Organization Metrics

Importance

Organ transplant is a life-saving procedure for patients with end-stage organ failure. In the US, organ procurement organizations (OPOs) are responsible for the evaluation and procurement of organs from donors who have died; however, there is controversy regarding what measures should be used to evaluate their performance.

Objective

To evaluate OPO performance metrics using combined mortality and donation data and quantify the associations of population demographics with donation metrics.

Design, Setting, and Participants

This national cohort study includes data from the US organ transplantation system from January 2008 through December 2017. All individuals who died within the US, as reported by the National Death index, were included.

Exposures

Death, organ donation, and donation eligibility.

Main Outcomes and Measures

Evaluation of the variation in donation metrics and the use of ineligible donors by OPO and demographic subgroup.

Results

This study included 17 501 742 deaths and 75 769 deceased organ donors (45 040 men [59.4%]; 51 908 White individuals [68.5%]). Of these donors, 15 857 (20.9%) were not eligible, as defined by the OPOs. The median donation metrics by OPO were 0.004 (range, 0.002-0.012) donors per death, 0.89 (range, 0.68-1.30) donors per eligible death, and 0.72 (range, 0.57-0.86) eligible donors per eligible death. The OPOs in the upper quartile of the overall eligible donors per eligible death metric were in the upper quartile of annual rankings on 90 of 140 occasions (64.3%). There was little overlap in top-performing OPOs between metrics; an OPO in the upper quartile for 1 metric was also in the upper quartile for the other metrics on 37 of 570 occasions (6.5% of the time). The median donor eligibility rate, defined as the number of eligible donors per donor, was 0.79 (range, 0.61-0.95) across OPOs. Age (eg, 65 to 84 years, coefficient, -0.55 [SE, 0.03]; P < .001; vs those aged 18 to 34 years), sex (male individuals, -0.09 [SE, 0.02]; P < .001; vs female individuals), race (eg, Black individuals, 0.35 [SE, 0.02]; P < .001; vs White individuals), cause of death (eg, central nervous system tumor, 0.48 [SE, 0.08]; P < .001; vs anoxia), year (eg, 2016-2017: -0.10 [SE, 0.03]; P < .001; vs 2008-2009), and OPO were associated with the use of ineligible donors; OPO was a significant factor associated with performance in all metrics (χ256, 500.5; P < .001; coefficient range across individual OPOs, -0.15 [SE, 0.09] to 0.75 [SE, 0.09]), even after accounting for population differences. Female and non-White individuals were significantly less likely to be used as ineligible donors.

Conclusions and Relevance

We demonstrate significant variability in OPO performance rankings, depending on which donation metric is used. There were significant differences in OPO performance, even after accounting for differences in potential donor populations. Our data suggest significant variation in use of ineligible donors among OPOs, a source for increased donors. The performance of OPOs should be evaluated using a range of donation metrics.

Estimating the effect of focused donor registration efforts on the number of organ donors

Waiting times for organs in the United States are long and vary widely across regions. Donor registration can increase the number of potential donors, but its effect on the actual number of organ transplants depends upon several factors. First among these factors is that deceased donor organ donation requires both that death occur in a way making recovery possible and that authorization to recover organs is obtained. We estimate the potential donor death rate and donor authorization rate conditional on potential donor death by donor registration status for each state and for key demographic groups. With this information, we then develop a simple measure of the value of a new donor registration. This combined measure using information on donor authorization rates and potential death rates varies widely across states and groups, suggesting that focusing registration efforts on high-value groups and locations can significantly increase the overall number of donors. Targeting high-value states raises 26.7 percent more donors than a uniform, nationwide registration effort. Our estimates can also be used to assess alternative, but complementary, policies such as protocols to improve authorization rates for non-registered potential donors.

Importance of incorporating standardized, verifiable, objective metrics of organ procurement organization performance into discussions about organ allocation

Identifying and supporting specific organ procurement organizations (OPOs) with the greatest opportunity to increase donation rates could significantly increase the number of organs available for transplant. Accomplishing this is complicated by current Scientific Registry of Transplant Recipients/Centers for Medicare & Medicaid Services metrics of donation rates and OPO performance that rely on eligible deaths. These data are self-reported and unverifiable and have been shown to underestimate potential organ donors. We examine the limitations of current OPO performance/donation metrics to inform discussions related to strategies to increase donation. We propose changing to a simple, verifiable, and uniformly applied donation metric. This would allow the transplant community to (1) better understand inherent differences in donor availability based on geography and (2) identify underperforming areas that would benefit from systems improvement agreements to increase donation rates.

Patterns of geographic variability in mortality and eligible deaths between organ procurement organizations

Eligible deaths are currently used as the denominator of the donor conversion ratio to mitigate the effect of varying mortality patterns in the populations served by different organ procurement organizations (OPOs). Eligible death is an OPO-reported metric rather than a product of formal epidemiological analysis, however, and may be confounded with OPO performance. Using Scientific Registry of Transplant Recipients and Centers for Disease Control and Prevention data, patterns of mortality and eligible deaths within each OPO were analyzed with the use of formal geostatistical analysis to determine whether eligible deaths truly reflect the geographic patterns they are intended to mitigate. There was a 2.1-fold difference in mortality between the OPOs with the highest and lowest rates, with significant positive spatial autocorrelation evident in mortality rates (Moran I = .110; P < .001), meaning geographically proximate OPOs tended to have similar mortality rates. The eligible death ratio demonstrated greater variability, with a 4.5-fold difference between the OPOs with the highest and lowest rates. Contrary to the pattern of mortality rates, the geographic distribution of eligible deaths among OPOs was random (Moran I = -.002; P = .410). This finding suggests geographic patterns do not play a significant role in eligible deaths, thus questioning its continuing use in OPO performance comparisons.

Geographic disparities in liver supply/demand ratio within fixed-distance and fixed-population circles

Recent OPTN proposals to address geographic disparity in liver allocation have involved circular boundaries: the policy selected 12/17 allocated to 150-mile circles in addition to DSAs/regions, and the policy selected 12/18 allocated to 150-mile circles eliminating DSA/region boundaries. However, methods to reduce geographic disparity remain controversial, within the OPTN and the transplant community. To inform ongoing discussions, we studied center-level supply/demand ratios using SRTR data (07/2013-06/2017) for 27 334 transplanted deceased donor livers and 44 652 incident waitlist candidates. Supply was the number of donors from an allocation unit (DSA or circle), allocated proportionally (by waitlist size) to the centers drawing on these donors. We measured geographic disparity as variance in log-transformed supply/demand ratio, comparing allocation based on DSAs, fixed-distance circles (150- or 400-mile radius), and fixed-population (12- or 50-million) circles. The recently proposed 150-mile radius circles (variance = 0.11, P = .9) or 12-million-population circles (variance = 0.08, P = .1) did not reduce the geographic disparity compared to DSA-based allocation (variance = 0.11). However, geographic disparity decreased substantially to 0.02 in both larger fixed-distance (400-mile, P < .001) and larger fixed-population (50-million, P < .001) circles (P = .9 comparing fixed distance and fixed population). For allocation circles to reduce geographic disparities, they must be larger than a 150-mile radius; additionally, fixed-population circles are not superior to fixed-distance circles.

By the Contributors to the C4 Article (Appendix 1). Current opinions in organ allocation

Existing methods of academic publication provide limited opportunity to obtain stakeholder input on issues of broad interest. This article reports the results of an experiment to produce a collaborative, crowdsourced article examining a current controversial issue in transplant medicine (hereby referred to as the "C4 Article"). The editorial team as a whole selected the topic of organ allocation, then divided into six sections, each supported by an individual editorial team. Widely promoted by the American Journal of Transplantation, the C4 Article was open for public comment for 1 month. The nonblinded editorial teams reviewed the contributions daily and interacted with contributors in near-real time to clarify and expand on the content received. Draft summaries of each section were posted and subsequently revised as new contributions were received. One hundred ninety-four individuals viewed the manuscript, and 107 individuals contributed to the manuscript during the submission period. The article engaged the international transplant community in producing a contemporary delineation of issues of agreement and controversy related to organ allocation and identified opportunities for new policy development. This initial experience successfully demonstrated the potential of a crowdsourced academic manuscript to advance a broad-based understanding of a complex issue.

Offer acceptance practices and geographic variability in allocation model for end-stage liver disease at transplant

Offer acceptance practices may cause geographic variability in allocation Model for End-Stage Liver Disease (aMELD) score at transplant and could magnify the effect of donor supply and demand on aMELD variability. To evaluate these issues, offer acceptance practices of liver transplant programs and donation service areas (DSAs) were estimated using offers of livers from donors recovered between January 1, 2016, and December 31, 2016. Offer acceptance practices were compared with liver yield, local placement of transplanted livers, donor supply and demand, and aMELD at transplant. Offer acceptance was associated with liver yield (odds ratio, 1.32; P < 0.001), local placement of transplanted livers (odds ratio, 1.34; P < 0.001), and aMELD at transplant (average aMELD difference, -1.62; P < 0.001). However, the ratio of donated livers to listed candidates in a DSA (ie, donor-to-candidate ratio) was associated with median aMELD at transplant (r = -0.45; P < 0.001), but not with offer acceptance (r = 0.09; P = 0.50). Additionally, the association between DSA-level donor-to-candidate ratios and aMELD at transplant did not change after adjustment for offer acceptance. The average squared difference in median aMELD at transplant across DSAs was 24.6; removing the effect of donor-to-candidate ratios reduced the average squared differences more than removing the effect of program-level offer acceptance (33% and 15% reduction, respectively). Offer acceptance practices and donor-to-candidate ratios independently contributed to geographic variability in aMELD at transplant. Thus, neither offer acceptance nor donor-to-candidate ratios can explain all of the geographic variability in aMELD at transplant. Liver Transplantation 24 478-487 2018 AASLD.

Geographic variation in liver transplantation persists despite implementation of Share35

AIM

Geographic disparities persist in the USA despite locoregional organ sharing policies. The impact of national organ sharing policies on waiting-list mortality on a regional basis remains unknown.

METHODS

Data on all adult liver transplants between 1 February 2002 and 31 March 2015 were obtained from the United Network for Organ Sharing/Organ and Transplantation Network. Multivariable Cox proportional hazards models were constructed in a time-to-event analysis to estimate waiting-list mortality for the pre- and post-Share35 eras.

RESULTS

In the analyzed time period, 134 247 patients were listed for transplantation and 54 510 received organs (42.8%). Listing volume increased following the introduction of the Share35 organ sharing policy (15 976 candidates pre- vs. 18 375 post) without significant regional changes as did the number of transplants (7210 pre- vs. 8224 post). Waiting-list mortality improved from 12.2% to 8.1% (P < 0.001). Adjusted waiting-list mortality ratios remained geographically disparate. Region 10 and region 11 had lower hazard ratios (HR) but still had increased mortality (1.46, 95% confidence interval [CI] 1.34-1.60, P < 0.001; and HR 1.49, 95% CI 1.37-1.62, P < 0.001, respectively). Regions 3 and 6 had increased HR with persistently elevated waiting-list mortality (1.79, 95% CI 1.66-1.93, P < 0.001; and HR 1.29, 95% CI 1.16-1.45, P < 0.001, respectively). Model for End-state Liver Disease (MELD) exception continued to propagate a survival benefit (HR 0.65, 95% CI 0.63-0.68, P < 0.001).

CONCLUSIONS

Although overall waiting-list mortality has decreased, geographic disparities persist, but appear reduced despite broader sharing policies enacted by Share35. The advantage afforded by MELD exception, while still present, was diminished by Share35 as organs are being shifted to MELD >35 candidates. The disparities highlighted by our findings imply a need to review current allocation policies to best balance local, regional, and national transplant environments.

Outcomes and disparities in liver transplantation will be improved by redistricting-cons

PURPOSE OF REVIEW

Over the last 2 years, the liver transplant community has been debating a proposal to redraw the maps of organ distribution. The basis for these proposed changes is reported disparities in severity of illness at transplantation across the USA - however, this is based on the allocation model for end-stage liver disease score. In this review, we provide a critical overview of the redistribution proposal, its flaws and how it may worsen outcomes and exacerbate disparities in liver transplantation.

RECENT FINDINGS

The main findings we highlight are data questioning the disparity metric used to justify the redistribution. We also review data published in recent articles and presented at public forums questioning whether there truly are disparities in access to transplant care among the broader population with liver disease, and whether disparities even getting to the waitlist are important and not to be ignored.

SUMMARY

This review article highlights major methodological and policy flaws with the current redistribution proposal. We demonstrate how the waitlist disparities that the proposal is intended to fix are not as they seem. Furthermore, if this proposal is passed, outcomes of liver transplantation nationally may worsen, and disparities for those with limited access to healthcare will worsen.

A Concentric Neighborhood Solution to Disparity in Liver Access That Contains Current UNOS Districts

BACKGROUND

Policymakers are deliberating reforms to reduce geographic disparity in liver allocation. Public comments and the United Network for Organ Sharing Liver and Intestinal Committee have expressed interest in refining the neighborhoods approach. Share 35 and Share 15 policies affect geographic disparity.

METHODS

We construct concentric neighborhoods superimposing the current 11 regions. Using concepts from concentric circles, we construct neighborhoods for each donor service area (DSA) that consider all DSAs within 400, 500, or 600 miles as neighbors. We consider limiting each neighborhood to 10 DSAs and use no metrics for liver supplies and demands. We change Model for End-Stage Liver Disease (MELD) thresholds for the Share 15 policy to 18 or 20 and apply 3- and 5-point MELD proximity boosts to enhance local priority, control travel distances, and reduce disparity. We conduct simulations comparing current allocation with the neighborhoods and sharing policies.

RESULTS

Concentric neighborhoods structures provide an array of solutions where simulation results indicate that they reduce geographic disparity, annual mortalities, and the airplane travel distances by varying degrees. Tuning of the parameters and policy combinations can lead to beneficial improvements with acceptable transplant volume loss and reductions in geographic disparity and travel distance. Particularly, the 10-DSA, 500-mile neighborhood solution with Share 35, Share 15, and 0-point MELD boost achieves such while limiting transplant volume losses to below 10%.

CONCLUSIONS

The current 11 districts can be adapted systematically by adding neighboring DSAs to improve geographic disparity, mortality, and airplane travel distance. Modifications to Share 35 and Share 15 policies result in further improvements. The solutions may be refined further for implementation.

Inequity in organ allocation for patients awaiting liver transplantation: Rationale for uncapping the model for end-stage liver disease

BACKGROUND & AIM

The goal of organ allocation is to distribute a scarce resource equitably to the sickest patients. In the United States, the Model for End-stage Liver Disease (MELD) is used to allocate livers for transplantation. Patients with greater MELD scores are at greater risk of death on the waitlist and are prioritized for liver transplant (LT). The MELD is capped at 40 however, and patients with calculated MELD scores >40 are not prioritized despite increased mortality. We aimed to evaluate waitlist and post-transplant survival stratified by MELD to determine outcomes in patients with MELD >40.

METHODS

Using United Network for Organ Sharing data, we identified patients listed for LT from February 2002 through to December 2012. Waitlist candidates with MELD ⩾40 were followed for 30days or until the earliest occurrence of death or transplant.

RESULTS

Of 65,776 waitlisted patients, 3.3% had MELD ⩾40 at registration, and an additional 7.3% had MELD scores increase to ⩾40 after waitlist registration. A total of 30,369 (46.2%) underwent LT, of which 2,615 (8.6%) had MELD ⩾40 at transplant. Compared to MELD 40, the hazard ratio of death within 30days of registration was 1.4 (95% CI 1.2-1.6) for patients with MELD 41-44, 2.6 (95% CI 2.1-3.1) for MELD 45-49, and 5.0 (95% CI 4.1-6.1) for MELD ⩾50. There was no difference in 1- and 3-year survival for patients transplanted with MELD >40 compared to MELD=40. A survival benefit associated with LT was seen as MELD increased above 40.

CONCLUSIONS

Patients with MELD >40 have significantly greater waitlist mortality but comparable post-transplant outcomes to patients with MELD=40 and, therefore, should be given priority for LT. Uncapping the MELD will allow more equitable organ distribution aligned with the principle of prioritizing patients most in need. Lay summary: In the United States (US), organs for liver transplantation are allocated by an objective scoring system called the Model for End-stage Liver Disease (MELD), which aims to prioritize the sickest patients for transplant. The greater the MELD score, the greater the mortality without liver transplant. The MELD score, however, is artificially capped at 40 and thus actually disadvantages the sickest patients with end-stage liver disease. Analysis of the data advocates uncapping the MELD score to appropriately prioritize the patients most in need of a liver transplant.

Same policy, different impact: Center-level effects of share 35 liver allocation

Early studies of national data suggest that the Share 35 allocation policy increased liver transplants without compromising posttransplant outcomes. Changes in center-specific volumes and practice patterns in response to the national policy change are not well characterized. Understanding center-level responses to Share 35 is crucial for optimizing the policy and constructing effective future policy revisions. Data from the United Network for Organ Sharing were analyzed to compare center-level volumes of allocation-Model for End-Stage Liver Disease (aMELD) ≥ 35 transplants before and after policy implementation. There was significant center-level variation in the number and proportion of aMELD ≥ 35 transplants performed from the pre- to post-Share 35 period; 8 centers accounted for 33.7% of the total national increase in aMELD ≥ 35 transplants performed in the 2.5-year post-Share 35 period, whereas 25 centers accounted for 65.0% of the national increase. This trend correlated with increased listing at these centers of patients with Model for End-Stage Liver Disease (MELD) ≥ 35 at the time of initial listing. These centers did not overrepresent the total national volume of liver transplants. Comparison of post-Share 35 aMELD to calculated time-of-transplant (TOT) laboratory MELD scores showed that only 69.6% of patients transplanted with aMELD ≥ 35 maintained a calculated laboratory MELD ≥ 35 at the TOT. In conclusion, Share 35 increased transplantation of aMELD ≥ 35 recipients on a national level, but the policy asymmetrically impacted practice patterns and volumes of a subset of centers. Longer-term data are necessary to assess outcomes at centers with markedly increased volumes of high-MELD transplants after Share 35. Liver Transplantation 23 741-750 2017 AASLD.

Liver sharing and organ procurement organization performance under redistricted allocation

Concerns have been raised that optimized redistricting of liver allocation areas might have the unintended result of shifting livers from better-performing to poorer-performing organ procurement organizations (OPOs). We used liver simulated allocation modeling to simulate a 5-year period of liver sharing within either 4 or 8 optimized districts. We investigated whether each OPO's net liver import under redistricting would be correlated with 2 OPO performance metrics (observed to expected liver yield and liver donor conversion ratio), along with 2 other potential correlates (eligible deaths and incident listings above a Model for End-Stage Liver Disease score of 15). We found no evidence that livers would flow from better-performing OPOs to poorer-performing OPOs in either redistricting scenario. Instead, under these optimized redistricting plans, our simulations suggest that livers would flow from OPOs with more-than-expected eligible deaths toward those with fewer-than-expected eligible deaths and that livers would flow from OPOs with fewer-than-expected incident listings to those with more-than-expected incident listings; the latter is a pattern that is already established in the current allocation system. Redistricting liver distribution to reduce geographic inequity is expected to align liver allocation across the country with the distribution of supply and demand rather than transferring livers from better-performing OPOs to poorer-performing OPOs.