Access to Kidney Transplantation: In Search of Equipoise
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  • 1 Medical Director, Kidney and Pancreas TransplantationJohn C McDonald Regional Transplant CenterWillis-Knighton Health SystemShreveport, Louisiana
  • 2 Medical Director of Kidney and Kidney Pancreas TransplantationHenry Ford Health SystemDetroit, Michigan

“The greatest gift is a portion of thyself.”

Ralph Waldo Emerson

Kidney transplantation provides a longer life span, a better quality of life, and lower healthcare costs compared with long-term dialysis treatment. Kidney transplantation must be sought for all medically and psychosocially qualified patients with ESRD. Despite improvements in organ procurement and preservation, immunosuppressive medications, and graft and patient survival, the goal of equal access to kidney transplantation remains elusive. Although shortage and imbalance in the offer and demand of organs constitute the principal obstacles to access equipoise in kidney transplantation, multiple social, behavioral, cultural, racial, and ethnicity-related factors are associated with the extant lack of patient progress toward kidney transplantation.

Stewart et al. (1) have defined inequity in access to deceased donor organ transplants as “the degree to which disparities in rates of deceased donor organ transplantation exist among candidates on the waiting list for a particular organ, excluding intentional disparities attributable to candidate‐based priorities (e.g., pediatric status or medical urgency status) codified in allocation policy.” Several systematic and patient-related characteristics have been identified as barriers of access in kidney transplantation (210) (Table 1). Underserved populations, lower socioeconomic status, place of residence, race and ethnicity, older age, and cause of kidney disease are often linked to a lower rate of kidney transplantation despite the high burden of kidney disease in the affected populations. This disparity in access to transplantation will likely be aggravated by the increasing incidence and prevalence of these demographic and morbidity correlates nationwide.

Table 1.

Barriers in access to kidney transplantation

Older age
Racial minority
Limited health literacy
Female gender
Obesity
Diabetes mellitus
Lack of a living kidney donor
ABO blood types B or O
Lower income
Noncommercial insurance
Long distance to a transplantation center
Place of residence at listing
Late referral for transplantation
For-profit dialysis units
Unconscious patient and physician bias

Although the proportion of prevalent dialysis patients ineligible for kidney transplantation is imprecisely known, in 2016 only 15% of prevalent dialysis patients were waitlisted for a kidney transplant (9). The absence of access equipoise is being addressed by multiple dialysis and transplant regulatory agencies.

Effective in 2022, the Percentage of Prevalent Patients Waitlisted (PPPW) and the Standardized First Kidney Transplant Waitlist Ratio for incident dialysis patients (SWR) will be introduced as one component of the Conditions for Coverage for Medicare certification of ESRD dialysis facilities (11,12). These metrics constitute a gestalt of the waitlisting process as the requisite step of improvement of access to transplantation and incorporation of dialysis facilities as stakeholders in the progress of waitlisting.

As an access to kidney transplantation measure, PPPW tracks the percentage of patients at each dialysis facility on the kidney or kidney-pancreas transplant waiting list at the end of each month. The SWR tracks the number of incident patients under age 75 years listed on the kidney or kidney-pancreas transplant waitlist or those receiving a living donor transplant within the first year of initiating dialysis.

The intention of this editorial is to identify the barriers that affect patient access to transplantation and deliberate strategies that improve organ use and achieve equity in access to transplantation. Understanding the complexities facing dialysis patients during the waitlisting process is essential to establishing practice guidelines that target PPPW and SWR metrics.

Geographic Disparity in Access to Transplantation

The United States Department of Health and Human Services implemented a “Final Rule” in 1998 that established a regulatory framework for the structure and operations of the Organ Procurement and Transplantation Network (OPTN). The Final Rule states that “neither place of residence nor place of listing shall be a major determinant of access to a transplant.” However, a significant state-to-state disparity exists regarding access to the kidney waiting list and transplantation in the United States (8,9,13) (Figure 1). The disparity is not accounted for by differences in insurance, patient demographics, or cause of ESRD (8).

Figure 1.
Figure 1.

Geographic distribution of unadjusted transplant rate by state, 2016. Note that trends may be influenced by changes to the kidney allocation system (KAS) policy that were implemented in December 2014. Abbreviations: pt yrs; patient-years; tx, transplant. From United States Renal Data System. 2018 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2018.

Citation: Nephrology Self-Assessment Program nephsap 18, 5; 10.1681/nsap.2019.18.5.1

In 2011, the median waiting time to transplant for newly waitlisted candidates for a first or repeat kidney-alone transplant was 4.0 years (9). This waiting time varied greatly by region, from a low wait of 1.4 years in Nebraska to more than 5 years in Texas and Georgia (9).

Contrary to the purpose of the Final Rule, since inception, geographic disparities in waiting times, transplant rates, pretransplant mortality, and organ quality have worsened by approximately 30% (14). In particular, the southeastern United States has the lowest rate of kidney transplantation despite its disproportionately heavy burden of ESRD (15). This disparity in access to kidney transplantation is attributed to higher concentration of poverty, residential segregation, greater proportion of uninsured patients, lack of health education among both providers and patients, fewer transplantation centers, long distances to a transplantation center, for-profit dialysis facilities, and lower organ availability (15,16). The socioeconomic status of a potential recipient is an important contributor to geographic disparity. Patients with adequate education and financial means may travel to multiple centers for listing and transplantation in contrast to others of lesser economic means. The latter group typically restricts itself to local programs, consequently disadvantaged by fewer “organ opportunities,” particularly when residing in an area with prolonged wait times. The Southern dialysis networks, notably networks 6 (GA, NC, and SC), 8 (AL, MS, and TN), and 13 (AR, LA, and OK) exhibit the lowest facility-level standardized transplant ratios of all the ESRD networks (15).

The geographic location of waitlisted candidates also largely accounts for the racial disparities in waiting times for deceased donor kidney transplantation (DDKT) (17). The performance of organ procurement organizations (OPOs) or lack thereof plays a major role in these median wait time to transplant variations that range from 10–11 months to more than 72 months, placing patients living in areas with the longest wait time at a disadvantage (17). Two new metrics that measure geographic variation in DDKT rates across Donation Service Area (DSA) were recently introduced: access to transplant score (ATS) and the median incidence rate ratio. The ATS captures variability in access to DDKT based on various candidate factors such as age, race, ethnicity, sex, calculated panelreactive antibody (CPRA), ABO blood type, and DSA region (1). Using ATS, Stewart et al. (1) have shown that since the introduction of the Kidney Allocation System (KAS) in 2014, the DSA of a candidate's transplantation hospital has become the factor most associated with disparities in transplant access. This factor is followed by CPRA, blood type, and diagnosis of kidney disease. The ATS may be beneficial for frequent monitoring of equitability of deceased donor transplant access across disparate groups (18). A recent study using the median incidence rate ratio revealed that geographic inequity in DDKT has not decreased since the implementation of the KAS in 2014 (19).

Racial Disparity

Blacks are about 3.5 times more likely to experience ESRD than whites. Hispanics are about 1.5 times more likely to experience ESRD than non-Hispanics. Together, blacks and Hispanics constitute a majority (56%) of prevalent waitlisted ESRD patients, which is higher than their proportionate ESRD population (48%). However, it takes these minorities significantly longer time to waitlisting, in large part related to their lower socioeconomic status and fewer preemptive waitlisting (20). Historically, blacks have a lower kidney transplantation rate compared with whites. Disparities by race/ethnicity may be largely explained by insurance status and income, potentially suggesting that variable insurance coverage exacerbates disparities in access to transplantation in the ESRD population, despite Medicare entitlement (5).

Cultural behavior and attitudes toward the healthcare system also play an important role in access to transplantation. In a study of patients with newly diagnosed ESRD in Alabama, southern California, Michigan, and the mid-Atlantic region, Ayanian et al. (21) showed that blacks’ preference and experience with medical care were important determinants of access to transplantation. In this study, black patients were less likely than whites to want a kidney transplant, to be very certain about this preference, and to expect that their quality of life would improve with transplantation. Of particular interest to our community, blacks were less likely than whites to report that their primary nephrologist provided all the medical information they desired about transplantation or that a physician had discussed the possibility of receiving a kidney transplant from a living donor.

With the introduction of KAS in 2014, the racial/ethnic disparities in waitlisting and DDKT have decreased (22,23), and in 2016, the rates of DDKT for blacks were similar to those of whites (9). However, racial/ethnic disparities in the rates of living-donor kidney transplantation still exist and have increased in the past two decades, with living-donor kidney transplantation rate being the lowest for blacks compared with all other racial groups (9).

Barriers to transplantation for American Indians or Hispanics may be different from those in blacks. Sequist et al. (24) observed that prevalent dialysis patients in Arizona and New Mexico had similar referral rates for renal transplantation to whites, yet were less likely to be placed on the transplant waiting list or receive a transplant. In these populations, disparities were caused by barriers within the transplant evaluation process itself.

Implicit Physician Bias Regarding Benefits of Kidney Transplantation

Implicit bias about appropriateness of kidney transplantation is present in physicians, and correlates with unequal treatment of patients, even in the absence of explicit bias. Nephrologists’ views about the benefits of transplantation may affect how they present this treatment option to ethnic minorities or to patients with specific comorbidities.

Epstein et al. (25) investigated the appropriateness of dialysis patients as candidates for transplantation, and analyzed data on rates of referral for transplant evaluation, waitlisting, and transplantation according to race. Appropriateness of candidacy for transplantation was judged according to criteria established by a panel of experts. Nephrologists caring for study patients were asked to rate 18 coexisting disorders that were included in the appropriateness criteria as “critical” if the disorder alone would render transplantation inappropriate, “significant” if the disorder combined with other disorders would render transplantation inappropriate, or “incidental” if the disorder alone or with other disorders would generally not render transplantation inappropriate. There were racial differences for all indicators of access favoring the referral, waitlisting, and transplantation of white over black patients. Analysis of the pattern of referral and waitlisting of dialysis units showed that in high-referral dialysis facilities, 84.1% of blacks and 91.2% of whites were referred for evaluation (P=0.003), and 46.2% of blacks and 63.1% of whites were waitlisted (P<0.001). At low-referral facilities, 38.3% of blacks and 58.2% of whites were referred for evaluation (P<0.001), and 20.4% of blacks and 42.4% of whites were placed on the waiting list (P<0.001). Underuse or overuse of transplantation was also identified based on the treating nephrologist criteria of transplant appropriateness; underuse of transplantation was more frequent in blacks, whereas overuse was more frequent in whites. This observation indicates that disparities in transplantation partly stem from differences in the physician’s criteria of appropriateness for transplantation between whites and blacks.

Access to Transplantation for Veterans Affairs Patients

Patients with access to Veterans Affairs (VA) primary insurance coverage have universal coverage of immunosuppressive therapy, with low or absent copays after transplantation. With only seven VA kidney transplantation centers in the United States (Birmingham, AL; Bronx, NY; Houston, TX; Iowa City, IA; Nashville, TN; Pittsburgh, PA; and Portland, OR) (26), the limited number imposes travel constraints to veterans with ESRD and restricts their access to transplantation (6,27). Augustine et al. (6) found that VA patients had to travel a greater median distance to their transplantation center than those with other insurance payers (282 versus 22 miles). Also, the transplantation rate for VA patients was significantly lower than privately insured patients despite similar adjusted mortality rates. Recent legislation seeks to address the barriers to access to kidney transplantation for veterans, including the Veterans Access, Choice, and Accountability Act of 2014; Maintaining Internal Systems and Strengthening Integrated Outside Networks Act (MISSION Act) of 2018; and the Veterans Increased Choice for Transplanted Organs and Recovery (VICTOR) Act, which was passed by the US House of Representatives in November 2017 and referred to the Committee on Veterans Affairs in February 2018. The impact of these regulations remains to be established.

System-Related Barriers in Access to Kidney Transplantation

Organ Availability and Utilization

Organ donation figures show that 95% of adults in the United States support organ donation, but only 58% register to donate (28). The percentage of the adult population registered as donors (i.e., Donor Designation Share) varies from state to state (29). In 2017, more than 90% of adults in Alaska and Montana were registered as donors, compared with only 32% in New York.

Deceased kidney discard rate, defined as the percentage of kidneys recovered for the purpose of transplantation that are turned down by transplantation centers, contributes to organ shortage. Although the number of discarded kidneys increased immediately after KAS implementation, it later stabilized. In 2016, among the 19,135 kidneys that were recovered from deceased donors, 3423 (18%) were discarded for various reasons (9). Earlier analysis performed after the introduction of KAS showed that biopsy findings were the most common cause for organ discard. In a large database study, “biopsy findings” were cited as the reason for discard in 38.2% of discarded kidneys. Biopsy specimens from kidneys with increased odds of discard were often procured from older, female, black, obese, diabetic, hypertensive, or hepatitis C virus–positive donors (30).

Although the kidney biopsy is the “gold standard” to assess renal outcomes in patients with kidney disease, few studies have been done in individuals without kidney disease and measured normal kidney function. Using renal biopsy specimens from healthy living kidney donors, Bar et al. (31) found that limited histopathologic changes are common in healthy kidney donors around age 50 with normal kidney function. In this study of 109 kidney donor biopsy specimens, age and pack-years of smoking increased the risk of tubular atrophy, fibrosis, and arterial hyalinosis, with smoking having a stronger association with these findings than age.

The association of histologic findings from procurement biopsy specimens to renal transplantation outcomes is not significant. In a retrospective single-center study, Carpenter et al. (32) found procurement biopsy specimens to lack reproducibility and to be poor correlates of histology from reperfusion biopsy specimens. The discrepancy between procurement and reperfusion biopsy specimens was most pronounced in the report of the percentage of glomerulosclerosis. Furthermore, histologic findings of procurement biopsy specimens were not significantly associated with graft failure. In a subsequent study from this same group, Mohan et al. (33) found that although deceased donor kidneys with “suboptimal histology” had lower death censored outcomes after transplantation, 73.2% of deceased donor kidneys with “suboptimal histology” remained functional at 5 years, suggesting that discarding donated kidneys on the basis of histologic factors may be inappropriate.

Addressing the issue of organ discard on the basis of histology of preimplantation biopsy specimens, the 2018 National Kidney Foundation Consensus Conference to Decrease Kidney Discards recommended standardization of technical aspects of obtaining and interpreting deceased donor renal biopsy specimens and to use renal pathologists to improve decision making based on biopsy. To this end, a Banff working group was established in 2010 to develop consensus criteria for the interpretation of preimplantation biopsy specimens. This group surveyed renal pathologists through the Renal Pathology Society website and published in 2017 the results of their first study reporting histologic criteria for the gold standard interpretation of preimplantation kidney biopsy specimens (34). Compared with previous studies, the Banff group reported that good wedge biopsy specimens not restricted to the subcapsular cortex can be superior to needle biopsy specimen. The histologic parameters with good or fair reproducibility according to the workgroup are listed in Table 2. Two recommendations deserve special consideration: 1. Rigid histologic cutoffs (i.e., 20% glomerulosclerosis) should not be used in isolation to discard kidneys. 2. Rigorous reading of preimplantation biopsy specimens may have an incremental value over clinical assessment alone, given the low ability of kidney donor profile index (KDPI) to predict graft failure (KDPI C-statistic, 0.6).

Table 2.

Histopathologic parameters of preimplantation biopsy specimens with good or fair reproducibility

Number of glomeruli
Number of globally sclerosed glomeruli
Percentage of globally sclerosed glomerulia
Interstitial fibrosisb
Arteriosclerosisb

Identified as statistically significant parameter associated with graft function.

Interstitial fibrosis and arteriosclerosis can affect graft function.

In addition to reducing the rate of organ discard, several programs have been implemented in the United States and other countries to identify overlooked or underused organ donors. The American Society of Transplantation introduced the initiative “Power2Save” to encourage adult organ registration. Many European and South American countries have laws that make organ donation the default option at the time of death. To avoid organ procurement at death, individuals must explicitly opt out of organ donation while they are still alive. This policy of presumed consent has been demonstrated to increase organ donation rates (35,36). However, such a policy runs contrary to the idea of altruism and individual autonomy enshrined in the Uniform Anatomical Gift Act of 2006 (37) and is currently not supported in the United States (38).

Performance of Organ Procurement Organizations

In the United States, OPOs are tasked with managing the organ procurement and recovery process in their DSAs. Performance of OPOs is highly variable and cannot be explained by local demographics (39) (Figure 2).

Figure 2.
Figure 2.

Organs per potential donors per year, by Organ Procurement Organizations. From Reforming Organ Donation in America. Reprinted from reference 39 (Available at:

https://www.bridgespan.org/bridgespan/Images/articles/reforming-organ-donation-in-america/reforming-organ-donation-in-america-01-2019.pdf. Accessed May 11, 2019), which is available under the terms of the Creative Commons Attribution License.

Citation: Nephrology Self-Assessment Program nephsap 18, 5; 10.1681/nsap.2019.18.5.1

The Centers for Medicare and Medicaid Services (CMS) evaluates OPOs every 4 years. Although no OPO has been decertified for poor performance in the past 20 years, in January 2019 CMS did not renew its contract with the OPO for the greater New York City area, with jurisdiction over 13.5 million people and second largest in the country, because of poor performance. OPOs are evaluated on the number of organs procured per donor, which leads to older single-organ donors being overlooked, and the conversion rate calculated as a percentage of the number of actual donors divided by the number of eligible deaths. Given that the denominator in these metrics is self reported and subject to interpretation, the metrics are not considered objective or verifiable. In addition, there is a marked variability in organ donation rates per DSA (Figure 3) (40) and referrals of in-hospital deaths to OPOs.

Figure 3.
Figure 3.

Marked variability in organ donation rates across the United States. Data from the State Inpatient Databases (SIDs), which included hospital zip codes, allowed us to map the inpatient deaths to Donation Service Area (DSA) to estimate the donor potential within a DSA (the total donor potential for a given organ procurement organizations [OPO]). The donation rate was calculated as: (number of organ donors) / (“possible” deceased donors), with possible donors based on the methodology described above. As shown to the right, there was marked variability in organ donation rates, without geographic clustering, with areas of high donation (e.g., San Diego and Philadelphia) adjacent to areas of low donation (Los Angeles and New York). Reprinted with permission from reference 69 (Goldberg D, Kallan MJ, Fu L, Ciccarone M, Ramirez J, Rosenberg P, Arnold J, Segal G, Moritsugu KP, Nathan H, Hasz R, Abt PL: Changing metrics of organ procurement organization performance in order to increase organ donation rates in the United States. Am J Transplant 17: 3183–3192, 2017) and reference 70 (Available at: https://www.med.upenn.edu/goldberglab/data.html).

Citation: Nephrology Self-Assessment Program nephsap 18, 5; 10.1681/nsap.2019.18.5.1

In 2015, the Health Resources and Services Administration modified the OPTN contract for the purpose of identifying relevant data needed to calculate objective measures of OPO donation performance, i.e., the ability to convert a possible donor to an actual donor. Donation rate—a ratio of actual organ donors over a surrogate measure for the pool of possible organ donors—is currently being proposed as a future metric (Table 3).

Table 3.

CMS Requirements for OPO compliance with established outcome measures as determined by donation rate

Outcome measure oneDonation rate is not more than 1.5 standard deviations below the national mean.
Outcome measure twoDonation rate is not significantly lower than the expected donation rate estimated using  the Scientific Registry of Transplant Recipients (SRTR) statistical methodology.
Outcome measure three•Organ transplants per 100 donors is not significantly lower than the expected transplant rate estimated using SRTR risk-adjusted statistical methodology, O/E <0.9.and number of transplants under expected is over 10 organs.
•Number of organs to research per donor is not more than 1 standard deviation below the national mean.

CMS, Centers for Medicare and Medicaid Services; OPO, organ procurement organization.

Late Referral for Transplantation

As discussed previously, substantial variation exists among dialysis centers in the rates of referral for kidney transplantation (41). Some patients are not referred for transplantation because of the perception by healthcare providers of their ineligibility for transplantation. The upcoming SWR and PPPW metrics acknowledge and tackle this precise barrier. According to the PPPW metric, all prevalent patients, with the exception of those aged 75 or older and/or those admitted to a skilled nursing facility or hospice care during the month of evaluation, should be considered for transplantation referral. The choice of age as an exclusion for transplantation referral is controversial. In this regard, age should not be considered an absolute exclusion for referral for and/or transplantation, particularly in nondiabetic subjects with good functional status and/or access to living donor transplantation. As far as transplantation referral of incident dialysis patients is concerned, in addition to the PPPW exceptions, preemptive patients will not be included in the calculation of the SWR.

Another factor contributing to late referral is the lack of comprehensive transplantation education offered by dialysis units (42,43). In a study by Waterman et al. (44), only 18% of 170 dialysis centers reported having detailed discussions about transplantation with their patients. Centers providing transplantation information usually included a greater proportion of younger patients, had a nonprofit status, and were located in an urban area or close to a transplant center.

Historical and ongoing interventions attempted to address the issue of late referral and low waitlisting rate. In 2007, the National Kidney Foundation convened a Kidney Disease Outcomes Quality Initiative conference to promote early referral for transplantation and preemptive or early transplantation (i.e., within the first year of dialysis). This consensus conference proposed the implementation of early patient education and referral to transplantation centers coincident with creation of the vascular access with the goal of waitlisting early in the course of ESRD. Among their recommendations, the creation of performance benchmarks for nephrologists and dialysis providers to evaluate transplantation referral and waitlisting constitute the basis of the CMS PPPW and SWR metrics. Moreover, the conference addressed the need for financial incentives to promote the stakeholder role of dialysis units in transplantation, including higher reimbursement rates for dialysis units with higher case mix–adjusted transplantation rates and better reimbursement to nephrologists for posttransplantation care relative to long-term dialysis.

The Allocation System Changes for Equity in Kidney Transplantation (ASCENT) study is an ongoing randomized, controlled, effectiveness-implementation trial estimated to enroll 600 dialysis facilities in the United States in all 18 ESRD networks with low waitlisting rates (45). The ASCENT study will demonstrate the feasibility and effectiveness of a multicomponent intervention designed to increase access to the deceased donor kidney waitlist and to reduce racial disparities in waitlisting.

The co-primary outcomes include change in waitlisting and waitlist disparity at 1 year; secondary outcomes include changes in facility medical director knowledge about KAS, staff training regarding KAS, patient education regarding transplantation, and the intent of the medical directors to refer patients for transplantation evaluation.

Variation in Transplantation Center Practices

The determination of patients’ candidacy for transplantation is a complex, tedious, and subjective process. Nearly 80% of patients may not make it to the waitlist (46). Often, time from referral to evaluation by transplantation centers is significantly delayed. In the absence of national guidelines, transplantation programs develop their own criteria for determination of patient suitability for waitlisting for transplantation (2). Such homegrown criteria are often vague and arbitrary, and inadequately consider the needs of the population they serve. There are substantial differences in transplantation programs’ acceptance practices with regard to age, body mass index, diabetes, cardiovascular disease, frailty, psychosocial support, insurance coverage, financial status, medical nonadherence, criminal record, mental retardation, and marijuana/other recreational drug use. The variability in acceptance criteria may stem from an underlying philosophy of the program (conservative versus risk taking), level of training of the surgeons, available resources (e.g., staff availability for the management of multiple posttransplantation delayed graft function patients), experience of the staff (e.g., comfort level with transplantation in highly sensitized patients), size of the transplantation program, or regulatory concerns. Small-volume programs may avoid performing transplantation in marginal patients because of the risk of poor outcomes and, possibly, being flagged.

The Kidney Disease Outcomes Quality Initiative conference on early transplantation recognized two major obstacles for early waitlisting: lack of efficiency in the evaluation process and inadequate communication between transplantation centers and referring nephrologists. Furthermore, the conference proposed standardization of transplantation evaluation protocols. The interval from referral to waitlisting would be just 6 weeks.

Significant practice variation exists across centers regarding willingness to accept an organ offer. Centers may have zero or low acceptance rates for deceased donor kidneys with high KDPIs, donor after cardiac death, high cold ischemia time, or procurement from donors infected with human immunodeficiency virus and/or hepatitis C virus or from US Public Health Service increased risk donors, which might deny some patients the opportunity of transplantation who otherwise might be eligible for these organs. In an analysis by Huml et al. (47), one-third of organ refusals were related to concerns about organ quality. Yet, a majority of these organs were eventually transplanted by other centers, suggesting underestimation of the organ quality, implicit bias, risk-averse behavior, and lack of oversight for the decision made at the centers refusing those organs (48). Also, organs procured on weekends versus weekdays are more likely to be discarded than transplanted, probably because of inadequate manpower and/or resources on the weekends (49). A significant center-level variation exists in the use of marginal kidney allografts (50,51). Zhou et al. (51) recently developed the Probability of Delay or Discard (PODD) model to identify marginal kidneys at risk of discard or delayed allocation beyond 36 hours of cold ischemia time. Use of high-PODD kidneys was clustered more tightly among a few centers; just 15 centers used them consistently. Of all high-PODD kidney offers, 35.0% were arguably unnecessarily made to centers that never accepted such kidneys. Prioritizing the allocation of high-PODD kidneys to centers that are more likely to accept and transplant them will reduce the number of discarded organs.

Regulatory Oversight

The fear of being flagged by CMS and United Network for Organ Sharing (UNOS) forces many centers to transplant only a few selected, healthy candidates. As a corollary, marginal but otherwise viable organs are declined. The centers that receive low-performance evaluations may thus become risk-averse, leading to reductions in transplant volume (52,53) and patient access to transplantation. Reducing transplant volumes may not result in measurable improvement in post-transplant outcomes (54). Even at low-performing centers, deceased donor kidney transplantation is associated with lower mortality compared with residency on the waiting list (55). Current regulatory criteria may be limited in scope to accurately identify poorly performing centers (56). Policies that concurrently emphasize improved center performance with access to transplantation should be prioritized to improve ESRD population outcomes (55).

Ongoing Efforts and Future Directions

Increasing Organ Use

Over the past 4 years, several initiatives have been implemented to improve organ use without affecting transplantation center performance. In June 2016, UNOS launched the Collaborative Innovation and Improvement Network (COIIN), a 3-year pilot study to encourage transplantation centers to increase use of deceased donor kidneys with a KDPI score >50% with no punitive consequences. UNOS waivered COIIN centers; however, CMS did not afford exemptions to participating centers. Preliminary results revealed that many participating centers observed an increase in transplantation rates and greater use of moderate to high KDPI kidneys (57). Similar COIIN projects are likely required to encourage the transplantation of kidneys infected with human immunodeficiency virus into infected recipients, use of hepatitis C–positive kidneys into negative recipients, and use of blood type non-A1/A1B donor kidneys into blood type B recipients. Because recipients of high-KDPI kidneys have a higher risk of delayed graft function, greater length of stay, and greater healthcare costs, some propose risk-adjusted reimbursement for kidney transplantation to relieve the financial disincentives associated with high KDPI kidney use (58).

In September 2018, CMS announced a proposed rule to relieve excessive regulatory burden on transplantation centers and unnecessary flagging of programs. The consequences of the latter practice are reduced transplantation volumes and exclusion from Medicare coverage and private insurers’ center of excellence networks (59). To align the quality grading system of transplantation programs with the goal of improving access to transplantation and outcomes, in February 2019, the Scientific Registry of Transplant Recipients included two new pretransplant metrics, deceased donor kidney transplant rate and waitlist mortality, in its five-tier outcome assessment system for transplantation programs (60). Whereas the addition of kidney transplantation rate is a welcome change, inclusion of waitlist mortality in outcome assessment of centers may have the unintended consequence of avoiding waitlisting sicker patients who may otherwise benefit from transplantation.

Improving Access to Transplantation

Strong evidence-based national guidelines with standardization of medical eligibility criteria are required to encourage similar listing practices across transplantation centers in the United States. In the absence of equitable listing practices across centers, transplantation centers should clearly convey their selection criteria/acceptance policies to referring nephrologists, who may then optimally direct patients toward transplantation centers more likely to accept them. There is also a demand for a more personalized approach toward racial/linguistic minorities and elderly and obese patients. A few centers have undertaken a prospective study to implement culturally targeted interventions to increase transplantation rates in the Hispanic population (61). The program includes providing linguistically and culturally appropriate information to the patients, hiring bilingual providers, and cultural competency training of staff. A transplantation center–based patient navigator may help to increase waitlisting among patients at high risk of dropping out of the transplantation process (62). Kidney transplantation in obese patients also begs a new approach. Body mass index is a poor surrogate measure of adiposity, and prediction may improve when combined with other measures such as waist circumference and measures of muscle mass (63). Participants in any weight loss program must be under medical supervision to avoid sarcopenia (64). Laparoscopic sleeve gastrectomy and minimally invasive robotic surgery are associated with reduced risk of perioperative complications and increase transplantation rates in morbidly obese patients. These procedures must be used more frequently (65,66).

New Framework of Organ Distribution

The OPTN approved a continuous distribution model in December 2018 with the principle of distributing organs as broadly as feasible and with no geographic constraints (67). The OPTN intended to eliminate DSA and OPTN/UNOS regions. Instead, a single unified model across all organ types was implemented. The new model gave candidates a priority score based on medical urgency, likelihood of graft survival, and proximity to the donor location. The new policy was met with opposition because the policy might reduce the number of organ transplantations and increase organ wastage and healthcare costs. More importantly, the new policy would potentially increase geographic disparities in access to kidney transplantation. Critics also contended that the plan would divert organs away from rural and low-income communities in the South, Midwest, and Northwest to larger metropolitan areas (68). Before the liver distribution policy could take effect, a Federal court order in May 2019 reverted it to its former state. However, to date, UNOS/OPTN has continued to pursue the goal of removing DSA and regions from kidney and pancreas distribution.

In summary, the solution of existing disparities in access to kidney transplantation requires greater integrated and coordinated efforts by the transplantation community, dialysis providers, and government. Notwithstanding efforts to augment the number of organs available, there is the necessity of overall performance system improvement.

“The greatest gift is a portion of thyself.” Ralph Waldo Emerson

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If the inline PDF is not rendering correctly, you can download the PDF file here.

  • View in gallery

    Geographic distribution of unadjusted transplant rate by state, 2016. Note that trends may be influenced by changes to the kidney allocation system (KAS) policy that were implemented in December 2014. Abbreviations: pt yrs; patient-years; tx, transplant. From United States Renal Data System. 2018 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2018.

  • View in gallery

    Organs per potential donors per year, by Organ Procurement Organizations. From Reforming Organ Donation in America. Reprinted from reference 39 (Available at:

    https://www.bridgespan.org/bridgespan/Images/articles/reforming-organ-donation-in-america/reforming-organ-donation-in-america-01-2019.pdf. Accessed May 11, 2019), which is available under the terms of the Creative Commons Attribution License.

  • View in gallery

    Marked variability in organ donation rates across the United States. Data from the State Inpatient Databases (SIDs), which included hospital zip codes, allowed us to map the inpatient deaths to Donation Service Area (DSA) to estimate the donor potential within a DSA (the total donor potential for a given organ procurement organizations [OPO]). The donation rate was calculated as: (number of organ donors) / (“possible” deceased donors), with possible donors based on the methodology described above. As shown to the right, there was marked variability in organ donation rates, without geographic clustering, with areas of high donation (e.g., San Diego and Philadelphia) adjacent to areas of low donation (Los Angeles and New York). Reprinted with permission from reference 69 (Goldberg D, Kallan MJ, Fu L, Ciccarone M, Ramirez J, Rosenberg P, Arnold J, Segal G, Moritsugu KP, Nathan H, Hasz R, Abt PL: Changing metrics of organ procurement organization performance in order to increase organ donation rates in the United States. Am J Transplant 17: 3183–3192, 2017) and reference 70 (Available at: https://www.med.upenn.edu/goldberglab/data.html).

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    Report for the Percentage of Prevalent Patients Waitlisted (PPPW). Available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/ESRDQIP/Downloads/Report-for-Percentage-of-Prevalent-Patients-Waitlisted.pdf. Accessed June 22, 2019

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    Davis AE, Mehrotra S, Ladner DP, Kilambi V, Friedewald JJ: Changes in geographic disparity in kidney transplantation since the final rule. Transplantation 98: 931936, 2014 PubMed

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    Patzer RE, Pastan SO: Kidney transplant access in the Southeast: View from the bottom. Am J Transplant 14: 14991505, 2014 PubMed

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    Kasiske BL, Snyder JJ, Skeans MA, Tuomari AV, Maclean JR, Israni AK: The geography of kidney transplantation in the United States. Am J Transplant 8: 647657, 2008 PubMed

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    Vranic GM, Ma JZ, Keith DS: The role of minority geographic distribution in waiting time for deceased donor kidney transplantation. Am J Transplant 14: 25262534, 2014 PubMed

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    Lynch RJ, Patzer RE: Geographic inequity in transplant access. Curr Opin Organ Transplant 24: 337342, 2019 PubMed

  • 19.

    Zhou S, Massie AB, Luo X, Ruck JM, Chow EKH, Bowring MG, : Geographic disparity in kidney transplantation under KAS. Am J Transplant 18: 14151423, 2018 PubMed

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    • Export Citation
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    Joshi S, Gaynor JJ, Bayers S, Guerra G, Eldefrawy A, Chediak Z, : Disparities among Blacks, Hispanics, and Whites in time from starting dialysis to kidney transplant waitlisting. Transplantation 95: 309318, 2013 PubMed

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    • Export Citation
  • 21.

    Ayanian JZ, Cleary PD, Weissman JS, Epstein AM: The effect of patients’ preferences on racial differences in access to renal transplantation. N Engl J Med 341: 16611669, 1999 PubMed

    • Search Google Scholar
    • Export Citation
  • 22.

    Zhang X, Melanson TA, Plantinga LC, Basu M, Pastan SO, Mohan S, : Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system. Am J Transplant 18: 19361946, 2018 PubMed

    • Search Google Scholar
    • Export Citation
  • 23.

    Melanson TA, Hockenberry JM, Plantinga L, Basu M, Pastan S, Mohan S, : New kidney allocation system associated with increased rates of transplants among black and Hispanic patients. Health Aff (Millwood) 36: 10781085, 2017 [Millwood] PubMed

    • Search Google Scholar
    • Export Citation
  • 24.

    Sequist TD, Narva AS, Stiles SK, Karp SK, Cass A, Ayanian JZ: Access to renal transplantation among American Indians and Hispanics. Am J Kidney Dis 44: 344352, 2004 PubMed

    • Search Google Scholar
    • Export Citation
  • 25.

    Epstein AM, Ayanian JZ, Keogh JH, Noonan SJ, Armistead N, Cleary PD, : Racial disparities in access to renal transplantation: Clinically appropriate or due to underuse or overuse? N Engl J Med 343: 15371544, 2000 PubMed

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    • Export Citation
  • 26.

    Gunnar W: The VA Transplant Program: A rebuttal to criticism and a look to the future. Am J Transplant 19: 12881295, 2019 PubMed

  • 27.

    Pullen LC: Transplantation remains daunting for many veterans. Am J Transplant 17: 12, 2017 PubMed

  • 28.

    Organ Donation Statistics: 2019. Available at: https://www.organdonor.gov/statistics-stories/statistics.html. Accessed May 12, 2019

  • 29.

    America DL: Annual Organ Report 2018. Available at: https://www.donatelife.net/wp-content/uploads/2018/09/DLA_AnnualReport.pdf. Accessed May 11, 2019

    • Export Citation
  • 30.

    Mohan S, Chiles MC, Patzer RE, Pastan SO, Husain SA, Carpenter DJ, : Factors leading to the discard of deceased donor kidneys in the United States. Kidney Int 94: 187198, 2018 PubMed

    • Search Google Scholar
    • Export Citation
  • 31.

    Bar Y, Barregard L, Sallsten G, Wallin M, Mölne J: Quantitative and semi-quantitative histopathological examination of renal biopsies in healthy individuals, and associations with kidney function. APMIS 124: 393400, 2016 PubMed

    • Search Google Scholar
    • Export Citation
  • 32.

    Carpenter D, Husain SA, Brennan C, Batal I, Hall IE, Santoriello D, : Procurement biopsies in the evaluation of deceased donor kidneys. Clin J Am Soc Nephrol 13: 18761885, 2018 PubMed

    • Search Google Scholar
    • Export Citation
  • 33.

    Mohan S, Campenot E, Chiles MC, Santoriello D, Bland E, Crew RJ, : Association between reperfusion renal allograft biopsy findings and transplant outcomes. J Am Soc Nephrol 28: 31093117, 2017 PubMed

    • Search Google Scholar
    • Export Citation
  • 34.

    Liapis H, Gaut JP, Klein C, Bagnasco S, Kraus E, Farris AB 3rd, ; Banff Working Group: Banff histopathological consensus criteria for preimplantation kidney biopsies. Am J Transplant 17: 140150, 2017 PubMed

    • Search Google Scholar
    • Export Citation
  • 35.

    Ugur ZB: Does presumed consent save lives? Evidence from Europe. Health Econ 24: 15601572, 2015 PubMed

  • 36.

    Shepherd L, O’Carroll RE, Ferguson E: An international comparison of deceased and living organ donation/transplant rates in opt-in and opt-out systems: A panel study. BMC Med 12: 131, 2014 PubMed

    • Search Google Scholar
    • Export Citation
  • 37.

    Verheijde JL, Rady MY, McGregor JL: The United States Revised Uniform Anatomical Gift Act (2006): New challenges to balancing patient rights and physician responsibilities. Philos Ethics Humanit Med 2: 19, 2007 PubMed

    • Search Google Scholar
    • Export Citation
  • 38.

    Ethics of deceased organ donor recovery. Available at: https://optn.transplant.hrsa.gov/resources/ethics/ethics-of-deceased-organ-donor-recovery/. Accessed May 23, 2019

    • Export Citation
  • 39.

    Reforming Organ Donation in America: Available at: https://www.bridgespan.org/bridgespan/Images/articles/reforming-organ-donation-in-america/reforming-organ-donation-in-america-01-2019.pdf. Accessed May 11, 2019

  • 40.

    Goldberg DS, Shafer T, Siminoff L: Important facts about organ donation and OPO performance. Transplantation 102: e249e250, 2018 PubMed

    • Search Google Scholar
    • Export Citation
  • 41.

    Pullen LC: CMS proposes new quality metric. Am J Transplant 19: 967968, 2019 PubMed

  • 42.

    Kucirka LM, Grams ME, Balhara KS, Jaar BG, Segev DL: Disparities in provision of transplant information affect access to kidney transplantation. Am J Transplant 12: 351357, 2012 PubMed

    • Search Google Scholar
    • Export Citation
  • 43.

    Johansen KL, Zhang R, Huang Y, Patzer RE, Kutner NG: Association of race and insurance type with delayed assessment for kidney transplantation among patients initiating dialysis in the United States. Clin J Am Soc Nephrol 7: 14901497, 2012 PubMed

    • Search Google Scholar
    • Export Citation
  • 44.

    Waterman AD, Peipert JD, Goalby CJ, Dinkel KM, Xiao H, Lentine KL: Assessing transplant education practices in dialysis centers: Comparing educator reported and Medicare data. Clin J Am Soc Nephrol 10: 16171625, 2015 PubMed

    • Search Google Scholar
    • Export Citation
  • 45.

    Patzer RE, Smith K, Basu M, Gander J, Mohan S, Escoffery C, : The ASCENT (Allocation System Changes for Equity in Kidney Transplantation) Study: A randomized effectiveness-implementation study to improve kidney transplant waitlisting and reduce racial disparity. Kidney Int Rep 2: 433441, 2017 PubMed

    • Search Google Scholar
    • Export Citation
  • 46.

    Kucirka LM, Purnell TS, Segev DL: Improving access to kidney transplantation: Referral is not enough. JAMA 314: 565567, 2015 PubMed

  • 47.

    Huml AM, Albert JM, Thornton JD, Sehgal AR: Outcomes of deceased donor kidney offers to patients at the top of the waiting list [published online ahead of print Jul 27, 2017]. Clin J Am Soc Nephrol doi:10.2215/CJN.10130916, 2017 PubMed

    • Search Google Scholar
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