If you don't remember your password, you can reset it by entering your email address and clicking the Reset Password button. You will then receive an email that contains a secure link for resetting your password
If the address matches a valid account an email will be sent to __email__ with instructions for resetting your password
Address reprint requests to Melissa Y. Yeung, MD, FRCPC, FAST, AACHI, Department of Medicine, Brigham & Women's Hospital, 75 Francis St, Boston, MA, 02115.
Director of Kidney and Pancreatic Islet Transplantation, Professor of Medicine, Royal Adelaide Hospital, University of Adelaide, North Terrace, Adelaide, South Australia 5000
Address reprint requests to Philip Kam-Tao Li, MD, FRCP, FACP, FRACP, Honorary Professor, Department of Medicine & Therapeutics, Director, Carol and Richard Yu PD Research Centre, Prince of Wales Hospital, The Chinese University of Hong Kong, Hong Kong
Department of Medicine and Therapeutics, Prince of Wales Hospital, Shatin, Hong KongCarol and Richard Yu PD Research Centre, The Chinese University of Hong Kong, Hong Kong
Transplantation is a life-saving medical intervention that unfortunately is constrained by scarcity of available organs. An ideal system for allocating organs should seek to achieve the greatest good for the greatest number of people. It also must be fair and not disadvantage certain populations. However, policies aimed at reducing disparities also must be balanced with considerations of utility (graft outcomes), cost, efficiency, and any adverse effects on organ utilization. Here, we discuss the ethical challenges of creating a fair and equitable organ allocation system, focusing on the principles governing deceased donor kidney transplant waitlists around the world. The kidney organ allocation systems in the United States, Australia, and Hong Kong are used as illustrations.
For any medical intervention or resource that is scarce, allocation is necessary because demand exceeds supply. Policies addressing allocation inherently pose ethical challenges; the severe imbalance between demand and availability requires organs be allocated explicitly, transparently, and, to an extent, independent of financial concerns. In this article we focus on the ethical challenges of an organ allocation system, focusing on the principles governing deceased donor kidney transplant waitlists around the world and whether allocation is occurring justly.
BROAD PRINCIPLES FOR ALLOCATION OF SCARCE MEDICAL RESOURCES
Medical ethicists have described a set of principles upon which allocation decisions can be made.
These principles can be categorized into four fundamental values: maximizing the benefits offered by the scarce resource, treating people equally, giving priority to the worst off, and promoting and rewarding social usefulness. No single principle alone results in a completely just system; rather, a set of principles often are combined to create the fairest system and, at times, these principles may be at odds with one another. In addition, a single set of principles does not reflect the moral and ethical opinions of all societies/communities, and priorities and opinions also may change over time. Thus, fair allocation requires an ethical framework that can be adapted depending on both the resource and context in question.
Allocation Based on Maximization of Benefits: Utility
The principle of utility seeks to maximize the benefit to the greatest number of individuals.
Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
One strategy to maximize benefits involves allocating the resource in a way that saves the most lives. However, in transplantation, only one life can be saved with each intervention; one available organ translates into one life saved. Another option, prognosis allocation, is based on those who would benefit the most from the scarce resource, aiming to save the most life-years by giving priority to patients likely to survive longest after transplantation. However, this strategy holds the potential of excluding those with a poor prognosis. Factors to be considered in determining utility on balance include the following: (1) patient survival, both in terms of if they undergo transplantation or die while awaiting transplant (waitlist mortality); (2) potential harmful consequences, including associated short-term morbidities (such as postoperative complications, delayed graft function, and acute rejection), and long-term morbidities (such as side effects and complications associated with immunosuppressive medications, and chronic rejection); (3) long-term graft survival; (4) quality of life; and (5) the availability of alternative treatments.
Allocation Based on Treating People Equally: Equity
The goal of an equitable system is to provide equal access or opportunity to transplantation for all patients who are medically qualified for an organ transplant.
Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
Importantly, as defined in a white paper by the United Network for Organ Sharing (UNOS)/Organ Procurement and Transplantation Network (OPTN), this “does not mean treating all patients the same but does require giving equal respect and concern to each patient.”
A lottery system has the appeal of supporting an equal claim with little knowledge, and therefore no bias, about the recipients; is easy to implement; and resists against corruption or gaming of the system. However, lack of knowledge about recipients is also a major disadvantage; being blind to relevant factors may inadvertently result in unequal treatment of individuals. For example, random allocation of a life-saving resource to someone who can gain 40 years of life versus someone who can gain only a few months is viewed by many as inappropriate. The second option is a first-come, first-served approach. Similar to lottery allocation, it ignores differences (both relevant and nonrelevant) between individuals and seemingly provides equal opportunity. However, in practice, it tends to favor people who have the means, resources, and knowledge to get into line quickly.
Until 2014, kidney allocations from deceased donors were allocated somewhat on a first-come, first-served basis in the United States with accrual of waiting time beginning when candidates were placed onto the waitlist. However, it now is well appreciated that this led to disparities in access to transplantation by favoring those who were referred early for transplant candidacy and underwent the evaluation process expeditiously.
Allocation Based on Giving Priority to the Worst-Off Patients
This concept is based on prioritizing individuals with the greatest need for the intervention, either to the sickest or to the youngest, who will have lived the shortest lives if they die untreated.
Treating the sickest first prioritizes those with the worst outcomes if left untreated. Examples of this include transplantation of life-saving organs (heart, liver, or lung), where there are no alternatives to treatment. However, allocation based on sickest-first fails to ignore postintervention prognosis; the sickest may fare the poorest even after treatment, leading to only minor benefits at the expense of the high cost of utilizing a scarce resource. Because this principle is based on medical need at the current time, allocation to the sicker patient unjustly ignores a currently healthier person who inevitably will be worse off in the future.
It assumes that the scarcity is temporary, and that we can save the sickest person now, and then the progressively ill person later. However, when resources are persistently scarce, there is no guarantee this will be the case.
Another option is to prioritize the youngest, which gives priority to the worst-off in that these patients would otherwise die having lived the fewest life-years. Ethicists contend that allocating preferentially to the young is different than favoring other groups that might be worse off (such as women, the poor, or the ethnic minority) in that “because [all people] age, treating people of different ages differently does not mean that we are treating persons unequally.”
Because it is a simple, quantifiable measure, age often is considered as a factor for allocation. However, age is often a proxy for more subjective variables such as expected patient survival, expected graft survival, and quality-adjusted life-years
Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
Hence, most agree that the youngest-first principle is insufficient on its own. However, because there is strong public preference for allocating scarce life-saving interventions to younger people,
An example of autonomy in transplantation is a patient's right to refuse a particular organ, based on medical factors of the donor; explicit consent must be obtained if a candidate is to be transplanted with an organ from a hepatitis C+ donor or a “lower quality” kidney from a donor with Kidney Donor Profile Index (KDPI) greater than 85%. In these examples, the candidate's decision will not take away from another's opportunity. In contrast, the process of a directed donation has a more direct impact on another potential recipient. In the United States, laws governing consent for organ donation explicitly permits organ donors (or their surrogate maker) to direct a donation to a particular recipient if they are compatible, allowing for the usual allocation process to be bypassed. The intent of this policy is to allow family members some autonomy over the organs of their deceased loved one. It was never intended to be inequitable or unfair. However, there have been cases in which this policy has been exploited by patients soliciting directed donation or creating groups in which members promise their organs to others upon death in return for the promise that they will be afforded the same opportunity should they themselves need an organ.
No single principle is sufficient on its own; a multiprinciple system adds complexity and controversy but is inevitable if it is to reflect the complexity of our moral values.
Importantly, an acceptable system in one part of the world may not be amenable elsewhere; differences in each community or society's moral and ethical values dictate the importance of the different principles. However, consensus is that the most effective and ethical way to allocate organs is through a balance of the main principles of equity and utility.
Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
An ideal system for allocating deceased donor organs should seek to achieve the greatest good for the greatest number of people, reflecting the principle of utility. It should aim to minimize the discard of transplantable organs and promote efficiency of their placement. The system also must strive to maintain the most sustainably equitable approach and not leave vulnerable candidates at a disadvantage. Finally, the process should involve all stakeholders and be explicit, transparent, justifiable, and easily understandable so that patients are able to participate in the decision-making process, in accordance with the principle of transparency and autonomy.
At times, these main ethical principles may be at odds with one another, but, on balance, an ideal allocation system should accommodate all three without disproportionately preferencing one principle over another. Pragmatically, a system with no undesirable disparities in access to transplantation is unattainable. For example, for candidates who are very highly sensitized (calculated panel of reactive antibodies [cPRA], >99.5%), the pool of compatible donors is so limited that equalizing their opportunities may be futile. In other circumstances, achieving perfect equipoise may come at the expense of goals of utility such as optimizing organ utilization and improving recipient outcomes. Similarly, an allocation system that prioritizes utility above all else would not be perceived as the most equitable because maximizing utility without regard to equity could disadvantage certain groups. Factors impacting a waitlist candidate's ability to receive a transplant can be biological or social. These include characteristics such as age, race, socioeconomic status, education level, citizenship, health insurance coverage, rural vs urban location, blood type, body mass index, comorbidities, HLA phenotype, and degree of alloimmune sensitization (cPRA), many of which are known to be associated with inferior outcomes. Incorporating these factors into allocation could inherently create bias against certain groups of individuals. Even if there is evidence that one race or gender fares more poorly, these factors should not form the basis for allocation decisions. That is not to say that we cannot use these factors as objective medical predictors of outcome, but rather that it would be unethical to exclude individual members of a group or give them lower priority simply because the group has statistically poorer outcomes. In such instances in which the principle of justice (equity) conflicts with the principle of utility, both deserve deliberation in deciding whether to include the factor in the allocation schema.
How Do We Measure the Success of an Allocation System?
Allocation policy proposals must undergo meticulous evaluation to assess the trade-offs between utility and equity. Metrics need to be defined, simulated, and tracked after implementation to identify unintended consequences. Improving utility can be interpreted as increasing the number of transplants, increasing the longevity of the allograft, improving the outcomes of both waitlisted and transplanted patients, or a combination thereof. Common outcome measures include short-term (1-year) and long-term graft survival rates, patient survival rates, predicted years of life added, predicted quality-adjusted life-years added, time to transplant, waitlist mortality, transplantation rates, and organ utilization rates. None of these metrics are sufficient on their own, and a combination is likely a better reflection of the system's overall success.
To determine whether a system is equitable, UNOS/OPTN recently began using an access to transplant score (ATS),
a numeric measure that quantifies a particular waitlist candidate's individual likelihood of receiving a deceased donor transplant. This metric is derived from a Cox proportional hazards regression model that considers 15 patient characteristics (Fig. 1).
Differences intended by policy to address inequities in patients’ ability to wait for a transplant, such as medical urgency, pediatric status, and prior organ donation, are purposefully not included in the ATS score. The degree of variation in the scores among waitlist candidates reflects the degree to which the allocation system is equitable; the greater the SD the greater the inequity in the system (Fig. 1). Over time, if the SD decreases, the system has become more equitable with fewer differences in wait time between individual candidates irrespective of their biological or social factors. Alternatively, a more traditional way of gauging equity in organ allocation compares the percentage of transplants received by a particular group of patients with the percentage of the waiting list represented by that group: roughly equal percentages suggest allocation is equitable. However, because this approach is not risk-adjusted, apparent inequities in the factor being evaluated could be attributable to confounding factors. An important caveat to both these measures is its exclusive focus on equity in access among active waitlisted candidates. However, a fundamental prerequisite to organ allocation is a patient's access to the waiting list. Thus, inherent to disparities in access to organ transplantation is a combination of both access to the waitlist and access to organs once on the waitlist. If access to organ transplantation is to be equitable, then access to the waitlist also must be equitable. Access to the waitlist depends on the timely and appropriate referral for transplant evaluation, as well as timely evaluation for candidate suitability by transplant programs. Both bottlenecks are fraught with known inequities and show marked regional and hospital-level variations: delays in referral and longer processes of evaluation for transplant candidacy are more common among minority candidates and those of lower socioeconomic class.
In addition, there are large variations in listing practices and requirements among different transplant programs. This is exacerbated by the unintended consequences of the current regulatory oversight policies that evaluate transplant program performance that disincentivize the acceptance of higher-risk patients for transplant.
The Centers for Medicare and Medicaid (CMS) is now implementing new metrics to attempt to address these inequalities in access to transplantation at all levels from referral to candidate selection for waitlist and organ offer selection.
Figure 1A) The degree of variation in access to transplant scores (ATS) amongst all candidates on the waitlist reflects the degree to which the allocation system is equitable. The greater the standard deviation (S.D.), the greater the disparity between candidates. B) Factors included in the access to transplant score.
Finally, apart from finding equipoise between utility and equity, the system also must balance optimizing organ matching and placements (organ utilization rates) with trade-offs in system efficiency (including cost).
HISTORY OF ORGAN ALLOCATION IN THE UNITED STATES
After the first successful kidney transplantation in 1954, individual transplant hospitals managed all aspects of organ recovery and transplantations in the United States. Subsequently, local organ procurement organizations (OPOs) were established to facilitate the process. However, if an organ could not be used locally, there was no nationwide system to find suitable candidates elsewhere, leading to the unnecessary discarding of a substantial number of organs because compatible recipients could not be identified in a timely manner. In 1984, Congress passed the National Organ Transplant Act, which provided initial guidance regarding the development of organ allocation policies and established the OPTN to be run by a private, nonprofit organization under federal contract. Shortly thereafter, UNOS was founded to fulfill this mission, and was awarded the initial OPTN contract and has served as the OPTN ever since. UNOS's mission is to unite and strengthen the donation and transplant community to save lives, with a vision of providing a life-saving transplant for everyone in need. In 2000, the US Department of Health and Human Services implemented a ‘final rule’ establishing a regulatory framework for the structure and operations of the OPTN.
The final rule requires UNOS/OPTN to develop allocation policies that are equitable and to promote the efficient management of organ placement with consideration of the ethical principles of utility, equity, transparency, and autonomy.
Centers for Medicare & Medicaid Services (CMS) HHS, Medicare and Medicaid programs; conditions for coverage for organ procurement organizations (OPOs). Final rule.
CMS also provides quality oversight of OPOs, transplant programs, and dialysis facilities by monitoring outcome and process metrics such as rates of referral, rates of patients placed on the waiting list, donation rates, transplantation rates, 1-year graft and patient survival rates, and performance benchmarking. The census of transplant candidates, recipients, donors, and organs procured for the purpose of transplant are tracked by the Scientific Registry of Transplant Recipients. These data then are used to inform policy development as well as ensuring transplant programs and OPOs are meeting the requirements for conditions of participation. These reports are publicly available, and summarize national, regional, and center-specific outcomes.
CURRENT STATUS OF DECEASED DONOR KIDNEY TRANSPLANTATION: SCOPE OF THE PROBLEM
Organ transplantation continues to be a scarce medical resource. After remaining relatively stagnant for many years, the number of kidney transplants has increased in the United States each year since 2015. However, despite a record number of kidney transplants occurring in 2021 (n = 25,489), there remains approximately 90,000 individuals awaiting a kidney, with nearly 37,000 new patients added to the waitlist each year.
Furthermore, although the number of transplants performed has increased each year, the growth rate of waitlist additions far exceeds the supply (7.8% versus 11.1% growth rate in the past year). The latest OPTN annual report estimates that only 25% of patients receive a deceased donor kidney transplant within 5 years, with drastic variation (14.8%-73.0%) depending on geographic region.
pre-KAS: THE ERA BEFORE IMPLEMENTATION OF THE KIDNEY ALLOCATION SYSTEM (KAS)
Before December 2014, the old pre–kidney allocation system (pre-KAS) system was primarily a first-come, first-serve classification-based model driven to a large extent by a candidate's waiting time. Priority was given on a local basis (as determined by the transplant hospital's OPO affiliation) to candidates with the greatest number of points within each classification. Points were allotted based on waiting time (defined from the time of listing), degree of human leukocyte antigen (HLA) matching, and degree of alloantigen sensitization. Because allograft survival is linked to the number of HLA mismatches, more points were given for fewer mismatches at the HLA-B and HLA-DR loci.
In addition, certain exceptions such as pediatric candidates (reflecting the youngest-first principle), prior living donors (reflecting the principle of reciprocity), and candidates with zero-antigen mismatches with the donor afforded candidates the highest priority, with national allocation.
Advantages
One advantage of the points-based system is its simplicity and flexibility: all possible principles can be included, new principles can be incorporated easily by translating it into a points framework, and the relative weights of each principle can be easily revised. Although primarily based on the first-come, first-served principle, some considerations were given to the sickest first (provision for medical exceptions) and prognosis (HLA and blood type matching between donor and recipient).
Shortcomings
Arguably, the first-come, first-served is least justifiable and most vulnerable to exploitation. Inequities resulted from the way the wait time was calculated, variability in access to transplants for candidates who are harder to match owing to biologic reasons (blood type, sensitization, HLA phenotype), a matching system that failed to maximize life-years saved leading to a need for retransplant, and high organ discard rates.
Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
In addition, although the system used a points-based allocation, this was within a larger construct of a classification-based system in which candidates were grouped into rigid classifications such as geographic boundaries or ABO blood type. For example, candidates in New England with blood type B had much longer wait times than those with blood type A, and candidates listed in California had substantially longer wait times compared with those listed in New England, all else being equal.
WAITING TIME DEFINED BY THE TIME OF LISTING
Wait time in this era was defined by the time of listing with a transplant center. This led to unintended disparities in transplantation for minority candidates and those of lower socioeconomic class, who tended to be referred later and in whom evaluation processes take longer.
INSUFFICIENT CONSIDERATION FOR THE PRINCIPLE OF MAXIMIZING BENEFITS
The pre-KAS system also failed to sufficiently consider the principle of maximizing benefits, including consideration of prognosis (life-years saved) or saving the most lives. Although pediatric patients (candidates listed before the age of 18) were prioritized, there was little other consideration for matching the best kidneys with patients who had the greatest need for a long-lasting organ. Consequently, severe mismatches in the expected lifespan between the organ and recipient were not uncommon. Among those receiving a transplant between 2005 and 2010 (pre-KAS), rates of death with a functioning graft at 10 years were approximately 25% and appeared to be trending slightly higher, which may reflect a higher rate of transplants in older recipients who are more likely to die before graft failure.
Longevity-matching is an increasingly important consideration in preserving a scarce resource as the waitlist population has become progressively older: approximately 26% of waitlist candidates are currently 65 years of age or older, compared with approximately 18% in 2016 and approximately 10% in 2004.
Although use of HLA matching to promote graft longevity and improved patient outcomes has sound scientific basis and thereby promotes the principle of utility, its incorporation inadvertently led to infringement on the principle of equity. This is because HLA matching and cPRA are not distributed randomly among racial or gender groups. Because nearly 70% of deceased donors are Caucasian and HLA antigen frequencies are tied inherently to racial descent, candidates of ethnic minorities, who comprise more than 60% (non-white) of the waitlist, were less likely to receive a well-matched kidney and less likely to be at the top of the list for a less well-matched kidney.
Exacerbating the issue was that points allotted for fewer HLA mismatches often exceeded those accumulated based on waiting time. As a result, African American candidates received a transplant at a lower rate and had longer wait times, resulting in a higher risk of death on dialysis
To incorporate HLA matching to maximize utility, we need to think of ways to offset its negative impact on equity because, ultimately, a better-matched graft benefits everyone.
KAS: 2014-2021
After 10 years of deliberation and feedback from patient groups, professional transplant societies, individual transplant programs, the organ procurement organizations, and the general public, UNOS/OPTN implemented a new KAS in December 2014.
KAS was envisioned to address the shortcomings of the prior allocation policy with the goals of reducing organ/recipient longevity mismatches, increasing access for biologically and historically disadvantaged groups, and increasing recovery and utilization of lower-quality kidneys. The following major changes were implemented: a change in how wait time was calculated (to begin at dialysis initiation instead of time of listing); allowing blood type B candidates to be considered for kidney offers from donors with blood subtype non-A1; increasing priority for sensitized candidates with a sliding scale points system, and additionally providing the highly sensitized candidates with local (cPRA, >98%), regional (cPRA, >99%), or national priority (cPRA, 100%); and the implementation of the Kidney Donor Profile Index (KDPI) and the Estimated Post-Transplant Survival (EPTS) scores for longevity matching. Figure 2 shows a simplified example of the KAS allocation model.
Figure 2A simplified example of the current KAS allocation model. Candidates are grouped into distinct categories which are ranked (left). “Local” candidates are defined as those listed at a transplant center <250 NM from donor hospital. Within each of these distinct categories, candidates are then further ranked according to their priority score (right). Priority points are allotted based on waiting time, match distance (distance from donor hospital), points for HLA-DR matching, and cPRA. Even if a candidate has a greater priority score, they cannot move up in the match sequence if they belong to a category that is considered of lesser priority.
After the implementation of KAS, the variability in ATS (discussed earlier) among all waitlisted kidney candidates decreased substantially from a SD of 1.493 to 0.865 post-KAS, reflecting an improvement in equity in access to deceased donor kidney transplants of approximately 40%.
However, these gains in equity to access to a transplant may have offset other goals such as optimizing utilization of the limited supply of kidneys and improving outcomes for transplant recipients. Early post-KAS outcomes suggest short-term (<2 year) patient and allograft survival has remained relatively stable post-KAS,
However, this was offset by persistent higher organ discard rates and increased incidence of delayed graft function (discussed further later, section 7.2). Longer-term follow-up analyses are needed to determine the global consequences of KAS policies, and whether the resulting trade-offs are acceptable to the transplant community.
KAS IMPROVEMENTS: PRIORITY FOR HIGHLY SENSITIZED CANDIDATES
The overall improvement in equity was driven largely by the improvement in transplant rates attributable to differences in candidates’ degree of allosensitization.
The national landscape of deceased donor kidney transplantation for the highly sensitized: transplant rates, waitlist mortality, and posttransplant survival under KAS.
Before KAS, four allocation points were given to candidates with a cPRA greater than 80%, compared with zero points for those with a cPRA below this arbitrary cut-off value. This binary cut-off value led to a disproportionate number of transplants among candidates with a cPRA of 80% to 94%, in whom the probability of finding an HLA compatible match was higher, than those with a cPRA greater than 95% who also received four additional points. KAS policy removed this artificial hard boundary and, instead, allocated points on a sliding scale and expanded the donor pool to local, regional, and national priority for candidates with a cPRA of 98%, 99%, and 100%, respectively. The improved equity was reflected by a decrease in ATS SD of more than 50% from 1.074 pre-KAS to between 0.39 and 0.50 post-KAS.
When categorized by cPRA levels, the average risk-adjusted (all else equal) ATS scores also were much lower in patients with cPRA levels greater than 98%, corresponding to long expected wait times to transplant.
Post-KAS, much of these imbalances normalized, except in candidates with a cPRA greater than 99.95% who still have much lower access to a transplant than those with lower cPRA levels, despite receiving national priority and exponentially higher priority points under KAS. Analyzed a different way, before KAS, candidates with a cPRA of 99% to 100% accounted for approximately 9% of the waitlist and received only 2% of transplants. Immediately post-KAS, this went up to 17% of transplants but has since reached a new equilibrium of approximately 12%, which is more in line with their proportion on the wait list. This increase was driven largely by access to a broader pool of organs and a higher number of priority points allotted. However, although most highly sensitized patients benefited from the new KAS policies, a subset of patients with a cPRA greater than 99.95% continue to receive far fewer transplant than their waiting list prevalence (discussed further later).
KAS IMPROVEMENTS: IMPLEMENTATION OF LONGEVITY MATCHING
Longevity matching was implemented to maximize the cumulative graft survival achieved from the available supply of deceased donor kidneys at the expected expense of reducing access for older candidates. Before KAS, older adults (age, >65 y) had slightly greater access to a transplant than younger adults, all else equal.
This trend reversed post-KAS after implementation of longevity matching, in which kidneys expected to function the longest are allocated preferentially to candidates expected to benefit from a transplant the longest. Concerns about drastically reduced access for older patients have not held true: active candidates older than age 65 years who account for 20% of the active waitlist still are receiving 19% of transplants post-KAS.
Although KAS has led to reduced age disparities, the true impact of longevity matching on its intended goal of improving utility remains undetermined because of its reliance on long-term graft survival and patient outcome metrics. However, short-term analyses suggest that it likely has contributed to higher organ discard rates (discussed later, section 7.2.3).
Longevity matching is determined using two new metrics: the KDPI and the EPTS score.
The KDPI is a more refined and continuous metric that replaces the previous dichotomous metric of characterizing donor quality as a standard criteria donor (SCD) versus an extended criteria donor (ECD). While the ECD criteria examined only four donor factors (age, history of hypertension, serum creatinine level ≥1.5 mg/dL, and death resulting from a stroke), KDPI incorporates 10 donor factors and weights them according to their attributable relative risk. Comparison between KDPI scores and ECD/SCD criteria have shown that some ECD kidneys have good KDPI scores and longer allograft survival rates while some kidneys categorized as SCD have lower estimated quality.
The KDPI score is derived from calculating the Kidney Donor Risk Index (KDRI), which is an estimate of the relative risk of allograft failure from a particular deceased donor compared with a reference donor. The factors used to calculate the KDRI include donor age, height, weight, ethnicity, history of hypertension, history of diabetes, cause of death, serum creatinine, hepatitis C virus status, and donation after circulatory death status.
The relative risk attributable to each of these donor factors and graft survival was determined using a multivariable Cox proportional hazards regression model using graft outcomes from approximately 70,000 adult, first-time deceased donor kidney recipients in the United States from 1995 to 2005.
A donor with a KDRI of 1.5, for example, confers an estimated risk of graft failure that is 1.5 times that of the median donor during the previous calendar year. This reference donor is neither the ideal donor nor an average donor, and can vary from year to year. The KDPI then maps the KDRI to a cumulative percentage scale; kidneys from a donor with a KDPI of 95%, for example, have an estimated risk of graft failure that is higher than 95% of recovered kidneys in the prior year. Although a marked improvement from the previous SCD/ECD categorization, the KDPI is still only moderately predictive, with a C-statistic of 0.60.
The primary purpose for including KDPI was to implement the concept of longevity matching into the kidney allocation system, with candidates with longer estimated post-transplant longevity (EPTS score, ≤20%) to receive priority for kidneys from donors with a KDPI of ≤20%. Candidates with a lower EPTS score are expected to experience more years of graft function compared with candidates with higher EPTS scores. The EPTS score comprises the following factors, each weighted according to its association with post-transplant candidate survival, as derived from a Cox proportional hazards model: candidate age, duration on dialysis, current diagnosis of diabetes, and whether the candidate has had a prior solid organ transplant.
The raw EPTS score then is mapped to an EPTS score. In the majority (80%) of deceased donor kidney allocations, EPTS is not used at all; it is used only when the donor has a KDPI ≤20% to prioritize the transplant of these highest-quality kidneys into candidates expected to live the longest. The intent of this is to achieve the most benefit from each donated organ: transplanting high-longevity kidneys into patients not expected to live long after transplant leads to unutilized graft-years from this scarce resource while transplanting kidneys that are not expected to last long into high-longevity recipients results in high rates of graft failure and a return to the wait list. EPTS scores do not apply to pediatric candidates (listed before age 18), who maintain priority over adult candidates. In addition, other “trumping” priority still was given to candidates awaiting multiple organs, prior living donors, and those with zero HLA mismatches to the donor.
KAS IMPROVEMENTS: REDUCED BLOOD TYPE DISPARITIES
For deceased donor kidneys, allocation occurs within a blood type; blood type O donors are allocated to blood type O candidates only. This results in differing waiting times between candidates of different blood types, with blood type B candidates, who comprise a greater proportion of ethnic minorities, having the longest wait time. Under KAS policy, blood type non-A1 and non-A1B kidneys now are offered to medically eligible and consented type B candidates who have low anti-A antibody titers. These candidates could be transplanted safely with non-A1 organs without the need for additional treatment.
KAS IMPROVEMENTS: REDUCED DISPARITIES IN DIALYSIS VINTAGE
Before KAS, wait time began at the time of a candidate's listing on the waitlist. KAS policy changed it such that waiting points begin at the date of dialysis initiation or when a candidate is listed and has a glomerular filtration rate less than 20 mL/min per 1.73 m2. Those who had been on dialysis for lengthy periods but were listed only recently (reflecting disparities in a candidate's access to listing) thus were made whole post-KAS; immediately post-KAS implementation, there was a significant bolus of transplants occurring in patients with a long dialysis history.
This has since stabilized to approximate pre-KAS levels now that the disparity gap has closed.
IMPROVED ACCESS TO TRANSPLANT FOR ETHNIC MINORITIES
After KAS, the proportion of transplants occurring among various ethnic groups became more comparable with their proportion on the waiting list, suggesting increased equity in nonadjusted analysis. However, if we examine disparity using the risk-adjusted ATS score, we can see that even pre-KAS the variability in ATS score by ethnicity, all else equal, was very small, with a SD of 0.074 (a SD of 0 represents complete equity).
This suggests that other factors included in the multivariate ATS score were the drivers of inequity among different ethnic groups. Indeed, the new KAS policies addressing allosensitization, waitlist time, and blood type differences were the major drivers of reducing disparity for minority candidates. For example, after KAS went into effect, an initial bolus of African American recipients underwent transplant as a result of waiting time priority being redefined to begin at the time of dialysis initiation instead of listing. This corrected the long-standing disparity between the proportion of African American candidates on the waiting list and the proportion receiving a transplant.
Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system.
For example, 25% of Asians have the more difficult-to-match blood type B, compared with 9% of Caucasians. Similarly, African Americans comprise 31.5% of the total current waitlist but 48.8% of highly sensitized candidates with a cPRA of 98% to 100%.
Thus, although the risk-adjusted ATS score by ethnicity suggested little inequity between ethnic groups, evaluation of unadjusted measures show disparate transplant rates among different ethnic groups and even different subsets of groups because of differences in allosensitization and blood types.
KAS Shortcomings, Unintended Consequences, and Remaining Challenges
Despite the improvements brought about by KAS policies, substantial disparities in access to transplant remain. The top three factors that contribute to the ongoing variability in access to transplant are geographic disparities, cPRA, and blood type (Fig. 3).
In addition, KAS policies have unintentionally led to higher organ discard rates and an increased incidence of delayed graft function (DGF).
Figure 3A) Current variability in access to transplant scores (ATS) amongst all candidates on the deceased donor kidney waitlist, broken down by candidate characteristic. B) Changes in the access to transplant score by candidate characteristic over time. Only the top 5 characteristics contributing to the greatest variability in access are shown. KAS: kidney allocation system implemented in December 2014; 250 NM: the donor service area redefined to be 250 nautical miles from the donor hospital implemented in March 2021.
Reducing geographic disparity in access to transplant was not an explicit goal of KAS, and allocation remained constrained by the geographic location of the transplant program, as defined by the program's donation service area (DSA). Under KAS, kidneys procured within each of the 58 DSAs continued to be allocated first to candidates waitlisted within that DSA. If declined locally within a given DSA, kidneys subsequently are offered within the donor hospital's OPTN region, and then allocated nationally if declined by all regional centers. Since their establishment, these arbitrary DSA and regional borders have had an unintended direct impact on a candidate's access to organ offers, leading to large disparities in time to transplant for patients listed within different DSAs. Although KAS policy indirectly led to a 27% decrease in variability attributable to DSAs, DSA is still the greatest factor contributing to disparity among all factors evaluated in the ATS
This striking 17-fold difference between the highest- versus lowest-rate DSA formed the impetus for moving toward elimination of donor service areas (first by expanding to a 250 nautical mile [NM] radius, then ultimately to removal altogether, discussed further later in Section 8). Historically, the marked variation in transplantation rates has been attributed to differences in local organ supply. However, even within the same DSA, there is marked variability between transplant centers, suggesting a greater role for inconsistency in organ offer acceptance patterns as the driver of disparate wait times.
ONGOING DISPARITIES AMONG HIGHLY SENSITIZED PATIENTS
Although patients categorized as having a cPRA of 100% whose cPRA is between 99.5% and 99.95% received far more transplants post-KAS (7.6% versus 0.8%), and at a higher proportion than their 3.0% representation on the active waitlist, those with a cPRA greater than 99.95% continue to receive far fewer transplant than their waiting list prevalence (1.1% of transplants versus their 3.2% representation on the active waitlist).
Given this ongoing disparity, UNOS/OPTN now is considering recalibrating the points distribution for cPRA categorization to the first or second decimal point so that transplant rates among those with a cPRA of 99.5% to 99.95% have more comparable rates compared with all other cPRA categories. However, for those with a cPRA greater than 99.95%, the stark reality is that sometimes equipoise cannot be achieved; these individuals have less than a 1 in 2000 chance of an HLA-compatible organ becoming available.
BLOOD TYPE DISPARITIES
Despite the provision for transplanting non-A1 kidneys into blood group B candidates, this eligibility is possible for only approximately 40% of blood group B candidates.
Furthermore, blood group subtyping performed serologically underestimates 65% of blood type A donors who are in fact non-A1 by genotyping (William J. Lane, personal communication). All else equal, there was little change post-KAS to the degree of disparity in access to transplant by blood type (from an ATS SD of 0.37 pre-KAS to 0.34 post-KAS).
Blood type B and O candidates continue to receive a lower proportion of transplants compared with their percentage of the waiting list: blood type B and O candidates make up 16.9% and 53.7% of the active waitlist, respectively, and yet only 13.2% and 46.3% of those who received a transplant.
Thus, blood type B and O candidates still are suffering from longer wait times; blood type AB candidates are more than 2.5-fold more likely to receive a kidney transplant compared with blood type B or O candidates.
Although KAS policy was intended to decrease organ discard rates, the percentage of kidneys discarded has been increasing from approximately 18% pre-KAS to 25% in 2021, representing approximately 6,500 kidneys.
The greatest increase in discard rate has been for suboptimal kidneys: kidneys from donors with KDPI greater than 85%, discard rates went from approximately 53% pre-KAS to 60% post-KAS in 2019.
KAS may have exacerbated inefficiencies by prioritizing the highest risk-candidates (such as those with a high cPRA and long duration on dialysis) into whom centers may be more averse to transplanting a lower-quality kidney. In addition, KDPI is a percentile measure that compares the quality of the kidney relative to those transplanted in the prior year, leading to an ongoing shift in perceived quality of the kidney and introducing cognitive biases that contribute to offer refusal. This is despite research showing a survival advantage to transplantation with a high KDPI when compared with remaining on the waitlist for a better-quality kidney.
Given the ever-growing gap between the demand for a graft and the supply of deceased donor kidneys, it is incumbent upon the community to better understand the reasons behind refusal of high-KDPI kidneys and to assess when utilization of these organs could otherwise provide better patient outcomes. To help achieve this, UNOS/OPTN is currently piloting a new predictive analytics tool to help clinicians determine whether to accept or refuse an organ offer. This evidence-based, clinical decision making tool includes the predicted time to next offer (how long the candidate is likely to wait to receive another offer within the different KDPI ranges if the current offer is refused) and the predicted likelihood of death (the candidate-specific chances of survival over time without a transplant). In addition, the community must re-evaluate the current regulatory oversight policies that lead to risk aversion in transplanting marginal kidneys with statistically poorer outcomes for fear of punitory measures.
DGF also became more common after KAS took effect, in part owing to more recipients having lengthy dialysis history and longer cold ischemic times from more widespread sharing of organs.
Post-KAS, kidneys were more likely to be procured after cardiac death (21.5% versus 17.8%), to travel farther (P < .0005), and to experience cold ischemia time longer than 24 hours (20.0% versus 18.8%) when compared with pre-KAS.
Longer-term follow-up evaluation is needed to determine the consequences of these increased rates of DGF.
MOVING TOWARD A CONTINUOUS DISTRIBUTION MODEL
Current allocation is a classification-based framework in which candidates are categorized into distinct groups based on specific criteria. They then are ranked for eligibility within these classifications but cannot move between classifications; these hard boundaries currently preclude a patient from being prioritized ahead of patients in a different category, some of which have arbitrary delineations. For example, allocation is constrained primarily to within arbitrary geographic borders of the 58 donor service areas, lending geography to continue to be one of the greatest inequalities post-KAS.
To address this, UNOS/OPTN is now proposing a move toward a points-based continuous distribution allocation system that will eliminate hard boundaries or classifications and permit differential weighting of factors when calculating each transplant candidate's priority score. The proposed borderless gravity model will generate a risk score weighted by the distance between the transplant center and the donor hospital, with the hopes of reducing the large wait time disparities between candidates living in different parts of the country by allowing for broader geographic sharing. Other approaches considered have included defining geographic zones as a function of the population density or supply/demand ratio.
Apart from strict geographic borders, this model also will remove other distinct classifications such as constraint to within the same blood type and allowing for donation to occur across compatible blood types, as is done with other solid organ transplants. In addition, under the current KAS-based system, certain factors determine the order in which these candidates are prioritized in a match run, regardless of their priority score (Fig. 2). For example, local pediatric candidates listed before age 18 are given priority over local candidates with a cPRA of 99%, even if their priority score is lower (Fig. 2). The goals of the new continuous distribution framework are to change how candidates are prioritized on the match run by considering all relevant attributes and factors together to generate a composite allocation score (Fig. 4). These factors may include those related to candidate biology (blood type, cPRA), medical urgency, efficient allocation practices, post-transplant outcomes, and ensuring equity in a candidate's access to transplant. Each category/factor is assigned a predefined weight according to its relative importance, which is to be determined by the transplant community. Within each category/factor, a candidate's attributes also must be converted into points, with consideration of whether relative differences in these points are linear, exponential (as in cPRA), or some other function. A candidate's composite allocation score is the sum of all points weighted by category. Allocation then is based on a single list of all candidates, each ranked according to their composite score.
Figure 4A schematic of the proposed “continuous distribution” allocation model. Candidates will no longer be grouped into rigid categories. Instead, all compatible candidates will be ranked on the match run according to a composite allocation score that will involve a combination of their allotted points within each category/factor and the pre-defined weight of each factor based upon its relative importance. Panel A shows a list of potential factors to be considered and the hypothetical weights assigned to them to generate the composite allocation score. Panel B shows a hypothetical example of four candidates with differing attributes. Within each category, the candidate is assigned points which are then multiplied by the relative weight assigned to the category/factor. The patient's composite score is then the sum of all points weighted by category. Candidates are then ranked based on their composite scores, with higher scores given increasing priority.
As an intermediary step toward elimination of DSAs, UNOS/OPTN redefined geographic boundaries in March 2021 with the goal to improve equity in access regardless of candidate residence or place of listing. Under this intermediary model, the classification-based system remains, but local allocation was redefined to a 250-NM radius circle from the donor hospital, and proximity points were added to a candidate's total allocation score. For full details on classifications and assignment of priority points under this system, see OPTN Policy 8, effective July 2022.
This radically changed the operational definition of local allocation. Modeling suggests that under the 250-NM system, kidneys procured at a given hospital have a median of 23 centers and a maximum of 73 centers that are considered local, compared with a median of 5 and a maximum of 15 centers under the old KAS allocation.
Greater complexity and monitoring of the new Kidney Allocation System: implications and unintended consequences of concentric circle kidney allocation on network complexity.
Rather than working primarily with a single OPO, transplant programs now have to interact with as many as 18 different OPOs. OPOs now are responsible for placing locally allocated kidneys at a median of 34 different transplant centers, compared with 3 before the 250-NM boundary change. This has led to significant impact on organ allocation complexity, leading to inefficiencies in placing organs (such as challenges involved with travel logistics and crossmatch testing), significant burdens on workflow for both OPOs and centers, and an anticipated increase in costs.
A 1-year postimplementation review performed by UNOS/OPTN showed transplant rates increased by 16% overall, with substantial improvements in several population groups. Notably, transplant rates increased by 63% for pediatric candidates, 78% for candidates with a cPRA of 80% to 97%, 36% for candidates with 3+ years of dialysis time at listing, and 20% to 30% increases for minority candidates.
These benefits were offset by increases in median cold ischemic time (from 17 to 19 hours postimplementation) and an increased rate of DGF from 29% to 31%, reflecting the increase in median distance between the donor and transplant hospitals from 68 to 121 NMs. The overall discard rate increased from 22% to 25%. The increased logistical complexity is highlighted by the increase in the proportion of transplants occurring at hospitals outside the DSA of the recovering OPO, which doubled from 30% to 60%, and may explain the adverse effects on organ allocation and utilization. Although 6-month post-transplant patient and graft survival remain unchanged, it is premature to see the effects on graft, recipient, and waitlist candidate outcomes. UNOS/OPTN plans to release a 2-year postimplementation report with additional metrics. This close monitoring is warranted to ensure the changes improve geographic disparities and do not inadvertently change practices or processes that result in or exacerbate other imbalances. This close scrutiny also will inform future iterative changes, such as the plan to eliminate hard geographic boundaries altogether, and allow for readjustments in policy to mitigate against unintended consequences.
OTHER ORGAN ALLOCATION SYSTEMS AROUND THE WORLD
Australia
Australia has a fully nationalized kidney transplant system that operates across the country almost exclusively through the public hospital system. Underpinning the transplant system is the Australian and New Zealand Dialysis and Transplant Registry, which keeps a detailed record of every kidney transplant patient in Australia since 1965 when transplantation began.
As a country, the sheer distances between donor organ retrieval transplant centers poses huge challenges on the successful sharing of organs, yet through a centralized and federally funded Organ and Tissue Authority, a network of donor coordinators placed within hospitals has dramatically increased deceased donor transplantation in the past 7 years. Allocation traditionally has been heavily HLA-based, with approximately 20% of organs transplanted being transplanted on HLA matching and 80% on waiting time. Recent studies have focused on disparities in access to transplantation based on geography—with significant disadvantage being shown for those living in the larger, more populous states (New South Wales and Victoria).
Although universal health care is federally funded in Australia (via a Medicare levy), the delivery of transplantation and health care itself is a state responsibility. Organ allocation, however, is controlled by the Australian Federal Department of Health, through the Organ and Tissue Authority and a new allocation program called Organ Match, which was launched in April 2019.
In 2021, the Australian organ allocation system changed in Organ Match with the following aims: (1) improving access to transplant for highly sensitized patients; (2) improving utility of donor organs; and (3) improving accessibility for HLA matching for younger patients and homozygous recipients. To improve access for very highly sensitized patients, the allocation scoring system has been changed to preference allocation to recipients with the upper levels of sensitization (from >99.7%). With the aim of improving utility of the transplant, the EPTS score (calculated from time on dialysis, previous transplant, and age) has been added to state and national algorithms. The KDPI also is included in the allocation system, and, in combination with the EPTS score, the first level of allocation now ensures the EPTS–KDPI score is less than 50. Clinicians also have the discretion to set a maximum KDPI for a specific recipient. Finally, because it is well recognized that good HLA matching is beneficial to younger patients, the new allocation system prioritizes HLA matching in transplant candidates with lower EPTS preferentially.
The initial analysis of the first 10 months of the new allocation system and nearly 580 transplants showed that it had achieved the goals that were set, with a higher rate of organ shipping between states (33%), with kidneys being allocated to highly sensitized individuals (eg, a patient in their 50s with a cPRA of 99.5% received a kidney offer having waited 12.3 years on dialysis). An analysis of KDPI and EPTS confirmed that better-quality kidneys were being sent. With an increasing emphasis on consumer engagement in health care the challenge for new allocation systems worldwide will be to include patient-reported outcome measures as identified by the Standardised Outcomes in Nephrology–Transplantation investigators as key outcomes that consumers worldwide regard as critical outcomes after kidney transplantation.
Developing consensus-based priority outcome domains for trials in kidney transplantation: a multinational Delphi survey with patients, caregivers, and health professionals.
At the same time, Hong Kong also promotes kidney transplantation as an important modality as kidney replacement therapy (KRT). Kidney transplantation enhances patient survival and quality of life, with good symptom management for ESKD patients.
The donation rate for deceased organs in Hong Kong was between 4.3 and 7.5 per million population and remained low when compared with Western countries such as the United States and Spain.
Despite promotional activities of kidney donation by the government and academic societies, the donation rate needs to be enhanced further for supporting ESKD patients who have been wait-listed for a long time.
The Renal Registry of Hong Kong is a direct, online, computerized registry system developed by the Central Renal Committee, Hospital Authority, to capture data of all public KRT patients in Hong Kong under Hospital Authority. It was first implemented in 1995 with special renal registry terminals in all renal units for data entry and retrieval to a central server.
The Renal Registry is part of the Organ Registry and Transplant System, which has a component of other organ registries: Organ Procurement System and Transplant and Immunogenetics System. An important function of the Renal Registry is to serve the central Cadaveric Kidney Allocation. A scoring system based on the years on KRT, HLA matching, and the age of patients is developed to determine the priority of the potential recipient list.
Currently, there are 16 renal dialysis centers in Hong Kong with 4 kidney transplant centers. When there is a deceased donor, the organ donor coordinators, transplant nephrologists, and surgeons and nurses can make use of the Organ Registry and Transplant System to input the potential donor demographics, clinical conditions, immunologic and virology results, as well as retrieve the results for kidney allocation. One designated Transplant and Immunogenetics laboratory centralizes the transplantation immunogenetics and tissue typing services of all of Hong Kong.
The concept of distributive justice in organ allocation has been incorporated into Hong Kong's allocation system, which has taken into consideration equal access and maximum benefit. The equal access criteria include length of time waiting (ie, first-come, first-served) and age (ie, youngest to oldest). To encourage equality in organ transplantation, the equal access theory encourages a distribution process for transplantable organs that is free of biases based on race, sex, income level, and geographic distance from the organ. Obviously, the small size of the city of Hong Kong means that geographic distance is not an issue.
The goal for maximum benefit criteria is to maximize the number of successful transplants and maximum benefit criteria can include medical need (ie, the sickest people are given the first opportunity for a transplantable organ) and probable success of a transplant (ie, giving organs to the person who will be most likely to live the longest). This is in the Hong Kong allocation system with zero mismatch and emergency cases having the priority to override the scoring system to get the kidney. The order of listing of recipients on the waiting list, other than zero subgroup mismatches or emergency cases, is as follows: age, years on waiting list, HLA matching, and clinical conditions. If the recipient has more than an 80% panel of reactive antibodies, the patient will have additional points in the scoring system.
In Hong Kong, the deceased donor is categorized according to the following age group: (1) pediatric (<13 y), (2) adult (13-60 y), (3) senior (61-70 y), and (4) advanced age (>70 y). There is an algorithm for donor age to match with the recipient age group listing priorities. When the donor is an adult (13-60 y), the recipient priority will be as follows: adult together with pediatric > senior > advanced. When the donor is a senior (61∼70 y), the recipient priority will be as follows: senior > adult > advanced. When the donor is an advanced age (>71 y), the priority will be as follows: advanced age > senior > adult. When the donor is a pediatric patient (<13 y), the recipient priority will be as follows: pediatric (<13 y) > adult together with pediatric ≥13 years old > senior > advanced age.
It is interesting to see that age is used as a proxy to calculate for medical efficiency. With the aging population getting healthier than, for example, a decade ago, the equation that the gain of years of what a senior candidate can achieve from a kidney transplantation (compared with remaining on dialysis) will not necessarily be much lower than that for a younger recipient. Sometimes the concept of frailty may give an additional factor for consideration in the aged population and not just relying on the chronological duration of life. A recent study showed that frailty predicted both kidney transplant wait-listing and subsequent delisting. Frailty interacted with body composition on transplant wait list delisting.
If a patient on the waiting list has previously donated a kidney for transplant purposes, he will have priority in receiving an ABO-compatible deceased donor kidney once available. This principle of reciprocity (rewarding past sacrifice) also has been a long-standing policy in the United States, with prior living donors given priority over most other candidates (Fig. 2). In Australia, there is also a priority listing for previous kidney donors who have end-stage kidney failure. In other countries such as Israel, there also have been practices that those who have been registered to be organ donors be given priority bonus points should they have the need for an organ, as a way to incentivize organ donation (further discussed by Chow et al
All in all, the donor kidney allocation system in Hong Kong is trying to provide equal access, aiming for maximal benefit under the constraints of the small number of donor kidneys available.
CONCLUDING REMARKS
An ideal system for allocating deceased donor organs should seek to achieve the greatest good for the greatest number of people. It also must be fair and not disadvantage certain populations. However, the benefits of broadening organ distribution to reduce disparities also must be balanced with considerations of cost, logistics, efficiency, and any adverse effects on organ quality or utilization. Although numerous changes have been made to ensure a more equitable system that also promotes maximal utility, further improvements to promoting organ donation and improving utilization rates must be made to reduce the gap between supply and demand, and make access to transplant equitable for all in need of a life-saving organ.
REFERENCES
Persad G
Wertheimer A
Emanuel EJ.
Principles for allocation of scarce medical interventions.
(In)Textbook of Organ Transplantation. Allan D. Kirk, Stuart J. Knechtle, Christian P. Larsen, Joren C. Madsen, Thomas C. Pearson, Steven A. Webber. John Wiley & Sons, Ltd,
2014: 1645-1653https://doi.org/10.1002/9781118873434.ch137
The national landscape of deceased donor kidney transplantation for the highly sensitized: transplant rates, waitlist mortality, and posttransplant survival under KAS.
Racial/ethnic disparities in waitlisting for deceased donor kidney transplantation 1 year after implementation of the new national kidney allocation system.
Greater complexity and monitoring of the new Kidney Allocation System: implications and unintended consequences of concentric circle kidney allocation on network complexity.
Developing consensus-based priority outcome domains for trials in kidney transplantation: a multinational Delphi survey with patients, caregivers, and health professionals.
00056-0&id=gr1.jpg){kind=link}
00056-0&id=gr2.jpg){kind=link}
00056-0&id=gr3.jpg){kind=link}
00056-0&id=gr4.jpg){kind=link}