American Journal of Transplantation 2015; 15: 2117–2125 Wiley Periodicals Inc.
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Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13362
Increasing the Number of Organ Transplants in the United States by Optimizing Donor Authorization Rates D. S. Goldberg1,2,3,*, B. French2,3, P. L. Abt4 and R. K. Gilroy5 1
Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 2 Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 3 Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 4 Division of Transplantation, Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA 5 Center for Transplantation and Department of Medicine, University of Kansas Medical Center, Kansas City, KS Corresponding author: David Goldberg, [email protected]
While recent policies have focused on allocating organs to patients most in need and lessening geographic disparities, the only mechanism to increase the actual number of transplants is to maximize the potential organ supply. We conducted a retrospective cohort study using OPTN data on all ‘‘eligible deaths’’ from 1/1/08 to 11/1/13 to evaluate variability in donor service area (DSA)-level donor authorization rates, and to quantify the potential gains associated with increasing authorization rates. Despite adjustments for donor demographics (age, race/ethnicity, cause of death) and geographic factors (rural/urban status of donor hospital, statewide participation in deceased-donor registries) among 52 571 eligible deaths, there was significant variability (p < 0.001) in donor authorization rates across the 58 DSAs. Overall DSA-level adjusted authorization rates ranged from 63.5% to 89.5% (median: 72.7%). An additional 773–1623 eligible deaths could have been authorized, yielding 2679–5710 total organs, if the DSAs with authorization rates below the median and 75th percentile, respectively, implemented interventions to perform at the level of the corresponding reference DSA. Opportunities exist within the current organ acquisition framework to markedly improve DSA-level donor authorization rates. Such initiatives would mitigate waitlist mortality while increasing the number of transplants.
Abbreviations: DCD, donation after cardiac death; DSA, donor service area; HRSA, Health Resources and Services Administration; KDPI, kidney donor profile index; LAS, lung allocation score; MELD, Model for End-Stage Liver Disease; OPOs, organ procurement organizations; OPTN, Organ Procurement and Transplantation Network; RUCA, rural urban commuting area; UNOS, United Network for Organ Sharing Received 11 December 2014, revised 23 February 2015 and accepted for publication 26 February 2015
Introduction The Organ Procurement and Transplantation Network’s (OPTN) Strategic Plan includes six key goals for improving the national organ transplant system in the United States. The top priority, as stated by the OPTN Board of Directors, is to increase the number of transplants among patients with end-stage organ disease (1). Despite this priority, substantial effort has been devoted to proposals that focus on altering the distribution of the current organ supply, and/ or modifying waitlist prioritization. Policies that focus on waitlist priority would not, however, increase the overall number of transplants because such policies simply redistribute the existing supply. The mechanisms with the greatest potential to increase the number of transplants include: greater use of medically compromised organs (e.g. donation after cardiac death [DCD] donors); reducing organ discards; increasing living donation; and maximizing the use of potential donors through increased authorization rates. Increased use of extended criteria donors may compromise the survival of transplant recipients (2–6). DCD and living donation are restricted almost uniformly to kidney and liver transplants (7) (with a small number of lung transplants), and would be insufficient to substantially increase the organ supply (8). In contrast to each of these, optimizing the collective performance of organ procurement organizations (OPOs), critical care physicians, donor hospitals, transplant centers, and the general public to increase donor service area (DSA)-level donor authorization rates may provide the best opportunity to help the OPTN achieve its goal. 2117
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The responsibility for coordinating all aspects of organ procurement—from communication with donor families, working with the local donor hospital and transplant center, to providing education to promote organ donation—is the domain of the local OPO (9). Although the OPO may subsume the administrative accountability for organ procurement, responsibility for the process of identifying and sustaining potential organ donors is shared much more broadly including the donor hospitals, physicians caring for potential donors, and the donor families and their communities. OPOs, working in collaboration with the transplant community to share best practices have previously demonstrated a substantial increase in the number of US organ donors (10,11). While data suggest there is substantial geographic variability in authorization rates of ‘‘eligible deaths’’ (hospitalized brain dead patients 70 years of age without any exclusionary medical conditions) (7,9,12,13) at the DSA level, the potential etiology of such variability is unknown. It has been posited that this inter-DSA variability is due to geographic distribution of racial/ethnic minorities, who are known to have lower authorization rates (14–19). Yet there are no empiric data that support this hypothesis, or to quantify the potential gains associated with optimizing DSA-level donor authorization rates. The 2003 Health Resources and Services Administration (HRSA)-sponsored collaborative effort was successful in improving OPO performance and increasing organ donation. Similar renewed efforts could potentially help to increase the number of donors, save more lives than the current system, and potentially mitigate some of the geographic disparities when implemented in concert with broader organ sharing by increasing the overall organ pool for the transplant community. In order to quantify the potential opportunities for increasing deceased organ donation through evaluation, we sought to test two hypotheses: (1) variability in DSA-level donor authorization rates is not explained simply by different racial/ethnic demographic characteristics, age, or cause of death of the potential donor population within each DSA; and (2) the potential to increase donation activity associated with optimizing donor authorization rates equals or exceeds gains from proposals focused solely on redistributing the current organ supply. These data can be used to initiate a broader dialogue within the transplant community on how to define the potential donor pool and ways in which authorization of potential donors can be improved.
Methods Study design and data source All analyses used an OPTN/United Network for Organ Sharing (UNOS) dataset on all eligible deaths from 1/1/08 to 11/1/13. As part of the Hospital Conditions of Participation in the Medicare program, the Health Care Financing Administration mandates that participating hospitals contact their OPO about individuals whose death is imminent or who die in the hospital (20). Hospitals within certain DSAs may report a larger number of imminently brain-dead patients due to requests by their local OPO (e.g.
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some OPOs request referrals for older potential donors, including those >75 years of age). Yet, despite these differences, the definition of an eligible death is a standardized, uniformly applied OPTN definition—a patient 70 years of age: (1) declared brain-dead according to hospital policy and (2) who lacked exclusionary medical conditions to organ donation. All patient-level data must be submitted by the OPOs to the OPTN (7,12,21–24), with the definition of an eligible death uniform across all OPOs. While eligible deaths represent a fraction of in-hospital deaths (25), >95% of all deceased liver donors derive from this eligible-death patient pool (8,23,25).
Study outcomes The primary outcome was whether authorization for organ donation was obtained, defined as from next-of-kin (Consent-Yes) or through a registry or a legal document (Registry-Yes).
Statistical analysis A mixed-effects logistic regression model for the patient-level outcome of authorization was used to quantify and test for variability in DSA-level authorization rates. The model adjusted for observed characteristics associated with variation in authorization rates: age; sex; race/ethnicity, as defined by UNOS (18) (white, black, Hispanic, Asian, multi-racial, or other); cause of death (stroke, head trauma, anoxia, brain tumor, other) (18); ‘‘timely’’ versus not ‘‘timely’’ referral of the eligible death, defined by the OPO; weekend versus weekday status of eligible death referral (26); rural versus urban status of the donor hospital, defined using the modified rural urban commuting area (RUCA) measure based on the zip code of the hospital (27,28); number of transplant centers in a DSA; and the percentage of a state’s population enrolled as an organ donor through a state-sponsored registry (29). An interaction term between age and race/ethnicity was used given the potential for differences in authorization rates based on age within racial/ethnic groups (i.e. differences in cultural beliefs towards donation among different generations). The model included DSA-level random intercepts to quantify unobserved variability in the odds of authorization across OPOs after adjustment for observed covariates, as well as to account for the correlation due to clustering of patients within DSAs. We conducted a hypothesis test of no unobserved heterogeneity across DSAs after adjusting for patient-level factors based on the variance of the DSA-level random intercepts, with the null-hypothesized value of 0 indicating no unobserved heterogeneity (i.e. p < 0.05 indicated statistically significant differences in DSA authorization rates after adjustment for the observed characteristics listed above). We calculated DSA-specific authorization rates, adjusted for patient-level covariates, using postestimation summaries obtained from the mixedeffects logistic regression model described above. We computed an adjusted rate of authorization by standardizing the observed rate to the expected rate based on the mixed-effects logistic regression model (30). If the adjusted rates of authorization differed among DSAs, such variation indicated that DSA-level differences were due to DSA-level factors/OPO performance or unobserved factors. Because of the potential for unmeasured differences of the racial/ethnic categories in UNOS that could potentially contribute to DSA variability, we performed a subgroup analysis among eligible deaths who were white and ages 18–39 years (the racial/ ethnic and age categories previously shown to have the highest authorization rates). These analyses allowed for verification that DSA variability was not explained solely due to differences in the age and racial/ethnic characteristics of eligible deaths in an DSA (18). To simulate the potential increase in the number of organ donors if interventions were enacted to increase donor authorization rates among DSAs with lower rates, we calculated the difference between a DSA’s adjusted authorization rate and that of (1) the median performing DSA and
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Increasing the Number of Organ Transplants (2) the OPO in the 75th percentile. The difference between the DSA’s adjusted authorization rate and that of the reference DSA was used to calculate the potential number of increased authorized donors within a DSA. The organ yield per donor was then calculated based on the organ yield per donor from each of the 58 DSAs in 2011, the midpoint of the study period (31).
rate between 70.0% and 75.0% (Figure 1A). Additionally, within individual UNOS regions, there was broad variability in adjusted authorization rates (Figure 1B). The differences in adjusted authorization rates (accounting for factors
All analyses were performed using Stata 13.0 (College Station, TX). This study was approved by the Institutional Review Board at the University of Pennsylvania.
Results From January 1, 2008 through November 1, 2013, there were 52 571 reported eligible deaths, from which authorization for donation was obtained in 38 432 (73.1%) cases. Of the 38 432 authorized donors, 30 870 (80.3%) were obtained from family or next-of-kin (with or without prior registration in a donor registry), while 7562 (19.7%) were based on registration in a donor registry. The median age of eligible deaths was 43 (IQR: 25-54), with 30 700 (58.4%) males (Table S1). Potential donor age, racial/ethnic category, cause of death, timeliness of the eligible death referral, weekday referral, and RUCA classification of the donor hospital were all significantly associated with authorization rates (Table S2). Although there was a significant interaction between donor age and race/ethnicity, there was only a moderate inverse relationship between the DSA-level proportion of eligible deaths that were a racial/ethnic minority and authorization rates in the DSA (r ¼ 0.57). There was no association between the proportion of patients in a state registered as an organ donor through a state-sponsored registry (p ¼ 0.80) or the number of transplant centers within a DSA (p ¼ 0.92) and authorization rates in multivariable models. There was a strong positive correlation (r ¼ 0.83) between a DSA’s overall unadjusted authorization rate and its authorization rate of ideal donors ages 18–39 years. Unadjusted and adjusted DSA-specific rates of authorization for donation The unadjusted authorization rates varied considerably across the 58 DSAs: 85.8% in the highest-performing DSA versus 57.7% in the lowest-performing DSA. Despite adjusting for patient and geographic factors independently associated with authorization (Table S1), there still were significant differences in authorization rates across the 58 DSAs (p < 0.001). This unobserved variability in authorization rates across DSAs was likely due to unmeasured factors, inherent baseline differences in OPO performance and process-of-care measures (i.e. training of OPO staff, interactions and outreach with donor hospitals, or broader community-based education), or a combination of the two. The adjusted authorization rates of all eligible deaths across the 58 DSAs ranged from 63.5% to 89.5%, with nearly onehalf of DSAs (28/58) having an overall adjusted authorization American Journal of Transplantation 2015; 15: 2117–2125
Figure 1: Adjusted rates of authorization for organ donation within donor service areas in the United States from January 1, 2008 through November 1, 2013. (A) Density plot shows the distribution of adjusted authorization rates among all eligible deceased donors across all donor service areas; p < 0.001 indicated statistically significant variability in adjusted authorization rates across donor service areas. (B) Adjusted authorization rates according to geographic region; each point represents an organ procurement organization. (C) Density plot to shows the distribution of adjusted authorization rates across all donor service areas among eligible deceased donors who were white and between 18 and 39 years old.
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associated with authorization other than age and race/ ethnicity) across DSAs persisted in subgroup analyses restricted to all eligible deaths among whites, ages 18–39 years (n ¼ 9939), ranging from 71.5% to 91.8% (Figure 1C), with significant heterogeneity in adjusted authorization rates across the DSAs (p < 0.001). There was no association between the number of organ donors (overall or ideal) and authorization rates (data not shown).
authorized eligible deaths/year) could potentially have authorized for donation during the study period. Nearly one-third of the increased donors were located in Region 9 (Figure 2A, Table S3). If DSAs performing below the 75th percentile enacted measures to increase donor authorization to the 75th percentile-performing DSA, the potential increased yield of authorized donors during the study period would have been 1623 (average of 278 increased authorized eligible deaths/year; Figure 2B, Table S3).
Potential increase in authorized donors The median adjusted authorization rate among the 58 DSAs was 72.7% (Figure 1A). If the 28 DSAs performing below the national median implemented interventions to increase their authorization rates to the median, then a total of 773 increased eligible deaths (average of 132 increased
Increased donor authorization rates could potentially yield an additional 2679 organs over the study period if DSAs currently performing below the median level could achieve such targets, and 5710 additional organs if all DSAs performed at the level of the current 75th percentile (Table 1).
Figure 2: (A) Simulated increased in eligible deaths consenting (authorizing) for donation if ‘‘low-performing’’ DSAs had authorization rates at the level of the median DSA in the US from 2008 to 2013, n ¼ 773 nationally. Increase in authorized donors is based on simulated outcomes if the 43 DSAs with adjusted authorization rates below the adjusted national 75th percentile for all DSAs from 1/1/08 to 11/1/13 had instituted interventions to improve their adjusted authorization rates to that of the 75th percentileperforming DSA. Numbers represent UNOS region. (B) Simulated increased in eligible deaths consenting (authorizing) for donation if ‘‘low-performing’’ DSAs had authorization rates at the level of the 75th percentile DSA in the US from 2008–2013, n ¼ 1623 nationally. Increase in authorized donors is based on simulated outcomes if the 43 DSAs with adjusted authorization rates below the adjusted national 75th percentile for all DSAs from 1/1/08–11/1/13 had instituted interventions to improve their adjusted authorization rates to that of the 75th percentile–performing DSA. Numbers represent UNOS region.
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Increasing the Number of Organ Transplants Table 1: Potential increase in transplantable organs with increased donor authorization rates, 2008–20131 Organ
DSAs with authorization below the median1
DSAs with authorization below the 75th percentile2
1385 660 257 231 134 13 2679
2931 1366 600 488 293 29 57103
healthcare costs would be delivered to the system by shortening both the time and number of patients waiting across all organ categories (33,34).
Conclusions
Despite the OPTNs stated priority to increase the number of organ transplants, recent efforts, and media attention have, however, focused on redistributing the current organ supply, and altering the prioritization scheme for waitlisted patients (19,35–40). Such recently approved policy proposals or considerations include: the new kidney donor profile index (KDPI) (38) for prioritization of patients on the kidney transplant waitlist (41); initiation and subsequent modifications to the lung allocation score (LAS), which prioritizes patients for lung transplants (36,37,39,40); and altering the distribution of transplantable livers by redrawing distribution maps (14,19). These policy revisions focus solely on how to utilize the current supply of transplantable organs, without directly increasing the authorization rate of potential donors, thus increasing the absolute number of transplants. Yet measures to increase the organ supply through improvements in DSA-level authorization rates, in conjunction with other policy revisions, may serve to improve the current system of organ transplantation while also helping to mitigate geographic disparities.
This analysis of the national cohort of identified potential brain-dead organ donors from 2008 to 2013 illustrates marked variability in authorization rates, leading to a substantial number of unrealized organ transplants. This variation in DSA authorization rates was not fully explained by differences in the demographic characteristics of the potential donor pool within a geographic area. This is underscored by the significant variability in donor authorization rates when adjusting for such demographic characteristics, and the persistent differences in performance when restricted to the highest authorizing cohort of white patients ages 18–39 years. The root causes of these differences in authorization rates cannot be solely attributed to the local OPO. Although the OPO has administrative responsibility for authorization and organ donation, these are complex processes that ultimately reflect the broader support of the community, including the donor families, the donor hospitals, and the staff of these hospitals. Improving donor authorization rates would require not only OPObased initiatives, but those that target the wider community, which the OPO serves. Reapplying interventions similar to those used in the highly successful Organ Donor Breakthrough Collaborative (32) would likely assist the OPTN and the organ donation and transplantation community to achieve the OPTNs most important goal listed for 2014–2015. Increasing donor authorization rates also has the greatest potential to minimize geographic disparities in access to organ transplantation by providing a greater pool of donor organs to be applied to any measure seeking to address geographic disparities. When considered on a national scale, donation provides a substantial economic benefit by increasing the total number of transplants across all solid organ categories. By this, a greater reduction to
As an example, the recent OPTN/UNOS proposal for liver redistribution seeks to redraw distribution maps in order to normalize Model for End-Stage Liver Disease (MELD) scores, an index of disease severity, across the country by more broadly sharing livers. Such redistricting would change the available donor pool in certain geographic regions in order to minimize waitlist mortality in other areas. Simulations suggest a decrease of 332 to 554 waitlist deaths over 5 years (14,19). However, this policy, while important with regards to helping to minimize geographic disparities, would have little influence on the overall national mismatch between organ supply and demand (42). Furthermore, the impact of this policy on waitlist mortality in areas that will see a great reduction in their volume of liver transplants, in particular those centers serving patients dispersed over a large geographic area at greatest risk of waitlist mortality (43), is unknown. The data in this manuscript also show that certain regions that stand to benefit the greatest from redistribution would also achieve the greatest increase in transplant numbers from optimization of DSA-level donor authorization (e.g. Region 9). Although other regions might have much smaller increases based on our analyses (e.g. Region 1), all regions ultimately would benefit from optimized OPO performance. Efforts to maximize DSA-level donor authorization rates are complementary to broader organ sharing, and could potentially be instituted in concert with redistribution proposals. Under redistribution, ‘‘high-MELD’’ regions (e.g. Regions 1 and 5), which only would have a small increase in donors with improved authorization rates, would benefit from improved authorization in ‘‘low-MELD’’ regions (e.g. Region 3). However, broader sharing alone would not allow the OPTN to meet its stated goal. Importantly, whether and
Kidney Liver Lung Heart Pancreas Intestine Total
1 The estimated organ yield is based on Scientific Registry of Transplant Recipients (SRTR) data from 2011, and represents the current organ yield per donor for each of the 58 DSAs (26). 2 Low-performing DSAs defined as the 28 DSAs whose adjusted rates of authorization for donation of all eligible deaths from 1/1/08 to 11/1/13 were below the adjusted national median for all DSAs of 72.7%. 3 Low-performing DSAs defined as the 43 DSAs whose adjusted rates of authorization for donation of all eligible deaths from 1/1/08 to 11/1/13 were below the adjusted national 75th percentile for all DSAs of 75.4%.
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how broader sharing might impact the relationships between OPOs, donor hospitals, transplant centers and the donor communities is not understood. Our work is the first to use national data on reported potential brain-dead organ donors to examine variability in DSA-level donor authorization rates and to look to quantify what gains in donation rates might exist. Importantly, the current analysis did not demonstrate that differences in demographic characteristics (i.e. age, race/ethnicity) and geographic factors (i.e. rural/urban status) explain most of the geographic variability in donor authorization rates as we had expected it might. Thus, opportunities for increasing donation exist. Previous studies have attempted to quantify geographic differences in the absolute number of potential brain-dead organ donors, yet these studies relied on death certificate data to define the ‘‘underlying organ donor potential (23,44).’’ Unfortunately, death certificates do not classify a patient as brain-dead and cannot determine a patient’s eligibility as a potential organ donor (45). Despite these limitations, there are geographic differences in causes of death in the population, such as those seen between the Northeast and Southern regions of the United States. As a consequence, the likelihood of an eligible donor amongst hospital deaths will vary geographically (44). These data should not be used in isolation as a metric to predict OPO performance in organ acquisition for deceased donor transplantation. Eligible deaths do not include potential DCD, brain-dead patients >70 years of age, or potential donors who are imminently brain-dead, but the opportunity for organ donation is declined by next-of-kin. These too are potential donors that serve to increase the number of transplants. The definition of an eligible death as set forth by the OPTN is an imperfect measure of potential donors. Given hospital differences in brain death criteria (i.e. clinical criteria alone vs. clinical þ imaging), patients being >70 years of age excluded from reporting when they may in fact be eligible donors, and non–brain-dead donors not being considered within this definition, we agree a more optimal metric needs to be created. Utilization of eligible death data allows for an estimate of the minimal potential opportunity for increases in the number of organ donors. However, to use this metric to compare regional OPO performances and to classify an OPO as ‘‘good’’ or ‘‘bad’’ should not occur as factors beyond the OPOs control also impact eligible donor conversion. In order to accurately capture all potential donors, greater partnership with donor hospitals is needed if we seek to capitalize on all donation opportunities. Further refinement of brain-death declaration and tracking of hospital reporting will also enhance our donation potential as a transplant community. This is underscored by the differences in the number of eligible deaths based on OPTN/UNOS data, versus direct chart review (23). Also, it must be noted that the responsibility to successfully ‘‘convert’’ an eligible death falls not only to the OPO, but to all clinical entities caring for these patients, as well as a greater understanding within the community of 2122
the value of donation. Nevertheless, eligible deaths represent greater than 85–95% of the national pool of deceased donor transplants, depending on the organ type, and thus these data help to quantify the potential gains in organ donation with increased authorization rates. Additionally, Centers for Medicare and Medicaid Services (CMS) evaluations of an OPO’s donation rate is based on the number of eligible deaths (46). Nevertheless, a broader dialogue in the transplant community is needed in order to refine the eligible death definition, define additional objective metrics of OPO performance, and develop initiatives to improve the process of donor authorization. The current analysis demonstrates the potential for increasing the donor pool by optimizing DSA-level donor authorization rates. Variability in DSA-level donor authorization rates may be attributable to any and/or all aspects of the donation process, which includes factors independent of the OPO: relationships between donor hospitals and OPOs, relationships between OPOs and transplant centers, early involvement of OPOs prior to declaration of brain death, education initiatives for the public and for donor hospitals, differences in training of OPO staff, use of ethnicity-matched requestors for donation (32), differing OPO management structures, staffing models of individual OPOs (i.e. OPOs that accept organ referrals 24/7 vs. others that have limited staffing overnight), and/or public opinion of organ donation. Further efforts to identify and target barriers to donation have the potential to increase opportunities for transplantation (47–53). Targeted increases in tracking of DSA-level donor authorization rates by regulatory authorities may also be advisable. These initiatives alone may not allow for maximization of the potential organ supply. The CMS should consider policies at both the hospital and OPO level. These could include: increased financial penalties for hospitals that fail to refer eligible deaths in a timely manner; financial rewards for hospitals that refer the highest proportion of eligible deaths in a timely manner; decreased payments to OPOs that consistently have the lowest authorization rates beyond some prespecific rate; or increased payments to those that consistently perform at some prespecific target rate. In order to optimize and standardize DSA-level donor authorization rates, qualitative research is needed to identify the characteristics of the highest performing OPOs in contrast to those with authorization rates below the median. Mixed-methods qualitative research could utilize surveys of all OPO leaders to garner broad data on process-of-care measures of all OPOs, while also organizing focus groups restricted to executives of the highest- and lowest-performing OPOs. However, some potential initiatives, in part based on interventions proven to be successful based on the first HRSA-sponsored Organ Donor Breakthrough Collaborative (32), include: (1) increased OPO oversight of hospitals to ensure all potential organ donors are referred to the OPO in a timely manner; (2) uniform best-practices of OPO requestors, based on metrics of OPOs with the highest authorization rates; (3) dispatching American Journal of Transplantation 2015; 15: 2117–2125
Increasing the Number of Organ Transplants
the most effective requestor from an OPO to obtain authorization for donation; (4) ensuring that all OPOs provide 24/7 coverage for organ referrals; (5) employing uniform team huddles and debriefings across al OPOS; (6) increasing funding for national educational initiatives to increase organ donor awareness and/or and support for organ donation, targeting states that have traditionally been underserved with education; (7) required use of ethnicity-matched requestors when appropriate; (8) financial rewards or disincentives to hospitals that do not refer eligible deaths in a timely manner; and (9) utilizing secure electronic health records to streamline the referral process of eligible deaths. This study has limitations. First, OPOs receive a large number of referrals regarding in-hospital deaths that do not qualify as eligible deaths (25). While the majority of these referrals have medical contraindications to donation, a subset have neurologic injury not yet meeting brain death criteria (25). Eligible death data are still more reliable than death certificate data due to potential misclassification of causes of death, and inability to ascertain brain death from a death certificate. Second, there is the potential for underreporting of eligible deaths. If such under-reporting exists, it would be expected to falsely lower the number of eligible deaths. There are no objective data to demonstrate that under-reporting of eligible deaths is occurring, or that there is geographic variability in reporting practices. Because OPOs are subject to audits and work in collaboration with other OPOs, we believe these data are accurate. Furthermore, OPOs with the lowest authorization rates are also those with the fewest donors-per-million population, which suggests an absence of under-reporting of eligible deaths. We believe OPOs should continue to be responsible for reporting eligible deaths to the OPTN, yet greater oversight of the system, akin to the audits of transplant centers, may offer opportunities to further improve the system of organ donation. Continuous reviews of the process by which eligible donors are identified and outcomes are tracked are just two examples of these potential opportunities. Third, the decision underlying the denial of authorization was not captured. While this is important for future efforts to design interventions to improve authorization rates, the lack of such data does not discount the results of marked OPO variability. Fourth, we could not precisely calculate the hypothetical yield of potential organs through increased authorization rates due to lack of available medical data on nonauthorized donors. Yet a yield of increased organs at 50% of the estimated hypothetical yield would still result in 1300–2850 transplantable organs over a nearly 6-year period. Fifth, the OPTN/UNOS data is insufficient to account for variables that may contribute to donor authorization rates among racial/ethnic minorities, including country of origin or years of residence in the United States. Among racial/ethnic minorities (i.e. immigrants from Asian countries), viewpoints on organ donation versus receiving an organ may differ among first-generation immigrants versus second- and third-generation. These facts would not explain our results though, because although there may be some variation in American Journal of Transplantation 2015; 15: 2117–2125
authorization rates due to fixed preferences about donation among certain racial/ethnic minorities, this cannot explain the marked variability in the subgroup of white eligible deaths ages 18–39 years. Furthermore, the data demonstrate no association between enrollment in state-sponsored donor registries and authorization rates. Lastly, by definition, there will always be 50% of OPOs below the median, thus there are always OPOs that can increase authorization rates. However, Figures 1A–C demonstrate that there was a clustering of OPOs with authorization rates substantially below the median, thus increasing authorization rates in those OPOs, to the median level, or even very close to it, would provide a large increase in organ donors. In conclusion, efforts to improve and standardize donor authorization rates have been implemented in the past with marked success. Our data demonstrate that DSA-level donor authorization rates among reported eligible deaths are variable across the 58 DSAs and significant opportunity exists to improve these. Optimizing organ acquisition at the OPO, hospital, and community level, more so than any other proposal, provides the best opportunity to bridge the organ supply–demand mismatch. Clearly, this would serve as complementary to any organ redistricting proposals. The goal will be to build more effective collaborations between OPOs, HRSA, OPTN, CMS, and society to achieve our highest priority—saving hundreds of more lives each year in US patients with end-stage organ disease.
Acknowledgments This study was supported by research grant funding from the National Institutes of Health (K08 DK098272 to Dr. Goldberg). This work was also supported in part by Health Resources and Services Administration contract 234-2005-37011C.
Disclaimer The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, the Centers for Medicare and Medicaid Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. Dr. Gilroy is a member of the UNOS Liver and Intestinal Organ Transplantation Committee. This work represents the view of Dr. Gilroy and his co-authors, and does not necessarily reflect the views of the UNOS Liver and Intestinal Organ Transplantation Committee.
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation. 2123
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References 1. Organ Procurement and Transplantation Network Strategic Plan. No date [cited 2014 Nov 24]. Available from: http://optn.transplant. hrsa.gov/ContentDocuments/OPTN_Strategic_Plan.pdf. 2. Allen AM, Kim WR, Xiong H, et al. Survival of recipients of livers from donation after circulatory death who are relisted and undergo retransplant for graft failure. Am J Transplant 2014; 14: 1120– 1128. 3. Kim HJ, Larson JJ, Lim YS, et al. Impact of MELD on waitlist outcome of retransplant candidates. Am J Transplant 2010; 10: 2652–2657. 4. Reich DJ, Hong JC. Current status of donation after cardiac death liver transplantation. Curr Opin Organ Transplant 2010; 15: 316– 321. 5. Renz JF, Kin C, Kinkhabwala M, et al. Utilization of extended donor criteria liver allografts maximizes donor use and patient access to liver transplantation. Ann Surg 2005; 242: 556–563; discussion 563–555. 6. Selck FW, Grossman EB, Ratner LE, Renz JF, Utilization. Outcomes, and retransplantation of liver allografts from donation after cardiac death: Implications for further expansion of the deceased-donor pool. Ann Surg 2008; 248: 599–607. 7. Delmonico FL, Sheehy E, Marks WH, Baliga P, McGowan JJ, Magee JC. Organ donation and utilization in the United States, 2004. Am J Transplant 2005; 5: 862–873. 8. Halpern SD, Barnes B, Hasz RD, Abt PL. Estimated supply of organ donors after circulatory determination of death: A populationbased cohort study. JAMA 2010; 304: 2592–2594. 9. Stogis S, Hirth RA, Strawderman RL, Banaszak-Holl J, Smith DG. Using a standardized donor ratio to assess the performance of organ procurement organizations. Health Serv Res 2002; 37: 1329–1344. 10. Shafer TJ, Wagner D, Chessare J, et al. US organ donation breakthrough collaborative increases organ donation. Crit Care Nurs Q 2008; 31: 190–210. 11. Shafer TJ, Wagner D, Chessare J, Zampiello FA, McBride V, Perdue J. Organ donation breakthrough collaborative: Increasing organ donation through system redesign. Crit Care Nurs 2006; 26: 33–42, 44-38; quiz 49. 12. Ojo AO, Pietroski RE, O’Connor K, McGowan JJ, Dickinson DM. Quantifying organ donation rates by donation service area. Am J Transplant 2005; 5: 958–966. 13. Ozcan YA, Begun JW, McKinney MM. Benchmarking organ procurement organizations: A national study. Health Serv Res 1999; 34: 855–874; discussion 875–858. 14. OPTN/UNOS Liver and Intestinal Organ Transplantation Committee: Redesigning Liver Distribution to Reduce Variation in Access to Liver Transplantation. 2014. 15. Eberlein M, Garrity ER, Orens JB. Lung allocation in the United States. Clinics in Chest Medicine 2011; 32: 213–222. 16. Colvin-Adams M, Valapour M, Hertz M, et al. Lung and heart allocation in the United States. Am J Transplant 2012; 12: 3213– 3234. 17. Stein R. Who gets first dibs on transplanted liver? Rules May Change 2014. 18. Goldberg DS, Halpern SD, Reese PP. Deceased organ donation consent rates among racial and ethnic minorities and older potential donors. Crit Care Med 2013; 41: 496–505. 19. Committee OULaIOT. Redesigning Liver Distribution to Reduce Variation in Access to Liver Transplantation. No date [cited 2012 July 3]. Available from: http://www.cms.gov/quarterlyproviderupdates/downloads/cms3064f.pdf.
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20. Klein AS, Messersmith EE, Ratner LE, Kochik R, Baliga PK, Ojo AO. Organ donation and utilization in the United States, 1999-2008. Am J Transplant 2010; 10: 973–986. 21. Sheehy E, Conrad SL, Brigham LE, et al. Estimating the number of potential organ donors in the United States. New Engl J Med 2003; 349: 667–674. 22. Network OPaT. Data submission requirements. Available from: No date [cited 2014 Jun 19]. Available from: http://optn.transplant. hrsa.gov/PoliciesandBylaws2/policies/pdfs/policy_23.pdf. 23. Nathan HM, Jarrell BE, Broznik B, et al. Estimation and characterization of the potential renal organ donor pool in Pennsylvania. Report of the Pennsylvania Statewide Donor Study. Transplantation 1991; 51: 142–149. 24. Bell CM, Redelmeier DA. Mortality among patients admitted to hospitals on weekends as compared with weekdays. N Engl J Med 2001; 345: 663–668. 25. Carr BG, Branas CC, Metlay JP, Sullivan AF, Camargo CA, Jr. Access to emergency care in the United States. Ann Emerg Med 2009; 54: 261–269. 26. Carr BG, Branas CC. Time, distance, and access to emergency care in the United States. LDI Issue Brief 2009; 14: 1–4. 27. Donate Life America. 2011 National Donor Registration Report Card. June 2011. 28. Normand S-LTaDMS Statistical and clinical aspects of hospital outcomes. Stat Sci 2007; 22: 206–226. 29. Scientific Registry of Transplant Recipients: OPTN/SRTR 2011 Annual Data Report. No date [cited 2014 Oct 9]. Available from: http://srtr.transplant.hrsa.gov/annual_reports/2011/pdf/ 07_dod_12.pdf. 30. Shafer T, Wood RP, Van Buren CT, et al. A success story in minority donation: The LifeGift/Ben Taub General Hospital In-House Coordinator Program. Transplant Proc 1997; 29: 3753–3755. 31. Axelrod DA, Dzebisashvili N, Lentine K, et al. Assessing variation in the costs of care among patients awaiting liver transplantation. Am J Transplant 2014; 14: 70–78. 32. Laupacis A, Keown P, Pus N, et al. A study of the quality of life and cost-utility of renal transplantation. Kidney Int 1996; 50: 235–242. 33. United Network for Organ Sharing: Public forum addresses equity in liver distribution. Accessed September 17, 2014. 34. Egan TM, Murray S, Bustami RT, et al. Development of the new lung allocation system in the United States. Am J Transplant 2006; 6: 1212–1227. 35. Arnaoutakis GJ, Allen JG, Merlo CA, et al. Impact of the lung allocation score on resource utilization after lung transplantation in the United States. J Heart Lung Transplant 2011; 30: 14–21. 36. Gandolfini I, Buzio C, Zanelli P, et al. The Kidney Donor Profile Index (KDPI) of marginal donors allocated by standardized pretransplant donor biopsy assessment: Distribution and association with graft outcomes. Am J Transplant 2014; 14: 2515–2525. 37. Eberlein M, Garrity ER, Orens JB. Lung allocation in the United States. Clin Chest Med 2011; 32: 213–222. 38. Colvin-Adams M, Valapour M, Hertz M, et al. Lung and heart allocation in the United States. Am J Transplant 2012; 12: 3213–3234. 39. OPTN: A Guide to Calculating and Interpreting the Kidney Donor Profile Index (KDPI). No date [cited 2014 Nov 20]. Available from: http://optn.transplant.hrsa.gov/ContentDocuments/Guide_to_Calculating_Interpreting_KDPI.pdf. 40. Committee OULaIOT. Redesigning Liver Distribution to Reduce Variation in Access to Liver Transplantation. No date [cited 2014 July 3]. Available from: http://optn.transplant.hrsa.gov/ContentDocuments/Liver_Concepts_2014.pdf. 41. Goldberg DS, French B, Forde KA, et al. Association of distance from a transplant center with access to waitlist placement, receipt
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50. Rodrigue JR, Cornell DL, Howard RJ. Relationship of exposure to organ donation information to attitudes, beliefs, and donation decisions of next of kin. Prog Transplant 2009; 19: 173–179.
Supporting Information Additional Supporting Information may be found in the online version of this article. Table S1: Baseline demographics of all eligible deaths reported to the OPTN from 1/1/08–11/1/13, n¼52 571.
Table S2: Adjusted odds ratios for authorization for donation among eligible deaths, n¼52 571*.
Table S3: Simulated increased in eligible deaths authorizing for donation if OPOs with low authorization rates had increased donor authorization rates, 2008–2013.
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Copyright 2015 The American Society of Transplantation and the American Society of Transplant Surgeons doi: 10.1111/ajt.13362
Increasing the Number of Organ Transplants in the United States by Optimizing Donor Authorization Rates D. S. Goldberg1,2,3,*, B. French2,3, P. L. Abt4 and R. K. Gilroy5 1
Division of Gastroenterology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 2 Center for Clinical Epidemiology and Biostatistics, Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 3 Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA 4 Division of Transplantation, Department of Surgery, Hospital of the University of Pennsylvania, Philadelphia, PA 5 Center for Transplantation and Department of Medicine, University of Kansas Medical Center, Kansas City, KS Corresponding author: David Goldberg, [email protected]
While recent policies have focused on allocating organs to patients most in need and lessening geographic disparities, the only mechanism to increase the actual number of transplants is to maximize the potential organ supply. We conducted a retrospective cohort study using OPTN data on all ‘‘eligible deaths’’ from 1/1/08 to 11/1/13 to evaluate variability in donor service area (DSA)-level donor authorization rates, and to quantify the potential gains associated with increasing authorization rates. Despite adjustments for donor demographics (age, race/ethnicity, cause of death) and geographic factors (rural/urban status of donor hospital, statewide participation in deceased-donor registries) among 52 571 eligible deaths, there was significant variability (p < 0.001) in donor authorization rates across the 58 DSAs. Overall DSA-level adjusted authorization rates ranged from 63.5% to 89.5% (median: 72.7%). An additional 773–1623 eligible deaths could have been authorized, yielding 2679–5710 total organs, if the DSAs with authorization rates below the median and 75th percentile, respectively, implemented interventions to perform at the level of the corresponding reference DSA. Opportunities exist within the current organ acquisition framework to markedly improve DSA-level donor authorization rates. Such initiatives would mitigate waitlist mortality while increasing the number of transplants.
Abbreviations: DCD, donation after cardiac death; DSA, donor service area; HRSA, Health Resources and Services Administration; KDPI, kidney donor profile index; LAS, lung allocation score; MELD, Model for End-Stage Liver Disease; OPOs, organ procurement organizations; OPTN, Organ Procurement and Transplantation Network; RUCA, rural urban commuting area; UNOS, United Network for Organ Sharing Received 11 December 2014, revised 23 February 2015 and accepted for publication 26 February 2015
Introduction The Organ Procurement and Transplantation Network’s (OPTN) Strategic Plan includes six key goals for improving the national organ transplant system in the United States. The top priority, as stated by the OPTN Board of Directors, is to increase the number of transplants among patients with end-stage organ disease (1). Despite this priority, substantial effort has been devoted to proposals that focus on altering the distribution of the current organ supply, and/ or modifying waitlist prioritization. Policies that focus on waitlist priority would not, however, increase the overall number of transplants because such policies simply redistribute the existing supply. The mechanisms with the greatest potential to increase the number of transplants include: greater use of medically compromised organs (e.g. donation after cardiac death [DCD] donors); reducing organ discards; increasing living donation; and maximizing the use of potential donors through increased authorization rates. Increased use of extended criteria donors may compromise the survival of transplant recipients (2–6). DCD and living donation are restricted almost uniformly to kidney and liver transplants (7) (with a small number of lung transplants), and would be insufficient to substantially increase the organ supply (8). In contrast to each of these, optimizing the collective performance of organ procurement organizations (OPOs), critical care physicians, donor hospitals, transplant centers, and the general public to increase donor service area (DSA)-level donor authorization rates may provide the best opportunity to help the OPTN achieve its goal. 2117
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The responsibility for coordinating all aspects of organ procurement—from communication with donor families, working with the local donor hospital and transplant center, to providing education to promote organ donation—is the domain of the local OPO (9). Although the OPO may subsume the administrative accountability for organ procurement, responsibility for the process of identifying and sustaining potential organ donors is shared much more broadly including the donor hospitals, physicians caring for potential donors, and the donor families and their communities. OPOs, working in collaboration with the transplant community to share best practices have previously demonstrated a substantial increase in the number of US organ donors (10,11). While data suggest there is substantial geographic variability in authorization rates of ‘‘eligible deaths’’ (hospitalized brain dead patients 70 years of age without any exclusionary medical conditions) (7,9,12,13) at the DSA level, the potential etiology of such variability is unknown. It has been posited that this inter-DSA variability is due to geographic distribution of racial/ethnic minorities, who are known to have lower authorization rates (14–19). Yet there are no empiric data that support this hypothesis, or to quantify the potential gains associated with optimizing DSA-level donor authorization rates. The 2003 Health Resources and Services Administration (HRSA)-sponsored collaborative effort was successful in improving OPO performance and increasing organ donation. Similar renewed efforts could potentially help to increase the number of donors, save more lives than the current system, and potentially mitigate some of the geographic disparities when implemented in concert with broader organ sharing by increasing the overall organ pool for the transplant community. In order to quantify the potential opportunities for increasing deceased organ donation through evaluation, we sought to test two hypotheses: (1) variability in DSA-level donor authorization rates is not explained simply by different racial/ethnic demographic characteristics, age, or cause of death of the potential donor population within each DSA; and (2) the potential to increase donation activity associated with optimizing donor authorization rates equals or exceeds gains from proposals focused solely on redistributing the current organ supply. These data can be used to initiate a broader dialogue within the transplant community on how to define the potential donor pool and ways in which authorization of potential donors can be improved.
Methods Study design and data source All analyses used an OPTN/United Network for Organ Sharing (UNOS) dataset on all eligible deaths from 1/1/08 to 11/1/13. As part of the Hospital Conditions of Participation in the Medicare program, the Health Care Financing Administration mandates that participating hospitals contact their OPO about individuals whose death is imminent or who die in the hospital (20). Hospitals within certain DSAs may report a larger number of imminently brain-dead patients due to requests by their local OPO (e.g.
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some OPOs request referrals for older potential donors, including those >75 years of age). Yet, despite these differences, the definition of an eligible death is a standardized, uniformly applied OPTN definition—a patient 70 years of age: (1) declared brain-dead according to hospital policy and (2) who lacked exclusionary medical conditions to organ donation. All patient-level data must be submitted by the OPOs to the OPTN (7,12,21–24), with the definition of an eligible death uniform across all OPOs. While eligible deaths represent a fraction of in-hospital deaths (25), >95% of all deceased liver donors derive from this eligible-death patient pool (8,23,25).
Study outcomes The primary outcome was whether authorization for organ donation was obtained, defined as from next-of-kin (Consent-Yes) or through a registry or a legal document (Registry-Yes).
Statistical analysis A mixed-effects logistic regression model for the patient-level outcome of authorization was used to quantify and test for variability in DSA-level authorization rates. The model adjusted for observed characteristics associated with variation in authorization rates: age; sex; race/ethnicity, as defined by UNOS (18) (white, black, Hispanic, Asian, multi-racial, or other); cause of death (stroke, head trauma, anoxia, brain tumor, other) (18); ‘‘timely’’ versus not ‘‘timely’’ referral of the eligible death, defined by the OPO; weekend versus weekday status of eligible death referral (26); rural versus urban status of the donor hospital, defined using the modified rural urban commuting area (RUCA) measure based on the zip code of the hospital (27,28); number of transplant centers in a DSA; and the percentage of a state’s population enrolled as an organ donor through a state-sponsored registry (29). An interaction term between age and race/ethnicity was used given the potential for differences in authorization rates based on age within racial/ethnic groups (i.e. differences in cultural beliefs towards donation among different generations). The model included DSA-level random intercepts to quantify unobserved variability in the odds of authorization across OPOs after adjustment for observed covariates, as well as to account for the correlation due to clustering of patients within DSAs. We conducted a hypothesis test of no unobserved heterogeneity across DSAs after adjusting for patient-level factors based on the variance of the DSA-level random intercepts, with the null-hypothesized value of 0 indicating no unobserved heterogeneity (i.e. p < 0.05 indicated statistically significant differences in DSA authorization rates after adjustment for the observed characteristics listed above). We calculated DSA-specific authorization rates, adjusted for patient-level covariates, using postestimation summaries obtained from the mixedeffects logistic regression model described above. We computed an adjusted rate of authorization by standardizing the observed rate to the expected rate based on the mixed-effects logistic regression model (30). If the adjusted rates of authorization differed among DSAs, such variation indicated that DSA-level differences were due to DSA-level factors/OPO performance or unobserved factors. Because of the potential for unmeasured differences of the racial/ethnic categories in UNOS that could potentially contribute to DSA variability, we performed a subgroup analysis among eligible deaths who were white and ages 18–39 years (the racial/ ethnic and age categories previously shown to have the highest authorization rates). These analyses allowed for verification that DSA variability was not explained solely due to differences in the age and racial/ethnic characteristics of eligible deaths in an DSA (18). To simulate the potential increase in the number of organ donors if interventions were enacted to increase donor authorization rates among DSAs with lower rates, we calculated the difference between a DSA’s adjusted authorization rate and that of (1) the median performing DSA and
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Increasing the Number of Organ Transplants (2) the OPO in the 75th percentile. The difference between the DSA’s adjusted authorization rate and that of the reference DSA was used to calculate the potential number of increased authorized donors within a DSA. The organ yield per donor was then calculated based on the organ yield per donor from each of the 58 DSAs in 2011, the midpoint of the study period (31).
rate between 70.0% and 75.0% (Figure 1A). Additionally, within individual UNOS regions, there was broad variability in adjusted authorization rates (Figure 1B). The differences in adjusted authorization rates (accounting for factors
All analyses were performed using Stata 13.0 (College Station, TX). This study was approved by the Institutional Review Board at the University of Pennsylvania.
Results From January 1, 2008 through November 1, 2013, there were 52 571 reported eligible deaths, from which authorization for donation was obtained in 38 432 (73.1%) cases. Of the 38 432 authorized donors, 30 870 (80.3%) were obtained from family or next-of-kin (with or without prior registration in a donor registry), while 7562 (19.7%) were based on registration in a donor registry. The median age of eligible deaths was 43 (IQR: 25-54), with 30 700 (58.4%) males (Table S1). Potential donor age, racial/ethnic category, cause of death, timeliness of the eligible death referral, weekday referral, and RUCA classification of the donor hospital were all significantly associated with authorization rates (Table S2). Although there was a significant interaction between donor age and race/ethnicity, there was only a moderate inverse relationship between the DSA-level proportion of eligible deaths that were a racial/ethnic minority and authorization rates in the DSA (r ¼ 0.57). There was no association between the proportion of patients in a state registered as an organ donor through a state-sponsored registry (p ¼ 0.80) or the number of transplant centers within a DSA (p ¼ 0.92) and authorization rates in multivariable models. There was a strong positive correlation (r ¼ 0.83) between a DSA’s overall unadjusted authorization rate and its authorization rate of ideal donors ages 18–39 years. Unadjusted and adjusted DSA-specific rates of authorization for donation The unadjusted authorization rates varied considerably across the 58 DSAs: 85.8% in the highest-performing DSA versus 57.7% in the lowest-performing DSA. Despite adjusting for patient and geographic factors independently associated with authorization (Table S1), there still were significant differences in authorization rates across the 58 DSAs (p < 0.001). This unobserved variability in authorization rates across DSAs was likely due to unmeasured factors, inherent baseline differences in OPO performance and process-of-care measures (i.e. training of OPO staff, interactions and outreach with donor hospitals, or broader community-based education), or a combination of the two. The adjusted authorization rates of all eligible deaths across the 58 DSAs ranged from 63.5% to 89.5%, with nearly onehalf of DSAs (28/58) having an overall adjusted authorization American Journal of Transplantation 2015; 15: 2117–2125
Figure 1: Adjusted rates of authorization for organ donation within donor service areas in the United States from January 1, 2008 through November 1, 2013. (A) Density plot shows the distribution of adjusted authorization rates among all eligible deceased donors across all donor service areas; p < 0.001 indicated statistically significant variability in adjusted authorization rates across donor service areas. (B) Adjusted authorization rates according to geographic region; each point represents an organ procurement organization. (C) Density plot to shows the distribution of adjusted authorization rates across all donor service areas among eligible deceased donors who were white and between 18 and 39 years old.
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associated with authorization other than age and race/ ethnicity) across DSAs persisted in subgroup analyses restricted to all eligible deaths among whites, ages 18–39 years (n ¼ 9939), ranging from 71.5% to 91.8% (Figure 1C), with significant heterogeneity in adjusted authorization rates across the DSAs (p < 0.001). There was no association between the number of organ donors (overall or ideal) and authorization rates (data not shown).
authorized eligible deaths/year) could potentially have authorized for donation during the study period. Nearly one-third of the increased donors were located in Region 9 (Figure 2A, Table S3). If DSAs performing below the 75th percentile enacted measures to increase donor authorization to the 75th percentile-performing DSA, the potential increased yield of authorized donors during the study period would have been 1623 (average of 278 increased authorized eligible deaths/year; Figure 2B, Table S3).
Potential increase in authorized donors The median adjusted authorization rate among the 58 DSAs was 72.7% (Figure 1A). If the 28 DSAs performing below the national median implemented interventions to increase their authorization rates to the median, then a total of 773 increased eligible deaths (average of 132 increased
Increased donor authorization rates could potentially yield an additional 2679 organs over the study period if DSAs currently performing below the median level could achieve such targets, and 5710 additional organs if all DSAs performed at the level of the current 75th percentile (Table 1).
Figure 2: (A) Simulated increased in eligible deaths consenting (authorizing) for donation if ‘‘low-performing’’ DSAs had authorization rates at the level of the median DSA in the US from 2008 to 2013, n ¼ 773 nationally. Increase in authorized donors is based on simulated outcomes if the 43 DSAs with adjusted authorization rates below the adjusted national 75th percentile for all DSAs from 1/1/08 to 11/1/13 had instituted interventions to improve their adjusted authorization rates to that of the 75th percentileperforming DSA. Numbers represent UNOS region. (B) Simulated increased in eligible deaths consenting (authorizing) for donation if ‘‘low-performing’’ DSAs had authorization rates at the level of the 75th percentile DSA in the US from 2008–2013, n ¼ 1623 nationally. Increase in authorized donors is based on simulated outcomes if the 43 DSAs with adjusted authorization rates below the adjusted national 75th percentile for all DSAs from 1/1/08–11/1/13 had instituted interventions to improve their adjusted authorization rates to that of the 75th percentile–performing DSA. Numbers represent UNOS region.
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Increasing the Number of Organ Transplants Table 1: Potential increase in transplantable organs with increased donor authorization rates, 2008–20131 Organ
DSAs with authorization below the median1
DSAs with authorization below the 75th percentile2
1385 660 257 231 134 13 2679
2931 1366 600 488 293 29 57103
healthcare costs would be delivered to the system by shortening both the time and number of patients waiting across all organ categories (33,34).
Conclusions
Despite the OPTNs stated priority to increase the number of organ transplants, recent efforts, and media attention have, however, focused on redistributing the current organ supply, and altering the prioritization scheme for waitlisted patients (19,35–40). Such recently approved policy proposals or considerations include: the new kidney donor profile index (KDPI) (38) for prioritization of patients on the kidney transplant waitlist (41); initiation and subsequent modifications to the lung allocation score (LAS), which prioritizes patients for lung transplants (36,37,39,40); and altering the distribution of transplantable livers by redrawing distribution maps (14,19). These policy revisions focus solely on how to utilize the current supply of transplantable organs, without directly increasing the authorization rate of potential donors, thus increasing the absolute number of transplants. Yet measures to increase the organ supply through improvements in DSA-level authorization rates, in conjunction with other policy revisions, may serve to improve the current system of organ transplantation while also helping to mitigate geographic disparities.
This analysis of the national cohort of identified potential brain-dead organ donors from 2008 to 2013 illustrates marked variability in authorization rates, leading to a substantial number of unrealized organ transplants. This variation in DSA authorization rates was not fully explained by differences in the demographic characteristics of the potential donor pool within a geographic area. This is underscored by the significant variability in donor authorization rates when adjusting for such demographic characteristics, and the persistent differences in performance when restricted to the highest authorizing cohort of white patients ages 18–39 years. The root causes of these differences in authorization rates cannot be solely attributed to the local OPO. Although the OPO has administrative responsibility for authorization and organ donation, these are complex processes that ultimately reflect the broader support of the community, including the donor families, the donor hospitals, and the staff of these hospitals. Improving donor authorization rates would require not only OPObased initiatives, but those that target the wider community, which the OPO serves. Reapplying interventions similar to those used in the highly successful Organ Donor Breakthrough Collaborative (32) would likely assist the OPTN and the organ donation and transplantation community to achieve the OPTNs most important goal listed for 2014–2015. Increasing donor authorization rates also has the greatest potential to minimize geographic disparities in access to organ transplantation by providing a greater pool of donor organs to be applied to any measure seeking to address geographic disparities. When considered on a national scale, donation provides a substantial economic benefit by increasing the total number of transplants across all solid organ categories. By this, a greater reduction to
As an example, the recent OPTN/UNOS proposal for liver redistribution seeks to redraw distribution maps in order to normalize Model for End-Stage Liver Disease (MELD) scores, an index of disease severity, across the country by more broadly sharing livers. Such redistricting would change the available donor pool in certain geographic regions in order to minimize waitlist mortality in other areas. Simulations suggest a decrease of 332 to 554 waitlist deaths over 5 years (14,19). However, this policy, while important with regards to helping to minimize geographic disparities, would have little influence on the overall national mismatch between organ supply and demand (42). Furthermore, the impact of this policy on waitlist mortality in areas that will see a great reduction in their volume of liver transplants, in particular those centers serving patients dispersed over a large geographic area at greatest risk of waitlist mortality (43), is unknown. The data in this manuscript also show that certain regions that stand to benefit the greatest from redistribution would also achieve the greatest increase in transplant numbers from optimization of DSA-level donor authorization (e.g. Region 9). Although other regions might have much smaller increases based on our analyses (e.g. Region 1), all regions ultimately would benefit from optimized OPO performance. Efforts to maximize DSA-level donor authorization rates are complementary to broader organ sharing, and could potentially be instituted in concert with redistribution proposals. Under redistribution, ‘‘high-MELD’’ regions (e.g. Regions 1 and 5), which only would have a small increase in donors with improved authorization rates, would benefit from improved authorization in ‘‘low-MELD’’ regions (e.g. Region 3). However, broader sharing alone would not allow the OPTN to meet its stated goal. Importantly, whether and
Kidney Liver Lung Heart Pancreas Intestine Total
1 The estimated organ yield is based on Scientific Registry of Transplant Recipients (SRTR) data from 2011, and represents the current organ yield per donor for each of the 58 DSAs (26). 2 Low-performing DSAs defined as the 28 DSAs whose adjusted rates of authorization for donation of all eligible deaths from 1/1/08 to 11/1/13 were below the adjusted national median for all DSAs of 72.7%. 3 Low-performing DSAs defined as the 43 DSAs whose adjusted rates of authorization for donation of all eligible deaths from 1/1/08 to 11/1/13 were below the adjusted national 75th percentile for all DSAs of 75.4%.
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how broader sharing might impact the relationships between OPOs, donor hospitals, transplant centers and the donor communities is not understood. Our work is the first to use national data on reported potential brain-dead organ donors to examine variability in DSA-level donor authorization rates and to look to quantify what gains in donation rates might exist. Importantly, the current analysis did not demonstrate that differences in demographic characteristics (i.e. age, race/ethnicity) and geographic factors (i.e. rural/urban status) explain most of the geographic variability in donor authorization rates as we had expected it might. Thus, opportunities for increasing donation exist. Previous studies have attempted to quantify geographic differences in the absolute number of potential brain-dead organ donors, yet these studies relied on death certificate data to define the ‘‘underlying organ donor potential (23,44).’’ Unfortunately, death certificates do not classify a patient as brain-dead and cannot determine a patient’s eligibility as a potential organ donor (45). Despite these limitations, there are geographic differences in causes of death in the population, such as those seen between the Northeast and Southern regions of the United States. As a consequence, the likelihood of an eligible donor amongst hospital deaths will vary geographically (44). These data should not be used in isolation as a metric to predict OPO performance in organ acquisition for deceased donor transplantation. Eligible deaths do not include potential DCD, brain-dead patients >70 years of age, or potential donors who are imminently brain-dead, but the opportunity for organ donation is declined by next-of-kin. These too are potential donors that serve to increase the number of transplants. The definition of an eligible death as set forth by the OPTN is an imperfect measure of potential donors. Given hospital differences in brain death criteria (i.e. clinical criteria alone vs. clinical þ imaging), patients being >70 years of age excluded from reporting when they may in fact be eligible donors, and non–brain-dead donors not being considered within this definition, we agree a more optimal metric needs to be created. Utilization of eligible death data allows for an estimate of the minimal potential opportunity for increases in the number of organ donors. However, to use this metric to compare regional OPO performances and to classify an OPO as ‘‘good’’ or ‘‘bad’’ should not occur as factors beyond the OPOs control also impact eligible donor conversion. In order to accurately capture all potential donors, greater partnership with donor hospitals is needed if we seek to capitalize on all donation opportunities. Further refinement of brain-death declaration and tracking of hospital reporting will also enhance our donation potential as a transplant community. This is underscored by the differences in the number of eligible deaths based on OPTN/UNOS data, versus direct chart review (23). Also, it must be noted that the responsibility to successfully ‘‘convert’’ an eligible death falls not only to the OPO, but to all clinical entities caring for these patients, as well as a greater understanding within the community of 2122
the value of donation. Nevertheless, eligible deaths represent greater than 85–95% of the national pool of deceased donor transplants, depending on the organ type, and thus these data help to quantify the potential gains in organ donation with increased authorization rates. Additionally, Centers for Medicare and Medicaid Services (CMS) evaluations of an OPO’s donation rate is based on the number of eligible deaths (46). Nevertheless, a broader dialogue in the transplant community is needed in order to refine the eligible death definition, define additional objective metrics of OPO performance, and develop initiatives to improve the process of donor authorization. The current analysis demonstrates the potential for increasing the donor pool by optimizing DSA-level donor authorization rates. Variability in DSA-level donor authorization rates may be attributable to any and/or all aspects of the donation process, which includes factors independent of the OPO: relationships between donor hospitals and OPOs, relationships between OPOs and transplant centers, early involvement of OPOs prior to declaration of brain death, education initiatives for the public and for donor hospitals, differences in training of OPO staff, use of ethnicity-matched requestors for donation (32), differing OPO management structures, staffing models of individual OPOs (i.e. OPOs that accept organ referrals 24/7 vs. others that have limited staffing overnight), and/or public opinion of organ donation. Further efforts to identify and target barriers to donation have the potential to increase opportunities for transplantation (47–53). Targeted increases in tracking of DSA-level donor authorization rates by regulatory authorities may also be advisable. These initiatives alone may not allow for maximization of the potential organ supply. The CMS should consider policies at both the hospital and OPO level. These could include: increased financial penalties for hospitals that fail to refer eligible deaths in a timely manner; financial rewards for hospitals that refer the highest proportion of eligible deaths in a timely manner; decreased payments to OPOs that consistently have the lowest authorization rates beyond some prespecific rate; or increased payments to those that consistently perform at some prespecific target rate. In order to optimize and standardize DSA-level donor authorization rates, qualitative research is needed to identify the characteristics of the highest performing OPOs in contrast to those with authorization rates below the median. Mixed-methods qualitative research could utilize surveys of all OPO leaders to garner broad data on process-of-care measures of all OPOs, while also organizing focus groups restricted to executives of the highest- and lowest-performing OPOs. However, some potential initiatives, in part based on interventions proven to be successful based on the first HRSA-sponsored Organ Donor Breakthrough Collaborative (32), include: (1) increased OPO oversight of hospitals to ensure all potential organ donors are referred to the OPO in a timely manner; (2) uniform best-practices of OPO requestors, based on metrics of OPOs with the highest authorization rates; (3) dispatching American Journal of Transplantation 2015; 15: 2117–2125
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the most effective requestor from an OPO to obtain authorization for donation; (4) ensuring that all OPOs provide 24/7 coverage for organ referrals; (5) employing uniform team huddles and debriefings across al OPOS; (6) increasing funding for national educational initiatives to increase organ donor awareness and/or and support for organ donation, targeting states that have traditionally been underserved with education; (7) required use of ethnicity-matched requestors when appropriate; (8) financial rewards or disincentives to hospitals that do not refer eligible deaths in a timely manner; and (9) utilizing secure electronic health records to streamline the referral process of eligible deaths. This study has limitations. First, OPOs receive a large number of referrals regarding in-hospital deaths that do not qualify as eligible deaths (25). While the majority of these referrals have medical contraindications to donation, a subset have neurologic injury not yet meeting brain death criteria (25). Eligible death data are still more reliable than death certificate data due to potential misclassification of causes of death, and inability to ascertain brain death from a death certificate. Second, there is the potential for underreporting of eligible deaths. If such under-reporting exists, it would be expected to falsely lower the number of eligible deaths. There are no objective data to demonstrate that under-reporting of eligible deaths is occurring, or that there is geographic variability in reporting practices. Because OPOs are subject to audits and work in collaboration with other OPOs, we believe these data are accurate. Furthermore, OPOs with the lowest authorization rates are also those with the fewest donors-per-million population, which suggests an absence of under-reporting of eligible deaths. We believe OPOs should continue to be responsible for reporting eligible deaths to the OPTN, yet greater oversight of the system, akin to the audits of transplant centers, may offer opportunities to further improve the system of organ donation. Continuous reviews of the process by which eligible donors are identified and outcomes are tracked are just two examples of these potential opportunities. Third, the decision underlying the denial of authorization was not captured. While this is important for future efforts to design interventions to improve authorization rates, the lack of such data does not discount the results of marked OPO variability. Fourth, we could not precisely calculate the hypothetical yield of potential organs through increased authorization rates due to lack of available medical data on nonauthorized donors. Yet a yield of increased organs at 50% of the estimated hypothetical yield would still result in 1300–2850 transplantable organs over a nearly 6-year period. Fifth, the OPTN/UNOS data is insufficient to account for variables that may contribute to donor authorization rates among racial/ethnic minorities, including country of origin or years of residence in the United States. Among racial/ethnic minorities (i.e. immigrants from Asian countries), viewpoints on organ donation versus receiving an organ may differ among first-generation immigrants versus second- and third-generation. These facts would not explain our results though, because although there may be some variation in American Journal of Transplantation 2015; 15: 2117–2125
authorization rates due to fixed preferences about donation among certain racial/ethnic minorities, this cannot explain the marked variability in the subgroup of white eligible deaths ages 18–39 years. Furthermore, the data demonstrate no association between enrollment in state-sponsored donor registries and authorization rates. Lastly, by definition, there will always be 50% of OPOs below the median, thus there are always OPOs that can increase authorization rates. However, Figures 1A–C demonstrate that there was a clustering of OPOs with authorization rates substantially below the median, thus increasing authorization rates in those OPOs, to the median level, or even very close to it, would provide a large increase in organ donors. In conclusion, efforts to improve and standardize donor authorization rates have been implemented in the past with marked success. Our data demonstrate that DSA-level donor authorization rates among reported eligible deaths are variable across the 58 DSAs and significant opportunity exists to improve these. Optimizing organ acquisition at the OPO, hospital, and community level, more so than any other proposal, provides the best opportunity to bridge the organ supply–demand mismatch. Clearly, this would serve as complementary to any organ redistricting proposals. The goal will be to build more effective collaborations between OPOs, HRSA, OPTN, CMS, and society to achieve our highest priority—saving hundreds of more lives each year in US patients with end-stage organ disease.
Acknowledgments This study was supported by research grant funding from the National Institutes of Health (K08 DK098272 to Dr. Goldberg). This work was also supported in part by Health Resources and Services Administration contract 234-2005-37011C.
Disclaimer The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, the Centers for Medicare and Medicaid Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government. Dr. Gilroy is a member of the UNOS Liver and Intestinal Organ Transplantation Committee. This work represents the view of Dr. Gilroy and his co-authors, and does not necessarily reflect the views of the UNOS Liver and Intestinal Organ Transplantation Committee.
Disclosure The authors of this manuscript have no conflicts of interest to disclose as described by the American Journal of Transplantation. 2123
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Supporting Information Additional Supporting Information may be found in the online version of this article. Table S1: Baseline demographics of all eligible deaths reported to the OPTN from 1/1/08–11/1/13, n¼52 571.
Table S2: Adjusted odds ratios for authorization for donation among eligible deaths, n¼52 571*.
Table S3: Simulated increased in eligible deaths authorizing for donation if OPOs with low authorization rates had increased donor authorization rates, 2008–2013.
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