The National Landscape of Living Kidney Donor Follow-Up in the United States.

In 2013, the Organ Procurement and Transplantation Network (OPTN)/ United Network for Organ Sharing (UNOS) mandated that transplant centers collect data on living kidney donors (LKDs) at 6 months, 1 year, and 2 years postdonation, with policy-defined thresholds for the proportion of complete living donor follow-up (LDF) data submitted in a timely manner (60 days before or after the expected visit date). While mandated, it was unclear how centers across the country would perform in meeting thresholds, given potential donor and center-level challenges of LDF. To better understand the impact of this policy, we studied Scientific Registry of Transplant Recipients data for 31,615 LKDs between January 2010 and June 2015, comparing proportions of complete and timely LDF form submissions before and after policy implementation. We also used multilevel logistic regression to assess donor- and center-level characteristics associated with complete and timely LDF submissions. Complete and timely 2-year LDF increased from 33% prepolicy (January 2010 through January 2013) to 54% postpolicy (February 2013 through June 2015) (p < 0.001). In an adjusted model, the odds of 2-year LDF increased by 22% per year prepolicy (p < 0.001) and 23% per year postpolicy (p < 0.001). Despite these annual increases in LDF, only 43% (87/202) of centers met the OPTN/UNOS-required 6-month, 1-year, and 2-year LDF thresholds for LKDs who donated in 2013. These findings motivate further evaluation of LDF barriers and the optimal approaches to capturing outcomes after living donation.

Waitlist Outcomes of Liver Transplant Candidates Who Were Reprioritized Under Share 35.

Under Share 35, deceased donor (DD) livers are offered regionally to candidates with Model for End-Stage Liver Disease (MELD) scores ≥35 before being offered locally to candidates with MELD scores <35. Using Scientific Registry of Transplant Recipients data from June 2013 to June 2015, we identified 1768 DD livers exported to regional candidates with MELD scores ≥35 who were transplanted at a median MELD score of 39 (interquartile range [IQR] 37-40) with 30-day posttransplant survival of 96%. In total, 1764 (99.8%) exports had an ABO-compatible candidate in the recovering organ procurement organization (OPO), representing 1219 unique reprioritized candidates who would have had priority over the regional candidate under pre-Share 35 allocation. Reprioritized candidates had a median waitlist MELD score of 31 (IQR 27-34) when the liver was exported. Overall, 291 (24%) reprioritized candidates had a comparable MELD score (within 3 points of the regional recipient), and 209 (72%) were eventually transplanted in 11 days (IQR 3-38 days) using a local (50%), regional (50%) or national (<1%) liver; 60 (21%) died, 13 (4.5%) remained on the waitlist and nine (3.1%) were removed for other reasons. Of those eventually transplanted, MELD score did not increase in 57%; it increased by 1-3 points in 37% and by ≥4 points in 5.7% after the export. In three cases, OPOs exchanged regional exports within a 24-h window. The majority of comparable reprioritized candidates were not disadvantaged; however, 21% died after an export.

Changes in Utilization and Discard of Hepatitis C-Infected Donor Livers in the Recent Era.

The impact of interferon (IFN)-free direct-acting antiviral (DAA) hepatitis C virus (HCV) treatments on utilization and outcomes associated with HCV-positive deceased donor liver transplantation (DDLT) is largely unknown. Using the Scientific Registry of Transplant Recipients, we identified 25 566 HCV-positive DDLT recipients from 2005 to 2015 and compared practices according to the introduction of DAA therapies using modified Poisson regression. The proportion of HCV-positive recipients who received HCV-positive livers increased from 6.9% in 2010 to 16.9% in 2015. HCV-positive recipients were 61% more likely to receive an HCV-positive liver after 2010 (early DAA/IFN era) (aRR:1.45 1.611.79 , p < 0.001) and almost three times more likely to receive one after 2013 (IFN-free DAA era) (aRR:2.58 2.853.16 , p < 0.001). Compared to HCV-negative livers, HCV-positive livers were 3 times more likely to be discarded from 2005 to 2010 (aRR:2.69 2.993.34 , p < 0.001), 2.2 times more likely after 2010 (aRR:1.80 2.162.58 , p < 0.001) and 1.7 times more likely after 2013 (aRR:1.37 1.682.04 , p < 0.001). Donor HCV status was not associated with increased risk of all-cause graft loss (p = 0.1), and this did not change over time (p = 0.8). Use of HCV-positive livers has increased dramatically, coinciding with the advent of DAAs. However, the discard rate remains nearly double that of HCV-negative livers. Further optimization of HCV-positive liver utilization is necessary to improve access for all candidates.

The Living Donor Collective: A Scientific Registry for Living Donors.

In the setting of an overall decline in living organ donation and new questions about long-term safety, a better understanding of outcomes after living donation has become imperative. Adequate information on outcomes important to donors may take many years to ascertain and may be evident only by comparing large numbers of donors with suitable controls. Previous studies have been unable to fully answer critical questions, primarily due to lack of appropriate controls, inadequate sample size, and/or follow-up duration that is too short to allow detection of important risks attributable to donation. The Organ Procurement and Transplantation Network does not follow donors long term and has no prospective control group with which to compare postdonation outcomes. There is a need to establish a national living donor registry and to prospectively follow donors over their lifetimes. In addition, there is a need to better understand the reasons many potential donors who volunteer to donate do not donate and whether the reasons are justified. Therefore, the US Health Resources and Services Administration asked the Scientific Registry of Transplant Recipients to establish a national registry to address these important questions. Here, we discuss the efforts, challenges, and opportunities inherent in establishing the Living Donor Collective.

Risk of End-Stage Renal Disease in HIV-Positive Potential Live Kidney Donors.

New federal regulations allow HIV-positive individuals to be live kidney donors; however, potential candidacy for donation is poorly understood given the increased risk of end-stage renal disease (ESRD) associated with HIV infection. To better understand this risk, we compared the incidence of ESRD among 41 968 HIV-positive participants of North America AIDS Cohort Collaboration on Research and Design followed for a median of 5 years with the incidence of ESRD among comparable HIV-negative participants of National Health and Nutrition Examination III followed for a median of 14 years. We used risk associations from multivariable Cox proportional hazards regression to derive cumulative incidence estimates for selected HIV-positive scenarios (no history of diabetes, hypertension, AIDS, or hepatitis C virus coinfection) and compared these estimates with those from similarly selected HIV-negative scenarios. For 40-year-old HIV-positive individuals with health characteristics that were similar to those of age-matched kidney donors, viral load <400 copies/mL, and CD4+ count ≥500 cells/µL, the 9-year cumulative incidence of ESRD was higher than that of their HIV-negative peers, yet still low: 2.5 versus 1.1 per 10 000 among white women, 3.0 versus 1.3 per 10 000 among white men, 13.2 versus 3.6 per 10 000 among black women, and 15.8 versus 4.4 per 10 000 among black men. HIV-positive individuals with no comorbidities and well-controlled disease may be considered low-risk kidney donor candidates.

Changes in Discard Rate After the Introduction of the Kidney Donor Profile Index (KDPI).

Since March 26, 2012, the Kidney Donor Profile Index (KDPI) has been provided with all deceased-donor kidney offers, with the goal of improving the expanded criteria donor (ECD) indicator. Although an improved risk index may facilitate identification and transplantation of marginal yet viable kidneys, a granular percentile system may reduce provider-patient communication flexibility, paradoxically leading to more discards ("labeling effect"). We studied the discard rates of the kidneys recovered for transplantation between March 26, 2010 and March 25, 2012 ("ECD era," N = 28 636) and March 26, 2012 and March 25, 2014 ("KDPI era," N = 29 021) using Scientific Registry of Transplant Recipients (SRTR) data. There was no significant change in discard rate from ECD era (18.1%) to KDPI era (18.3%) among the entire population (adjusted odds ratio [aOR] = 0.97 1.041.10 , p = 0.3), or in any KDPI stratum. However, among kidneys in which ECD and KDPI indicators were discordant, "high risk" standard criteria donor (SCD) kidneys (with KDPI > 85) were at increased risk of discard in the KDPI era (aOR = 1.07 1.421.89 , p = 0.02). Yet, recipients of these kidneys were at much lower risk of death (adjusted Risk Ratio [aRR] = 0.56 0.770.94 at 2 years posttransplant) compared to those remaining on dialysis waiting for low-KDPI kidneys. Our findings suggest that there might be an unexpected, harmful labeling effect of reporting a high KDPI for SCD kidneys, without the expected advantage of providing a more granular risk index.

Recipient Outcomes Following Transplantation of Allografts From Live Kidney Donors Who Subsequently Developed End-Stage Renal Disease.

Live kidney donors have an increased risk of end-stage renal disease (ESRD) compared with nondonors; however, it is unknown whether undetected, subclinical kidney disease exists at donation that subsequently contributes to this risk. To indirectly test this hypothesis, the authors followed the donated kidneys, by comparing the outcomes of 257 recipients whose donors subsequently developed ESRD with a matched cohort whose donors remained ESRD free. The compared recipients were matched on donor (age, sex, race/ethnicity, donor-recipient relationship), transplant (HLA mismatch, peak panel-reactive antibody, previous transplantation, year of transplantation), and recipient (age, sex, race/ethnicity, body mass index, cause of ESRD, and time on dialysis) risk factors. Median recipient follow-up was 12.5 years (interquartile range 7.4-17.9, maximum 20 years). Recipients of allografts from donors who developed ESRD had increased death-censored graft loss (74% versus 56% at 20 years; adjusted hazard ratio [aHR] 1.7; 95% confidence interval [CI] 1.5-2.0; p < 0.001) and mortality (61% versus 46% at 20 years; aHR 1.5; 95% CI 1.2-1.8; p < 0.001) compared with matched recipients of allografts from donors who did not develop ESRD. This association was similar among related, spousal, and unrelated nonspousal donors. These findings support a novel view of the mechanisms underlying donor ESRD: that of pre-donation kidney disease. However, biopsy data may be required to confirm this hypothesis.

A Smartphone App for Increasing Live Organ Donation.

The incidence of live donor transplantation has declined over the past decade, and waitlisted candidates report substantial barriers to identifying a live donor. Since asking someone to donate feels awkward and unfamiliar, candidates are hesitant to ask directly and may be more comfortable with a passive approach. In collaboration with Facebook leadership (Facebook Inc., Menlo Park, CA), we developed a mobile application-an app-that enables waitlisted candidates to create a Facebook post about their experience with organ failure and their need for a live donor. We conducted a single-center prospective cohort study of 54 adult kidney-only and liver-only waitlisted candidates using the Facebook app. Cox proportional hazards models were used to describe donor referral on behalf of candidates using the app compared with matched controls. The majority of candidates who used the app reported it to be "good" or "excellent" with regard to the installation process (82.9%), readability (88.6%), simplicity (70.6%), clarity (87.5%) and the information provided (85.3%). Compared with controls, candidates using the Facebook app were 2.43 6.6117.98 times more likely to have a donor come forward on their behalf (p < 0.001). The Facebook app is an easy-to-use instrument that enables waitlisted candidates to passively communicate with their social network about their need for a live donor.

Patterns of End-Stage Renal Disease Caused by Diabetes, Hypertension, and Glomerulonephritis in Live Kidney Donors.

Inferences about late risk of end-stage renal disease (ESRD) in live kidney donors have been extrapolated from studies averaging <10 years of follow-up. Because early (<10 years) and late (≥10 years) postdonation ESRD may differ by causal mechanism, it is possible that extrapolations are misleading. To better understand postdonation ESRD, we studied patterns of common etiologies including diabetes, hypertension and glomerulonephritis (GN; as reported by providers) using donor registry data linked to ESRD registry data. Overall, 125 427 donors were observed for a median of 11.0 years (interquartile range 5.3-15.7 years; maximum 25 years). The cumulative incidence of ESRD increased from 10 events per 10 000 at 10 years after donation to 85 events per 10 000 at 25 years after donation (late vs. early ESRD, adjusted for age, race and sex: incidence rate ratio [IRR] 1.3 1.72.3 [subscripts are 95% confidence intervals]). Early postdonation ESRD was predominantly reported as GN-ESRD; however, late postdonation ESRD was more frequently reported as diabetic ESRD and hypertensive ESRD (IRR 2.3 7.725.2 and 1.4 2.64.6 , respectively). These time-dependent patterns were not seen with GN-ESRD (IRR 0.4 0.71.2 ). Because ESRD in live kidney donors has traditionally been reported in studies averaging <10 years of follow-up, our findings suggest caution in extrapolating such results over much longer intervals.

Where the Sun Shines: Industry's Payments to Transplant Surgeons.

The Open Payments Program (OPP) was recently implemented to publicly disclose industry payments to physicians, with the goal of enabling patient awareness of potential conflicts of interests. Awareness of OPP, its data, and its implications for transplantation are critical. We used the first wave of OPP data to describe industry payments made to transplant surgeons. Transplant surgeons (N = 297) received a total of $759 654. The median (interquartile range [IQR]) payment to a transplant surgeon was $125 ($39-1018), and the highest payment to an individual surgeon was $83 520; 122 surgeons received <$100, and 17 received >$10 000. A higher h-index was associated with 30% higher chance of receiving >$1000 (relative risk/10 unit h-index increase = 1.18 1.301.44 , p < 0.001). The highest payment category was consulting fees, with a total of $314 448 paid in this reported category. Recipients of consulting fees had higher h-indices, median (IQR) of 20 (10-35) versus nine (3-17) (p < 0.001). Ten of 122 companies accounted for 62% of all payments. Kidney transplant and liver transplant (LT) centers that received >$1000 had higher center volumes (p < 0.001). LT centers that received payments of >$1000 had a higher percentage of private-insurance/self-pay patients (p < 0.01). Continued surveillance of industry payments may further elucidate the relationship between industry payments and physician practices.

Early Hospital Readmission After Simultaneous Pancreas-Kidney Transplantation: Patient and Center-Level Factors.

Early hospital readmission is associated with increased morbidity, mortality, and cost. Following simultaneous pancreas-kidney transplantation, rates of readmission and risk factors for readmission are unknown. We used United States Renal Data System data to study 3643 adult primary first-time simultaneous pancreas-kidney recipients from December 1, 1999 to October 31, 2011. Early hospital readmission was any hospitalization within 30 days of discharge. Modified Poisson regression was used to determine the association between readmission and patient-level factors. Empirical Bayes statistics were used to determine the variation attributable to center-level factors. The incidence of readmission was 55.5%. Each decade increase in age was associated with an 11% lower risk of readmission to age 40, beyond which there was no association. Donor African-American race was associated with a 13% higher risk of readmission. Each day increase in length of stay was associated with a 2% higher risk of readmission until 14 days, beyond which each day increase was associated with a 1% reduction in the risk of readmission. Center-level factors were not associated with readmission. The high incidence of early hospital readmission following simultaneous pancreas-kidney transplant may reflect clinical complexity rather than poor quality of care.

A Risk Index for Living Donor Kidney Transplantation.

Choosing between multiple living kidney donors, or evaluating offers in kidney paired donation, can be challenging because no metric currently exists for living donor quality. Furthermore, some deceased donor (DD) kidneys can result in better outcomes than some living donor kidneys, yet there is no way to compare them on the same scale. To better inform clinical decision-making, we created a living kidney donor profile index (LKDPI) on the same scale as the DD KDPI, using Cox regression and adjusting for recipient characteristics. Donor age over 50 (hazard ratio [HR] per 10 years = 1.15 1.241.33 ), elevated BMI (HR per 10 units = 1.01 1.091.16 ), African-American race (HR = 1.15 1.251.37 ), cigarette use (HR = 1.09 1.161.23 ), as well as ABO incompatibility (HR = 1.03 1.271.58 ), HLA B (HR = 1.03 1.081.14 ) mismatches, and DR (HR = 1.04 1.091.15 ) mismatches were associated with greater risk of graft loss after living donor transplantation (all p < 0.05). Median (interquartile range) LKDPI score was 13 (1-27); 24.2% of donors had LKDPI < 0 (less risk than any DD kidney), and 4.4% of donors had LKDPI > 50 (more risk than the median DD kidney). The LKDPI is a useful tool for comparing living donor kidneys to each other and to deceased donor kidneys.

One Size Does Not Fit All--Regional Variation in the Impact of the Share 35 Liver Allocation Policy.

Allocation policies for liver transplantation underwent significant changes in June 2013 with the introduction of Share 35. We aimed to examine the effect of Share 35 on regional variation in posttransplant outcomes. We examined two patient groups from the United Network for Organ Sharing dataset; a pre-Share 35 group composed of patients transplanted between June 17, 2012, and June 17, 2013 (n = 5523), and a post-Share group composed of patients transplanted between June 18, 2013, and June 18, 2014 (n = 5815). We used Kaplan-Meier and Cox multivariable analyses to compare survival. There were significant increases in allocation Model for End-stage Liver Disease (MELD) scores, laboratory MELD scores, and proportions of patients in the intensive care unit and on mechanical, ventilated, or organ-perfusion support at transplant post-Share 35. We also observed a significant increase in donor risk index in this group. We found no difference on a national level in survival between patients transplanted pre-Share 35 and post-Share 35 (p = 0.987). Regionally, however, posttransplantation survival was significantly worse in the post-Share 35 patients in regions 4 and 10 (p = 0.008 and p = 0.04), with no significant differences in the remaining regions. These results suggest that Share 35 has been associated with transplanting "sicker patients" with higher MELD scores, and although no difference in survival is observed on a national level, outcomes appear to be concerning in some regions.

Landscape of Deceased Donors Labeled Increased Risk for Disease Transmission Under New Guidelines.

Deceased donors are labeled increased risk for disease transmission (IRD) if they meet certain criteria. New PHS guidelines were recently implemented; the impact of these changes remains unknown. We aimed to quantify the impact of the new guidelines on the proportion of deceased donors labeled IRD, as well as demographic and clinical characteristics. We used Poisson regression with an interaction term for era (new vs. old guidelines) to quantify changes. Under the new guidelines, 19.5% donors were labeled IRD, compared to 10.4%, 12.2%, and 12.3% in the 3 most recent years under the old guidelines (IRR = 1.45, p < 0.001). Increases were consistent across OPOs: 44/59 had an increase in the percent of donors labeled IRD, and 14 OPOs labeled 25% of their donors IRD under the new guidelines (vs. 5 OPOs under the old). African-Americans were 52% more likely to be labeled IRD under the new guidelines (RR = 1.52, p = 0.01). There has been a substantial increase in donors labeled IRD under the new PHS guidelines; it is important to understand the mechanism and consequences to ensure an optimal balance of patient safety and organ utilization is achieved.

Early changes in liver distribution following implementation of Share 35.

In June 2013, a change to the liver waitlist priority algorithm was implemented. Under Share 35, regional candidates with MELD ≥ 35 receive higher priority than local candidates with MELD < 35. We compared liver distribution and mortality in the first 12 months of Share 35 to an equivalent time period before. Under Share 35, new listings with MELD ≥ 35 increased slightly from 752 (9.2% of listings) to 820 (9.7%, p = 0.3), but the proportion of deceased-donor liver transplants (DDLTs) allocated to recipients with MELD ≥ 35 increased from 23.1% to 30.1% (p < 0.001). The proportion of regional shares increased from 18.9% to 30.4% (p < 0.001). Sharing of exports was less clustered among a handful of centers (Gini coefficient decreased from 0.49 to 0.34), but there was no evidence of change in CIT (p = 0.8). Total adult DDLT volume increased from 4133 to 4369, and adjusted odds of discard decreased by 14% (p = 0.03). Waitlist mortality decreased by 30% among patients with baseline MELD > 30 (SHR = 0.70, p < 0.001) with no change for patients with lower baseline MELD (p = 0.9). Posttransplant length-of-stay (p = 0.2) and posttransplant mortality (p = 0.9) remained unchanged. In the first 12 months, Share 35 was associated with more transplants, fewer discards, and lower waitlist mortality, but not at the expense of CIT or early posttransplant outcomes.

Big data in organ transplantation: registries and administrative claims.

The field of organ transplantation benefits from large, comprehensive, transplant-specific national data sets available to researchers. In addition to the widely used Organ Procurement and Transplantation Network (OPTN)-based registries (the United Network for Organ Sharing and Scientific Registry of Transplant Recipients data sets) and United States Renal Data System (USRDS) data sets, there are other publicly available national data sets, not specific to transplantation, which have historically been underutilized in the field of transplantation. Of particular interest are the Nationwide Inpatient Sample and State Inpatient Databases, produced by the Agency for Healthcare Research and Quality. The USRDS database provides extensive data relevant to studies of kidney transplantation. Linkage of publicly available data sets to external data sources such as private claims or pharmacy data provides further resources for registry-based research. Although these resources can transcend some limitations of OPTN-based registry data, they come with their own limitations, which must be understood to avoid biased inference. This review discusses different registry-based data sources available in the United States, as well as the proper design and conduct of registry-based research.

Survival benefit of primary deceased donor transplantation with high-KDPI kidneys.

The Kidney Donor Profile Index (KDPI) has been introduced as an aid to evaluating deceased donor kidney offers, but the relative benefit of high-KDPI kidney transplantation (KT) versus the clinical alternative (remaining on the waitlist until receipt of a lower KDPI kidney) remains unknown. Using time-dependent Cox regression, we evaluated the mortality risk associated with high-KDPI KT (KDPI 71-80, 81-90 or 91-100) versus a conservative, lower KDPI approach (remain on waitlist until receipt of KT with KDPI 0-70, 0-80 or 0-90) in first-time adult registrants, adjusting for candidate characteristics. High-KDPI KT was associated with increased short-term but decreased long-term mortality risk. Recipients of KDPI 71-80 KT, KDPI 81-90 KT and KDPI 91-100 KT reached a "break-even point" of cumulative survival at 7.7, 18.0 and 19.8 months post-KT, respectively, and had a survival benefit thereafter. Cumulative survival at 5 years was better in all three high-KDPI groups than the conservative approach (p < 0.01 for each comparison). Benefit of high-KDPI KT was greatest in patients age >50 years and patients at centers with median wait time ≥33 months. Recipients of high-KDPI KT can enjoy better long-term survival; a high-KDPI score does not automatically constitute a reason to reject a deceased donor kidney.

Experiences obtaining insurance after live kidney donation.

The impact of kidney donation on the ability to change or initiate health or life insurance following donation is unknown. To quantify this risk, we surveyed 1046 individuals who donated a kidney at our center between 1970 and 2011. Participants were asked whether they changed or initiated health or life insurance after donation, and if they had any difficulty doing so. Among 395 donors who changed or initiated health insurance after donation, 27 (7%) reported difficulty; among those who reported difficulty, 15 were denied altogether, 12 were charged a higher premium and 8 were told they had a preexisting condition because they were kidney donors. Among 186 donors who changed or initiated life insurance after donation, 46 (25%) reported difficulty; among those who reported difficulty, 23 were denied altogether, 27 were charged a higher premium and 17 were told they had a preexisting condition because they were kidney donors. In this single-center study, a high proportion of kidney donors reported difficulty changing or initiating insurance, particularly life insurance. These practices by insurers create unnecessary burden and stress for those choosing to donate and could negatively impact the likelihood of live kidney donation among those considering donation.

Quantifying the risk of incompatible kidney transplantation: a multicenter study.

Incompatible live donor kidney transplantation (ILDKT) offers a survival advantage over dialysis to patients with anti-HLA donor-specific antibody (DSA). Program-specific reports (PSRs) fail to account for ILDKT, placing this practice at regulatory risk. We collected DSA data, categorized as positive Luminex, negative flow crossmatch (PLNF) (n = 185), positive flow, negative cytotoxic crossmatch (PFNC) (n = 536) or positive cytotoxic crossmatch (PCC) (n = 304), from 22 centers. We tested associations between DSA, graft loss and mortality after adjusting for PSR model factors, using 9669 compatible patients as a comparison. PLNF patients had similar graft loss; however, PFNC (adjusted hazard ratio [aHR] = 1.64, 95% confidence interval [CI]: 1.15-2.23, p = 0.007) and PCC (aHR = 5.01, 95% CI: 3.71-6.77, p < 0.001) were associated with increased graft loss in the first year. PLNF patients had similar mortality; however, PFNC (aHR = 2.04; 95% CI: 1.28-3.26; p = 0.003) and PCC (aHR = 4.59; 95% CI: 2.98-7.07; p < 0.001) were associated with increased mortality. We simulated Centers for Medicare & Medicaid Services flagging to examine ILDKT's effect on the risk of being flagged. Compared to equal-quality centers performing no ILDKT, centers performing 5%, 10% or 20% PFNC had a 1.19-, 1.33- and 1.73-fold higher odds of being flagged. Centers performing 5%, 10% or 20% PCC had a 2.22-, 4.09- and 10.72-fold higher odds. Failure to account for ILDKT's increased risk places centers providing this life-saving treatment in jeopardy of regulatory intervention.

Rates of false flagging due to statistical artifact in CMS evaluations of transplant programs: results of a stochastic simulation.

The recent CMS conditions of participation are based on risk-adjusted models produced by the Scientific Registry for Transplant Recipients (SRTR). The accuracy of these models in identifying poor-performing centers is unknown. In this stochastic simulation study, 1-year mortality outcomes were simulated in virtual transplant centers, and used to flag centers according to the methods used by CMS, evaluating nine overlapping 2.5-year periods of simulated data. In a simulation where all centers had the same underlying risk, 10.2% were falsely flagged at least once during the 4.5 years of simulated evaluations. The probability of false-positive flagging was lowest in low-volume centers (2.5%) and highest in high-volume centers (16.2%). In another simulation where 5% of centers were assigned twofold risk ("poor-performing centers"), only 32% of poor-performing centers were correctly flagged. In a final simulation where each center was assigned a unique mortality risk, 94% of flagged centers had greater-than-median risk, but only 32% of flagged centers were among the 5% with highest risk. Even after disregarding known covariate limitations to the risk adjustment models, statistical noise alone leads to spurious flagging of many adequately-performing transplant centers, yet the methods used by CMS fail to flag most centers with true elevated risk.