Market Competition and Density in Liver Transplantation: Relationship to Volume and Outcomes

Identifying and understanding variation in population-based access to liver transplantation in the United States

We aimed to identify variations in liver transplant access across transplant referral regions (TRRs), accounting for differences in population characteristics and practice environments. Adult end-stage liver disease (ESLD) deaths and liver waitlist additions from 2015 to 2019 were included. The primary outcome was listing-to-death ratio (LDR). We modeled the LDR as a continuous variable and obtained adjusted LDR estimates for each TRR, accounting for clinical and demographic characteristics of ESLD decedents, socioeconomic and health care environment within the TRR, and characteristics of the transplant environment. The overall mean LDR was 0.24 (range: 0.10-0.53). In the final model, proportion of patients living in poverty and concentrated poverty was negatively associated with LDR; organ donation rate was positively associated with LDR. The R2 was 0.60, indicating that 60% of the variability in LDR was explained by the model. Approximately 40% of this variation remained unexplained and may be due to transplant center behaviors amenable to intervention to improve access to care for patients with ESLD.

Center expansion of liver transplants using donation after circulatory death organs is associated with reduced overall waitlist mortality

INTRODUCTION

Waitlist outcomes in liver transplantation (LT) for individual recipients are improved by use of allografts procured through donation after circulatory death (DCD). However, the impact of increased DCD acceptance on overall center outcomes is unknown.

METHODS

Using the United Network for Organ Sharing database, 88 centers performing an average of ≥10 LTs/year between 1/2004 and 12/2019 were compared by percent DCD use quartile and categorized into four phenotypes according to temporal usage trends. Overall center median Model for End-stage Liver Disease at LT (MMaT), waitlist mortality, and waiting time were evaluated.

RESULTS

The overall DCD rate was 6.1% (N = 4906/80,709), ranging from 0% to 25.5%. Centers in the top DCD use quartile had lower MMaT (24 vs. 26; p < .001) and shorter overall waiting times (median 66 days vs. 90 days; p < .001) compared to bottom quartile centers. MMaT increased less over time at centers with increasing DCD use and was lower than at centers with declining DCD use (27 vs. 32; p = .017). Overall waitlist mortality between 2016 and 2019 was lower at increasing DCD use centers (17.8% vs. 22.5%, p = .034), yet did not affect 1-year mortality (p = .747).

CONCLUSIONS

The improved waitlist outcomes at centers with expanded DCD use extend beyond DCD recipients alone without negative consequences to overall post-LT center metrics.

County-level Differences in Liver-related Mortality, Waitlisting, and Liver Transplantation in the United States

BACKGROUND

Much of our understanding regarding geographic issues in transplantation is based on statistical techniques that do not formally account for geography and is based on obsolete boundaries such as donation service area.

METHODS

We applied spatial epidemiological techniques to analyze liver-related mortality and access to liver transplant services at the county level using data from the Centers for Disease Control and Prevention and Scientific Registry of Transplant Recipients from 2010 to 2018.

RESULTS

There was a significant negative spatial correlation between transplant rates and liver-related mortality at the county level (Moran's I, -0.319; P  = 0.001). Significant clusters were identified with high transplant rates and low liver-related mortality. Counties in geographic clusters with high ratios of liver transplants to liver-related deaths had more liver transplant centers within 150 nautical miles (6.7 versus 3.6 centers; P  < 0.001) compared with all other counties, as did counties in geographic clusters with high ratios of waitlist additions to liver-related deaths (8.5 versus 2.5 centers; P  < 0.001). The spatial correlation between waitlist mortality and overall liver-related mortality was positive (Moran's I, 0.060; P  = 0.001) but weaker. Several areas with high waitlist mortality had some of the lowest overall liver-related mortality in the country.

CONCLUSIONS

These data suggest that high waitlist mortality and allocation model for end-stage liver disease do not necessarily correlate with decreased access to transplant, whereas local transplant center density is associated with better access to waitlisting and transplant.

Prognostic role of the Donor Risk Index, the Eurotransplant Donor Risk Index, and the Balance of Risk score on graft loss after liver transplantation

This study aimed to identify cutoff values for donor risk index (DRI), Eurotransplant (ET)-DRI, and balance of risk (BAR) scores that predict the risk of liver graft loss. MEDLINE and Web of Science databases were searched systematically and unrestrictedly. Graft loss odds ratios and 95% confidence intervals were assessed by meta-analyses using Mantel-Haenszel tests with a random-effects model. Cutoff values for predicting graft loss at 3 months, 1 year, and 3 years were analyzed for each of the scores. Measures of calibration and discrimination used in studies validating the DRI and the ET-DRI were summarized. DRI ≥ 1.4 (six studies, n = 35 580 patients) and ET-DRI ≥ 1.4 (four studies, n = 11 666 patients) were associated with the highest risk of graft loss at all time points. BAR > 18 was associated with the highest risk of 3-month and 1-year graft loss (n = 6499 patients). A DRI cutoff of 1.8 and an ET-DRI cutoff of 1.7 were estimated using a summary receiver operator characteristic curve, but the sensitivity and specificity of these cutoff values were low. A DRI and ET-DRI score ≥ 1.4 and a BAR score > 18 have a negative influence on graft survival, but these cutoff values are not well suited for predicting graft loss.

Evaluating Spatial Associations in Inpatient Deaths Between Organ Procurement Organizations

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Impact of the elimination of the donation service area on United States lung transplant practices and outcomes at high and low competition centers

In November 2017, the donation service area (DSA) was removed as the primary unit of US donor lung allocation. Our primary objective was to evaluate the effect of this change on recipient characteristics, the use of pretransplant extracorporeal membrane oxygenation (ECMO), and on index hospitalization length of stay (LOS) and early posttransplant complications. We also assessed whether these outcomes differed in high and low competition centers, as defined by the Herfindahl-Hirschman Index. Following DSA removal, there was a 9-day decrease in median waitlist time (P = .001) and an increase in median lung allocation score (40 vs 42, P < .0001) but no difference in the need for pretransplant ECMO (incidence rate ratio = 1.16, P = .12). Median LOS increased from 17 to 19 days in the post-DSA era (P = .01). There was no difference in posttransplant outcomes, including prolonged ventilation, new dialysis, or early survival, in the general cohort or between competition groups. High competition centers saw an 18.5-minute increase in ischemic time compared to low competition centers (P = .04) but did not differentially increase single lung transplants or pretransplant ECMO utilization. Overall, DSA elimination was associated with increased posttransplant LOS but no significant differences in pretransplant ECMO or other posttransplant outcomes. Effects were largely similar at low and high competition centers.

Center Variation in Intention-to-Treat Survival Among Patients Listed for Liver Transplant

In the United States, centers performing liver transplant (LT) are primarily evaluated by patient survival within 1 year after LT, but tight clustering of outcomes allows only a narrow window for evaluation of center variation for quality improvement. Alternate measures more relevant to patients and the transplant community are needed. We examined adults listed for LT in the United States, using data submitted to the Scientific Registry of Transplant Recipients. Intention-to-treat (ITT) survival was defined as survival within 1 year from listing, regardless of transplant. Mixed effects/frailty models were used to assess center variation in ITT survival. Between January 2010 and December 2016, there were 66,428 new listings at 113 centers. Overall, median 1-year ITT survival was 79.8% (interquartile range [IQR], 76.1%-83.4%), whereas 1-year waiting-list (WL) survival was 75.8% (IQR, 71.2%-79.4%), and 1-year post-LT survival was 90.0% (IQR, 87.9%-91.8%). Higher rates of ITT mortality were correlated with increased WL mortality (correlation, r = 0.76), increased post-LT mortality (r = 0.31), lower volume centers (r = -0.34), and lower transplant rate ratio (r = -0.25). Similar patterns were observed in the subgroup of WL candidates listed with Model for End-Stage Liver Disease (MELD) ≥25: median 1-year ITT survival was 65.2% (IQR, 60.2%-72.6%), whereas 1-year post-LT survival was 87.5% (IQR, 84.0%-90.9%), and 1-year WL survival was 36.6% (IQR, 27.9%-47.0%). In mixed effects modeling, the transplant center was an independent predictor of ITT survival even after adjustment for age, sex, MELD, and sociodemographic variables. Center variation for ITT survival was larger compared with post-LT survival. The measurement of ITT outcome offers a complementary method to assess center performance. This is a first step toward understanding differences in program quality beyond patient and graft survival after LT.

The Volume-outcome Relationship in Deceased Donor Kidney Transplantation and Implications for Regionalization

OBJECTIVE

The aim of this study was to investigate the volume-outcome relationship in kidney transplantation by examining graft and patient outcomes using standardized risk adjustment (observed-to-expected outcomes). A secondary objective was to examine the geographic proximity of low, medium, and high-volume kidney transplant centers in the United States.

SUMMARY OF BACKGROUND DATA

The significant survival benefit of kidney transplantation in the context of a severe shortage of donor organs mandates strategies to optimize outcomes. Unlike for other solid organ transplants, the relationship between surgical volume and kidney transplant outcomes has not been clearly established.

METHODS

The Scientific Registry of Transplant Recipients was used to examine national outcomes for adults undergoing deceased donor kidney transplantation from January 1, 1999 to December 31, 2013 (15-year study period). Observed-to-expected rates of graft loss and patient death were compared for low, medium, and high-volume centers. The geographic proximity of low-volume centers to higher volume centers was determined to assess the impact of regionalization on patient travel burden.

RESULTS

A total of 206,179 procedures were analyzed. Compared with low-volume centers, high-volume centers had significantly lower observed-to-expected rates of 1-month graft loss (0.93 vs 1.18, P<0.001), 1-year graft loss (0.97 vs 1.12, P<0.001), 1-month patient death (0.90 vs 1.29, P=0.005), and 1-year patient death (0.95 vs 1.15, P=0.001). Low-volume centers were frequently in close proximity to higher volume centers, with a median distance of 7 miles (interquartile range: 2 to 75).

CONCLUSIONS

A robust volume-outcome relationship was observed for deceased donor kidney transplantation, and low-volume centers are frequently in close proximity to higher volume centers. Increased regionalization could improve outcomes, but should be considered carefully in light of the potential negative impact on transplant volume and access to care.

Health Literacy Burden Is Associated With Access to Liver Transplantation

BACKGROUND

Getting listed for liver transplantation is a complex process. Institutional health literacy may influence the ability of patients with limited educational attainment (EA) to list. As an easily accessible indicator of institutional health literacy, we measured the understandability of liver transplant center education websites and assessed whether there was any association with the percentage of low EA patients on their waitlists.

METHODS

Patients on the waitlist for liver transplantation 2007-2016 were identified in Scientific Registry of Transplant Recipients. Understandability of patient education websites was assessed using the Clear Communication Index (CCI). The Centers for Disease Control and Prevention has set itself a goal CCI of 90 as being easy to understand. Low EA was defined as less than a high school education. We adjusted for center case-mix, Donor Service Area characteristics, and EA of the general population.

RESULTS

Patients (84 774) were listed across 112 liver transplant centers. The median percent of waitlisted patients at each center with low EA was 11.0% (IQR, 6.6-16.8). CCI ranged from 53 to 88 and correlated with the proportion of low EA patients on the waitlist. However, CCI was not associated with the percentage of low EA in the general population. For every 1-point improvement in CCI, low EA patients increase by 0.2% (P < 0.05), translating to a 3.6% increase, or additional 3000 patients, if all centers improved their websites to CCI of 90.

CONCLUSIONS

Educational websites that are easier to understand are associated with increased access to liver transplantation for patients with low EA. Lowering the health literacy burden by transplant centers may improve access to the liver transplant waitlist.

Do Social Determinants Define "Too Sick" to Transplant in Patients With End-stage Liver Disease?

BACKGROUND

Delisting for being "too sick" to be transplanted is subjective. Previous work has demonstrated that the mortality of patients delisted for "too sick" is unexpectedly low. Transplant centers use their best clinical judgment for determining "too sick," but it is unclear how social determinants influence decisions to delist for "too sick." We hypothesized that social determinants and Donor Service Area (DSA) characteristics may be associated with determination of "too sick" to transplant.

METHODS

Data were obtained from the Scientific Registry of Transplant Recipients for adults listed and removed from the liver transplant waitlist from 2002 to 2017. Patients were included if delisted for "too sick." Our primary outcome was Model for End-Stage Liver Disease (MELD) score at waitlist removal for "too sick." Regression assessed the association between social determinants and MELD at removal for "too sick."

RESULTS

We included 5250 delisted for "too sick" at 127 centers, in 53 DSAs, over 16 years. The mean MELD at delisting for "too sick" was 25.8 (SD ± 11.2). On adjusted analysis, social determinants including age, race, sex, and education predicted the MELD at delisting for "too sick" (P < 0.05).

CONCLUSIONS

There is variation in delisting MELD for "too sick" score across DSA and time. While social determinants at the patient and system level are associated with delisting practices, the interplay of these variables warrants additional research. In addition, center outcome reports should include waitlist removal rate for "too sick" and waitlist death ratios, so waitlist management practice at individual centers can be monitored.

The donor risk index: A decade of experience

In 2006, derivation of the donor risk index (DRI) highlighted the importance of donor factors for successful liver transplantation. Over the last decade, the DRI has served as a useful metric of donor quality and has enhanced our understanding of donor factors and their impact upon recipients with hepatitis C virus, those with low Model for End-Stage Liver Disease (MELD) score, and individuals undergoing retransplantation. DRI has provided the transplant community with a common language for describing donor organ characteristics and has served as the foundation for several tools for organ risk assessment. It is a useful tool in assessing the interactions of donor factors with recipient factors and their impact on posttransplant outcomes. However, limitations of statistical modeling, choice of donor factors, exclusion of unaccounted donor and geographic factors, and the changing face of the liver transplant recipient have tempered its widespread use. In addition, the DRI was derived from data before the MELD era but is currently being applied to expand the donor pool while concurrently meeting the demands of a dynamic allocation system. A decade after its introduction, DRI remains relevant but may benefit from being updated to provide guidance in the use of extended criteria donors by accounting for the impact of geography and unmeasured donor characteristics. DRI could be better adapted for recipients with nonalcoholic fatty liver disease by examining and including recipient factors unique to this population. Liver Transplantation 23 1216-1225 2017 AASLD.

Geographic Disparities in Liver Availability: Accidents of Geography, or Consequences of Poor Social Policy?

Recently, a redistricting proposal intended to equalize Model for End-stage Liver Disease score at transplant recommended expanding liver sharing to mitigate geographic variation in liver transplantation. Yet, it is unclear whether variation in liver availability is arbitrary and a disparity requiring rectification or reflects differences in access to care. We evaluate the proposal's claim that organ supply is an "accident of geography" by examining the relationship between local organ supply and the uneven landscape of social determinants and policies that contribute to differential death rates across the United States. We show that higher mortality leading to greater availability of organs may in part result from disproportionate risks incurred at the local level. Disparities in public safety laws, health care infrastructure, and public funding may influence the risk of death and subsequent availability of deceased donors. These risk factors are disproportionately prevalent in regions with high organ supply. Policies calling for organ redistribution from high-supply to low-supply regions may exacerbate existing social and health inequalities by redistributing the single benefit (greater organ availability) of greater exposure to environmental and contextual risks (e.g. violent death, healthcare scarcity). Variation in liver availability may not be an "accident of geography" but rather a byproduct of disadvantage.

Distance is associated with mortality on the waitlist in pediatric liver transplantation

The distance to liver transplant centers affects outcomes in adult liver transplantation. Because pediatric patients are particularly vulnerable, we hypothesized that distance adversely affects the time to transplantation and waitlist mortality. The SRTR was queried for isolated pediatric liver transplant registrants (under age 18) with valid ZIP code information from 2003 to 2012. Distance was measured from home ZIP code to listing transplant center. Competing events analysis, adjusted for demographic factors, indication, and PELD, was undertaken for transplantation and death while on the waitlist. The median distance to listing transplant center for 6924 children was 65 (IQR 17.5-189) miles. Median distance traveled increased by listing volume (73.9 vs 33.8 miles, highest vs lowest volume quartile, P<.001 for trend) and varied across the country. Longer distance was not associated with time to transplantation (HR 0.99, longest vs shortest distance quartile, P=.80), but was associated with increased mortality (HR 1.75, P<.001). Larger centers attract patients from a distance, while smaller centers serve local populations. Increasing distance is associated with a higher risk of waitlist death, which may reflect decreased access to specialist and tertiary care associated with a transplant center.

Deceased Organ Donor Management: Does Hospital Volume Matter?

BACKGROUND

Identification of strategies to improve organ donor use remains imperative. Despite the association between hospital volume and outcomes for many common disease processes, there have been no studies that assess the impact of organ donor hospital volume on organ yield.

STUDY DESIGN

A prospective observational study of all deceased organ donors managed by 10 organ procurement organizations across United Network for Organ Sharing regions 4, 5, and 6 was conducted from February 2012 to June 2015. To study the impact of hospital volume on organ yield, each donor was placed into a hospital-volume quartile based on the number of donors managed by their hospital. Stepwise logistic regression was used to identify the independent effect of hospital volume on the primary outcomes measure of having ≥4 organs transplanted per donor.

RESULTS

Data from 4,427 donors across 384 hospitals were collected and hospitals were assigned quartiles based on their volume of deceased donors. Hospitals managed a mean ± SD of 3.3 ± 5.2 donors per hospital per year. After adjusting for age, ethnicity, donor type, blood type, BMI, creatinine, and organ procurement organization/donor service area, being managed in hospitals within the highest volume quartile remained a positive independent predictor of ≥4 organs transplanted per donor (odds ratio = 1.52; 95% CI 1.29 to 1.79; p < 0.001).

CONCLUSIONS

Deceased organ donor hospital volume impacts organ yield, with the highest-volume centers being 52% more likely to achieve ≥4 organs transplanted per donor. Efforts should be made to share practices from these higher-volume centers and consideration should be given to centralization of donor care.