Outcomes of Liver Transplantation by Insurance Type in the United States

Patients with publicly sponsored insurance who were listed for liver transplantation have worse wait-list and posttransplant outcomes, as shown using the US Scientific Registry of Transplant Recipients (2001-2017).


Objectives: The outcomes of liver transplantation may vary according to socioeconomic factors such as insurance coverage. The aim of this study was to assess the association between the type of insurance payer and outcomes of liver transplant candidates and recipients in the United States.

Study Design: This was a retrospective cohort study of a national database.

Methods: The US Scientific Registry of Transplant Recipients was used to select adults (≥18 years) wait-listed for liver transplantation in the United States (2001-2017); patients were followed until March 2018.

Results: There were 177,862 liver transplant candidates with payer and outcomes data: The mean (SD) age was 54.1 (10.4) years, 64% were male, 39% had chronic hepatitis C with or without alcoholic liver disease (ALD), 19% had ALD alone, 17% had nonalcoholic steatohepatitis, and 16% had hepatocellular carcinoma. Fifty-nine percent were primarily covered by private insurance, 21% by Medicare, and 16% by Medicaid. After listing, 56% eventually received transplants (mean wait time of 229 days) and 22% dropped off the list. In multivariate analysis, adjusted for demographic and clinical factors, being covered by Medicare (odds ratio [OR], 0.81; 95% CI, 0.78-0.84) or Medicaid (OR, 0.76; 95% CI, 0.73-0.79) was independently associated with a lower chance of receiving a transplant (reference: private insurance). Posttransplant mortality was 11.6% at 1 year, 20.1% at 3 years, 26.8% at 5 years, and 41.6% at 10 years. Having Medicare (adjusted hazard ratio [aHR], 1.24; 95% CI, 1.17-1.31) or Medicaid (aHR, 1.14; 95% CI, 1.06-1.21) was independently associated with higher posttransplant mortality (P <.001) but not with the risk of graft loss (P >.05).

Conclusions: Liver transplant candidates covered by Medicare or Medicaid have poorer wait-list outcomes and higher posttransplant mortality.

Am J Manag Care. 2020;26(4):e121-e126. https://doi.org/10.37765/ajmc.2020.42839

Takeaway Points

  • The outcomes of liver transplantation may vary according to socioeconomic factors such as insurance coverage.
  • In this study, we have shown that liver transplant candidates covered by Medicare or Medicaid have poorer wait-list and transplant outcomes, including higher on-the-list and posttransplant mortality, even after adjustment for clinicodemographic confounders.
  • Because the proportion of such patients in the United States is increasing, providers may need to consider more vigilant management and follow-up of these patients to optimize their outcomes.

Liver transplantation is a life-saving treatment for patients with end-stage liver disease. In the United States, patients who are on the waiting list for liver transplantation are prioritized based on their Model for End-Stage Liver Disease (MELD) scores.1 In that model, higher scores are assigned to patients with higher estimated risks of pretransplant mortality. The ultimate aim of prioritization is to minimize wait-list mortality in the setting of limited organ supply.2,3 Despite this strategy, at present, there is a major organ shortage in the country resulting in substantial on-list mortality, which, despite recent decline, still exceeds 10 per 100 patient-years.4 In addition, recent trends in transplant and mortality rates reported by the US Organ Procurement and Transplantation Network (OPTN) suggest that there is notable geographic difference in wait-list outcomes and that those outcomes are influenced by factors other than organ availability; these factors may include referral and wait-list registration practices across the country, pretransplant patient management, and quality of care.4

Prior epidemiologic reports suggest that a number of patient clinical and demographic parameters could be associated with wait-list and posttransplant outcomes even after accounting for patients’ MELD scores.5-10 In this context, prior study findings regarding a number of high-cost treatments suggest the presence of an association between poorer outcomes and lower socio&shy;economic status and/or having publicly sponsored insurance.11-17 In fact, having a publicly sponsored plan has been reported as a significant risk factor in risk-adjustment models developed by the Scientific Registry of Transplant Recipients (SRTR).18 Further, the association of socioeconomic status and, in particular, insurance type with wait-list and transplantation outcomes has been reported for liver and nonliver transplant candidates and recipients.15,17,19-21 The aim of this study was to use recent national registry data to compare the outcomes of both liver transplant candidates and recipients covered by different types of insurance in the United States.


Study Cohort

This study used data from the SRTR. The SRTR data system has been described elsewhere; it includes data submitted by the members of the OPTN on all donors, wait-listed candidates, and transplant recipients in the United States. The Health Resources and Services Administration within HHS provides oversight of the activities of the OPTN and SRTR contractors.

For the purpose of this study, we included all wait-listed candidates and transplant recipients 18 years or older who were listed for or underwent liver transplantation with any listing diagnosis between 2001 and 2017 and had their primary payer data available. Patients’ demographic and clinical parameters were collected from SRTR candidate and transplantation records. For transplant recipients’ records, their donors’ characteristics were also extracted; high-risk donors were recorded according to the CDC criteria.22,23 Posttransplant follow-up data were collected 6 months after the transplantation and then annually. Patients’ outcomes (receiving a transplant, wait-list dropout owing to mortality or deterioration, posttransplant mortality, and graft loss) were recorded as of March 1, 2018.

Statistical Analysis

Patients were grouped based on their primary payer included in the SRTR database: private insurance, Medicare, Medicaid, or other (Veterans Affairs healthcare system, other government-sponsored, self-pay, donation). Clinicodemographic parameters were compared across the 4 groups using χ2 or Kruskal-Wallis nonparametric tests. The trends in outcomes over time were statistically assessed using Kendall correlation coefficients and were compared among payer groups using a linear trend regression model. Independent predictors of wait-list and posttransplant outcomes were studied using logistic (binary outcomes) and Cox proportional hazard (time-to-event outcomes) regression models.

All analyses were run in SAS version 9.4 (SAS Institute; Cary, North Carolina). The study was granted a nonhuman subject research status by the Inova Institutional Review Board.


There were 177,862 wait-listed candidates in SRTR who were 18 years or older, were listed between 2001 and 2017, and had payer data available. Of those, 59% had private insurance, 21% had Medicare, 16% had Medicaid, and 4% had another type of coverage. Over time, the proportion of privately insured candidates significantly decreased (from 67% in 2001 to 52% in 2017) while the proportions of both Medicaid (from 14% in 2001 to 17% in 2017) and especially Medicare (from 14% in 2001 to 27% in 2017) increased (all P <.01).

Wait-listed candidates had a mean (SD) age of 54 (10) years, 64% were male, 71% were white, 24% had a college degree, 23% were employed at listing, 70% were listed in 1 of 50 high-volume centers (>1500 listings for the study period), 19% had type 2 diabetes, and 6% underwent retransplantation (Table 1). Patients with private insurance were the most likely to be white, have a college degree, and be employed; had the highest functional status at listing; and had the lowest rates of ascites, bacterial peritonitis, hepatic encephalopathy, and dialysis (P <.0001) (Table 1). Patients with Medicare were the oldest and had the highest proportions of diabetes and hypertension (P <.0001) (Table 1). Patients with Medicaid were the most likely to be Hispanic and had the lowest rate of having a college degree, the lowest functional status, the highest MELD scores, and the highest rate of having bacterial peritonitis and variceal bleeding (P <.0001) (Table 1).

The most prevalent listing diagnosis in all patient groups was hepatitis C (31%-35%), followed by alcoholic cirrhosis (17%-23%) and nonalcoholic steatohepatitis (NASH) (11%-22%) (Table 2). In addition, between 15% and 20% had hepatocellular carcinoma (HCC). The greatest difference among the patient groups was in the proportion of NASH: It was 2-fold higher in those covered by Medicare than by Medicaid (P <.0001) (Table 2).

Of all candidates, 56% eventually underwent transplant after a mean waiting time of 229 days. The transplant rate was the highest in the privately insured group (58%) and the lowest among the Medicaid group (51%) (P <.0001) (Table 3). On the other hand, privately insured patients experienced the longest waiting time (mean of 243 days vs 203-214 days in the other groups; P <.0001) (Table 3). Over time, there were no changes in the transplant rates in all payer groups (all P >.05) (Figure [A]). The rate of wait-list dropout (death or deterioration) was the highest in Medicare-insured patients at 26% versus 21% in privately insured patients (P <.0001) (Table 3). Over the study period, the dropout rates decreased significantly in the privately insured and Medicaid-insured groups (Kendall τ = —0.48 and –0.43, respectively; both P <.05) and borderline significantly in the Medicare group (τ = —0.28; P = .12) (Figure [B]).

In multivariate regression analysis, compared with having private insurance, having Medicare and having Medicaid were independently associated with a lower chance of receiving a transplant after adjustment for the year of listing, demographics, and clinical parameters (Medicare: odds ratio [OR], 0.81; 95% CI, 0.78-0.84; Medicaid: OR, 0.76; 95% CI, 0.73-0.79; both P <.0001) (Table 4). Other predictors of a lower chance of receiving a transplant included older age, Hispanic ethnicity, being on life support, having hepatic encephalopathy, and history of a prior liver or nonliver transplantation (P <.001). Factors independently associated with a higher chance of receiving a transplant were listing in a high-volume center, male gender, having a college degree, having listing status 1 (the most medically urgent candidates), having HCC, having ascites, having bacterial peritonitis, having a higher MELD score, and being on dialysis (all P <.02) (Table 4). Of the most common diagnostic groups (prevalence >3%), having NASH or primary biliary cirrhosis was associated with a higher chance of receiving a transplant with reference to hepatitis C, whereas patients with alcoholic cirrhosis had a lower chance of eventually receiving a transplant (all P <.0001) (Table 4).

Payer and outcomes data were available for 99,531 liver transplant recipients. Clinicodemographic presentation of transplant recipients was similar to that of wait-listed candidates. Posttransplant noncompliance with medical treatment as reported in SRTR follow-up data was substantially higher in the Medicaid group at 11.2% versus 5.2% in private and 5.8% in Medicare groups (P <.0001). Posttransplant survival was the highest in the privately insured group (mortality: 10.8% at 1 year, 18.6% at 3 years, 24.7% at 5 years) followed by Medicaid (mortality: 12.2%, 21.5%, and 28.7%, respectively) and the lowest in the Medicare group (mortality: 13.0%, 23.1%, and 31.1%, respectively). Over time, mortality similarly and significantly decreased in all payer groups (Kendall τ <—0.54; all P <.01) (eAppendix Figure [eAppendix available at ajmc.com]).

In multivariate survival analysis, both Medicare and Medicaid insurance were associated with increased posttransplant mortality after adjustment for age and other clinicodemographic parameters and the year of transplantation (Medicare: adjusted hazard ratio [aHR], 1.24; 95% CI, 1.17-1.31; Medicaid: aHR, 1.14; 95% CI, 1.06-1.21; both P <.001). Other significant predictors of higher posttransplant mortality were an earlier year of transplantation, older age, being black, being on life support, higher MELD score, pretransplant diabetes, retransplant, noncompliance with posttransplant medical treatment in posttransplant follow-up data, and pretransplant HCC (all P <.01) (eAppendix Table). On the other hand, there was no association of payer type with posttransplant graft loss risk (both Medicare and Medicaid P >.30).


In this study, we summarized the outcomes of patients wait-listed for liver transplantation by insurance type in the United States. Because SRTR data include all candidates listed in the United States, the sample is nationally representative, allowing us to draw population-based conclusions. The main finding of the study is that, compared with privately insured patients, patients with Medicare and Medicaid had poorer wait-list outcomes, such as lower transplant and higher dropout rates, even after adjustment for age and other demographic factors, education, the year of listing, listing diagnoses, MELD scores, and a number of other clinical risk factors and comorbidities. In particular, although patients on Medicare were expectedly older than the rest of the cohort, age and age-related comorbidities such as diabetes could not explain the reported difference in outcomes. Similarly, patients on Medicaid had the highest average MELD score and the highest prevalence of alcoholic cirrhosis, but again, these factors alone did not explain the observed outcomes distribution. The exact reasons for this require further study. Possible factors not assessed in our study would include income level, psychiatric and other comorbidities, continuity of access to healthcare and of insurance coverage both pre- and post listing and transplantation, and center- and donor-related factors; all those factors may additionally affect both wait-list and posttransplant outcomes. Interestingly, the higher transplant rate in patients with private insurance was accompanied by longer wait times (ie, these patients are able to survive longer while waiting); notably, longer survival alone would improve chances of receiving a transplant. Higher-quality management while wait-listed, possibly owing to easier access to healthcare providers, procedures, or medications, or other clinical factors not measured in our study, may account for this observation.

In patients who eventually received a transplant, the difference in posttransplant mortality is similarly pronounced and could not be explained by age or recorded comorbidities or noncompliance with treatment in posttransplant follow-up data despite substantial confounding of the outcome by those factors. On the other hand, there was no similar association of the type of insurance with the risk of graft loss. This indirectly suggests that factors outside of posttransplant care are responsible for the observed mortality disparity. Given the lack of more detailed clinical and sociodemographic data, we recommend that wait-listed and posttransplant patients with publicly sponsored insurance should be considered as being at higher risk and carefully followed for any socioclinical factors that could potentially be addressed.


An important limitation of our study is the lack of systematic quality control in SRTR data; there is a chance of inconsistencies of medical history tracking across different transplant centers and changes in recording practices and diagnostic criteria with time. In addition, there was a notable proportion of missing or incomplete data, predominantly in the earliest and the most recent study years, which might have caused an unknown systematic bias. The duration of follow-up might be insufficient to track the most recent trends in outcomes following ongoing changes in US healthcare legislation, such as expansion of Medicaid, which started in 2014 in some states.


The outcomes of patients in need of a liver transplant and those who have received a liver transplant are poorer in those who have publicly sponsored insurance. Because the proportion of such patients is steadily increasing, providers may need to consider more vigilant management and follow-up of these patients to optimize their outcomes. Further studies are required to determine the exact reasons for the reported outcome disparities.


The data reported here have been supplied by the Minneapolis Medical Research Foundation as the contractor for the Scientific Registry of Transplant Recipients (SRTR). The interpretation and reporting of these data are the responsibility of the author(s) and in no way should be seen as an official policy of or interpretation by the SRTR or the US government.Author Affiliations: Center for Outcomes Research in Liver Diseases (MS, IY), Washington, DC; Betty and Guy Beatty Center for Integrated Research, Inova Health System (MS, AM, CV, ZMY), Falls Church, VA; Division of Gastroenterology, Johns Hopkins University (SAQ), Baltimore, MD; Center for Liver Diseases, Department of Medicine, Inova Fairfax Hospital (AM, CV, ZMY), Falls Church, VA.

Source of Funding: This study was supported by the Beatty Liver and Obesity Research Fund, Liver Outcomes Research Fund (Inova Health System, Falls Church, VA), and Center for Outcomes Research in Liver Disease (Washington, DC).

Author Disclosures: Dr Stepanova and Mr Younossi are employed by the Center for Outcomes Research in Liver Disease. Dr Al Qahtani is employed by The Johns Hopkins Hospital. Drs Mishra, Venkatesan, and Younossi are employed by Inova Health System.

Authorship Information: Concept and design (SAQ, AM, CV, ZMY); acquisition of data (MS); analysis and interpretation of data (MS); drafting of the manuscript (MS); critical revision of the manuscript for important intellectual content (MS, SAQ, AM, IY, CV, ZMY); statistical analysis (MS); obtaining funding (IY, ZMY); administrative, technical, or logistic support (IY); and supervision (SAQ, AM, CV, ZMY).

Address Correspondence to: Zobair M. Younossi, MD, MPH, Betty and Guy Beatty Center for Integrated Research, Claude Moore Health Education and Research Building, 3300 Gallows Rd, Falls Church, VA 22042. Email: zobair.younossi@inova.org.REFERENCES

1. Kamath PS, Wiesner RH, Malinchoc M, et al. A model to predict survival in patients with end-stage liver disease. Hepatology. 2001;33(2):464-470. doi: 10.1053/jhep.2001.22172.

2. Freeman RB, Wiesner RH, Edwards E, Harper A, Merion R, Wolfe R; United Network for Organ Sharing Organ Procurement and Transplantation Network Liver and Transplantation Committee. Results of the first year of the new liver allocation plan. Liver Transpl. 2004;10(1):7-15. doi: 10.1002/lt.20024.

3. Volk ML, Lok AS, Pelletier SJ, Ubel PA, Hayward RA. Impact of the model for end-stage liver disease allocation policy on the use of high-risk organs for liver transplantation. Gastroenterology. 2008;135(5):1568-1574. doi: 10.1053/j.gastro.2008.08.003.

4. Kim WR, Lake JR, Smith JM, et al. OPTN/SRTR 2016 annual data report: liver. Am J Transplant. 2018;18(suppl 1):172-253. doi: 10.1111/ajt.14559.

5. Trieu JA, Bilal M, Hmoud B. Factors associated with waiting time on the liver transplant list: an analysis of the United Network for Organ Sharing (UNOS) database. Ann Gastroenterol. 2018;31(1):84-89. doi: 10.20524/aog.2017.0217.

6. Younossi ZM, Stepanova M, Saab S, et al. The impact of type 2 diabetes and obesity on the long-term outcomes of more than 85,000 liver transplant recipients in the US. Aliment Pharmacol Ther. 2014;40(6):686-694. doi: 10.1111/apt.12881.

7. Stepanova M, Sayiner M, de Avila L, Younoszai Z, Racila A, Younossi ZM. Long-term outcomes of liver transplantation in patients with hepatitis C infection are not affected by HCV positivity of a donor. BMC Gastroenterol. 2016;16(1):137. doi: 10.1186/s12876-016-0551-z.

8. Wong RJ, Chou C, Bonham CA, Concepcion W, Esquivel CO, Ahmed A. Improved survival outcomes in patients with non-alcoholic steatohepatitis and alcoholic liver disease following liver transplantation: an analysis of 2002-2012 United Network for Organ Sharing data. Clin Transplant. 2014;28(6):713-721. doi: 10.1111/ctr.12364.

9. Yoo HY, Thuluvath PJ. Outcome of liver transplantation in adult recipients: influence of neighborhood income, education, and insurance. Liver Transpl. 2004;10(2):235-243. doi: 10.1002/lt.20069.

10. Kemmer N, Zacharias V, Kaiser TE, Neff GW. Access to liver transplantation in the MELD era: role of ethnicity and insurance. Dig Dis Sci. 2009;54(8):1794-1797. doi: 10.1007/s10620-008-0567-5.

11. Peluso H, Abougergi MS, Caffrey J. Impact of primary payer status on outcomes among patients with burn injury: a nationwide analysis. Burns. 2018;44(8):1973-1981. doi: 10.1016/j.burns.2018.06.009.

12. Brubaker WD, Dallas KB, Elliott CS, et al. Payer type, race/ethnicity, and the timing of surgical management of urinary stone disease. J Endourol. 2019;33(2):152-158. doi: 10.1089/end.2018.0614.

13. Pitman M, Korets R, Kates M, Hruby GW, McKiernan JM. Socioeconomic and clinical factors influence the interval between positive prostate biopsy and radical prostatectomy. Urology. 2012;80(5):1027-1032. doi: 10.1016/j.urology.2012.01.008.

14. Elsayed G, McClugage SG, Erwood MS, et al. Association between payer status and patient-reported outcomes in adult patients with lumbar spinal stenosis treated with decompression surgery. J Neurosurg Spine. 2018;30(2):198-210. doi: 10.3171/2018.7.SPINE18294.

15. Emani S, Tumin D, Foraker RE, Hayes D Jr, Smith SA. Impact of insurance status on heart transplant wait-list mortality for patients with left ventricular assist devices. Clin Transplant. 2017;31(2):e12875. doi: 10.1111/ctr.12875.

16. Chen Z, Gao W, Pu L, et al. Impact of insurance status on the survival of gallbladder cancer patients. Oncotarget. 2017;8(31):51663-51674. doi: 10.18632/oncotarget.18381.

17. DuBay DA, MacLennan PA, Reed RD, et al. Insurance type and solid organ transplantation outcomes: a historical perspective on how Medicaid expansion might impact transplantation outcomes. J Am Coll Surg. 2016;223(4):611-620.e4. doi: 10.1016/j.jamcollsurg.2016.07.004.

18. SRTR risk adjustment model documentation: waiting list models. Scientific Registry of Transplant Recipients website. www.srtr.org/reports-tools/waiting-list. Accessed April 23, 2019.

19. Axelrod DA, Dzebisashvili N, Schnitzler MA, et al. The interplay of socioeconomic status, distance to center, and interdonor service area travel on kidney transplant access and outcomes. Clin J Am Soc Nephrol. 2010;5(12):2276-2288. doi: 10.2215/CJN.04940610.

20. Sandhu GS, Khattak M, Pavlakis M, et al. Recipient’s unemployment restricts access to renal transplantation. Clin Transplant. 2013;27(4):598-606. doi: 10.1111/ctr.12177.

21. Gutin L, Yao F, Dodge JL, Grab J, Mehta N. Comparison of liver transplant wait-list outcomes among patients with hepatocellular carcinoma with public vs private medical insurance. JAMA Netw Open. 2019;2(8):e1910326. doi: 10.1001/jamanetworkopen.2019.10326.

22. SRTR 1811 public SAFs data dictionary. Scientific Registry of Transplant Recipients website. srtr.org/requesting-srtr-data/saf-data-dictionary. Accessed November 13, 2019.

23. Understanding HIV HBV HCV risks from increased risk donors. Organ Procurement and Transplantation Network website. optn.transplant.hrsa.gov/resources/guidance/understanding-hiv-hbv-hcv-risks-from-increased-risk-donors. Accessed November 13, 2019.