Implications of expanded medicaid eligibility for patient outcomes after liver transplantation: Caveat emptor

Potential association between public medical insurance, waitlist mortality, and utilization of living donor liver transplantation: An analysis of the Scientific Registry of Transplant Recipients

BACKGROUND

The Affordable Care Act (ACA) and subsequent Medicaid expansion has increased utilization of public health insurance. Living donor liver transplantation (LDLT) increases access to transplant and is associated with improved survival but consistently represents < 5% of LT in the United States.

STUDY DESIGN

National registry data were analyzed to evaluate the impact of insurance payor on waitlist mortality and LDLT rates at LDLT centers since implementation of the ACA.

RESULTS

Public insurance [Medicare RR 1.18 (1.13-1.22) P < .001, Medicaid RR 1.22 (1.18-1.27) P < .001], Latino ethnicity (P < .001), and lower education level (P = .02) were associated with increased waitlist mortality at LDLT centers. LDLT recipients were more likely to have private insurance (70.4% vs. 59.4% DDLT, P < .001), be Caucasian (92.1% vs. 83% DDLT, P < .001), and have post-secondary education (66.8% vs. 54.1% DDLT, P < .001). Despite 78% of LDLT centers being located in states with Medicaid expansion, there was no change in LDLT utilization among recipients with Medicaid (P = .196) or Medicare (P = .273).

CONCLUSION

Despite Medicaid expansion, registry data suggests that patients with public medical insurance may experience higher waitlist mortality and underutilize LDLT at centers offering LDLT. It is possible that Medicaid expansion has not increased access to LDLT.

County socioeconomic characteristics and pediatric renal transplantation outcomes

BACKGROUND

Existing risk adjustment models for solid organ transplantation omit socioeconomic status (SES). With limited data available on transplant candidates' SES, linkage of transplant outcomes data to geographic SES measures has been proposed. We investigate the utility of county SES for understanding differences in pediatric kidney transplantation (KTx) outcomes.

METHODS

We identified patients < 18 years of age receiving first-time KTx using United Network for Organ Sharing registry data in two eras: 2006-2010 and 2011-2015, corresponding to periods of county SES data collection. In each era, counties were ranked by 1-year rates of survival with intact graft, and by county SES score. We used Spearman correlation (ρ) to evaluate the association between county rankings on SES and transplant outcomes in each era and consistency between these measures across eras. We also evaluated the utility of county SES for improving prediction of individual KTx outcomes.

RESULTS

The analysis included 2972 children and 108 counties. County SES and transplant outcomes were not correlated in either 2006-2010 (ρ = 0.06; p = 0.525) or 2011-2015 (ρ = 0.162, p = 0.093). County SES rankings were strongly correlated between eras (ρ = 0.99, p < 0.001), whereas county rankings of transplant outcomes were not correlated between eras (ρ = 0.16, p = 0.097). Including county SES quintile in individual-level models of transplant outcomes did not improve model predictive utility.

CONCLUSIONS

Pediatric kidney transplant outcomes are unstable from period to period at the county level and are not correlated with county-level SES. Appropriate adjustment for SES disparities in transplant outcomes could require further collection of detailed individual SES data.

Change in Health Insurance Coverage After Liver Transplantation Can Be Associated with Worse Outcomes

BACKGROUND

Health insurance coverage changes for many patients after liver transplantation, but the implications of this change on long-term outcomes are unclear.

AIMS

To assess post-transplant patient and graft survival according to change in insurance coverage within 1 year of transplantation.

METHODS

We queried the United Network for Organ Sharing for patients between ages 18-64 years undergoing liver transplantation in 2002-2016. Patients surviving > 1 year were categorized by insurance coverage at transplantation and the 1-year transplant anniversary. Multivariable Cox regression characterized the association between coverage pattern and long-term patient or graft survival.

RESULTS

Among 34,487 patients in the analysis, insurance coverage patterns included continuous private coverage (58%), continuous public coverage (29%), private to public transition (8%) and public to private transition (4%). In multivariable analysis of patient survival, continuous public insurance (HR 1.29, CI 1.22, 1.37, p < 0.001), private to public transition (HR 1.17, CI 1.07, 1.28, p < 0.001), and public to private transition (HR 1.14, CI 1.00, 1.29, p = 0.044), were associated with greater mortality hazard, compared to continuous private coverage. After disaggregating public coverage by source, mortality hazard was highest for patients transitioning from private insurance to Medicaid (HR vs. continuous private coverage = 1.32; 95% CI 1.14, 1.52; p < 0.001). Similar differences by insurance category were found for death-censored graft failure.

CONCLUSION

Post-transplant transition to public insurance coverage is associated with higher risk of adverse outcomes when compared to retaining private coverage.