It is well recognized that kidney transplantation is the best outcome for most people with end-stage kidney disease; however, not everyone who would benefit from a transplant will receive one. Access to a kidney transplant is limited by the availability of donor organs; however, there are also a range of medical and nonmedical barriers that limit individual access.1 Nonmedical barriers include timeliness of referral, distance to transplant centers, referral patterns, cost structure, and type of insurance.2,3 These barriers lead to inequities in both access to and outcomes after transplantation in particular for marginalized groups and those of lower socioeconomic status.2-4 Ensuring equitable and timely access to kidney transplants requires multifactorial approaches to address common barriers as well as those specific to individual healthcare providers and transplant centers.
In this issue, Forbes et al5 provide an example of the nuances of addressing timely and fair access to transplantation within a single service provider, namely, the US Department of Veteran Affairs (VA) centralized healthcare system. Previous evaluations have suggested that individuals insured through the VA as well as Medicare and Medicaid patients, were less likely to receive a kidney transplant than privately insured patients.6 The rural locations of almost half of the VA patients presents difficulties in provision of healthcare, including kidney transplants, and likely contributes to both inefficiencies and disparities in access to transplantation. As a consequence, the VA have become the largest adopter of telehealth in the United States. Forbes et al present the findings of a retrospective evaluation of the use of video conferencing in the consultation process leading to approval or otherwise for waitlisting of VA patients for a kidney transplant. They examine the costs and time from initial referral to a decision to waitlist or not with video conferencing compared with the usual practice of in-person evaluation only. Because in-person evaluation is a requirement for the final approval to be waitlisted, video conferencing is used to prescreen patients before the in-person evaluation. The analysis presented by the authors concludes that videoconferencing is both viable and would lead to cost savings for the VA. The cost saving for the VA from referral to a waitlisting decision with inclusion of video conferencing is estimated to be in the order of US $500 per patient; however, the actual cost savings are uncertain given the retrospective evaluation and uncertainty in selection of patients for screening by video conferencing. Compared with the in-person only patients, the video conferencing group included patients who were on average older, had a higher body mass index, and less mobile with higher prevalence of diabetes. As such, video conferencing was used to prescreen a broader cross-section of patients than selected for in-person evaluation without the use of video conferencing. Of the 143 screened by video conferencing, 50% were approved for in-person evaluation. Of these, after in-person evaluation, the proportion of patients who were approved and not approved for waitlisting was essentially the same as the in-person only group. One interpretation of the data is that the approach used to select patients for in-person only evaluation maybe as effective as selection using video conferencing. Because video conferencing should not influence the costs of in-person evaluation, the basis for the cost comparison remains unclear.
Despite the uncertainties in the cost comparisons, the analysis by Forbes et al provides data to suggest the possibility of improvement in access to the waitlist for more distant VA patients prescreened by video conferencing. Individuals in the in-person only evaluation group had an average round trip of 932 miles compared with patients referred after video conferencing who had an average round trip of 1071 miles. This observation needs to be tempered by this being a retrospective study. As noted by Forbes et al, the evaluation did not address costs for patients including time off work and lost wages, both of which may also influence access to transplantation for VA patients. Receiving a kidney transplant is a multistep process with the potential for inequities to arise at each step,4 and the study by Forbes et al has examined processes aimed at improving access for one step. Indigenous Australians are less likely to receive a transplant compared with non-Indigenous Australians first because they are less likely to be waitlisted and second, once waitlisted they have longer waiting-times compared to non-Indigenous Australians.7 In the United States, there is evidence that after waitlisting, lower socioeconomic and more marginalized groups are more likely to be allocated and transplanted with an extended criteria deceased donor organ, suggesting an albeit unintended disparity in allocation of deceased donor organs for patients on the waitlist.8
As noted by Gill and Johnston,9 evaluating disparities in access is not straight forward because there are many interactions between health service, geographic locations, ethnicity, and biological factors. The question of how to provide fair and equitable access to a kidney transplant is therefore complex particularly given the increasing demand for transplants and the need to balance efficiency and equity. It is therefore imperative that the evaluation of practice changes, such as the use of telehealth in the VA centralized system, consider not only efficiency but also the extent to which the intervention redresses, minimizes, or exacerbates inequities. This in turn requires consideration of all steps of transplantation from evaluation for waitlisting to the allocation of donor organs.
1. Vamos EP, Novak M, Mucsi I. Non-medical factors influencing access to renal transplantation. Int Urol Nephrol
2. Browne T, Amamoo A, Patzer RE, et al. Everybody needs a cheerleader to get a kidney transplant: a qualitative study of the patient barriers and facilitators to kidney transplantation in the Southeastern United States. BMC Nephrol
3. Grace BS, Clayton P, Cass A, et al. Socio-economic status and incidence of renal replacement therapy: a registry study of Australian patients. Nephrol Dial Transplant
4. Patzer RE, Plantinga L, Krisher J, et al. Dialysis facility and network factors associated with low kidney transplantation rates among United States dialysis facilities. Am J Transplant
5. Forbes RC, Rybacki DB, Johnson TB, et al. A cost comparison for telehealth utilization in the kidney transplant waitlist evaluation process. Transplantation
6. Gill JS, Hussain S, Rose C, et al. Access to kidney transplantation among patients insured by the United States Department of Veterans Affairs. J Am Soc Nephrol
7. Yeates KE, Cass A, Sequist TD, et al. Indigenous people in Australia, Canada, New Zealand and the United States are less likely to receive renal transplantation. Kidney Int
8. Mohandas R, Casey MJ, Cook RL, et al. Racial and socioeconomic disparities in the allocation of expanded criteria donor kidneys. Clin J Am Soc Nephrol
9. Gill JS, Johnston O. Access to kidney transplantation: the limitations of our current understanding. J Nephrol