What drives transplant waitlisting disparities?

All potential transplant candidates undergo medical and psychosocial evaluations, which are crucial in determining whether they can get a transplant. The latter are meant to ensure that a patient has adequate social support and is committed to following the recommendations of their medical team. Psychosocial evaluations also consider a patient’s history of misusing alcohol or other substances, as well as factors related to their mental health.

While this information is important to transplant success, psychosocial evaluations, like other measures in the transplant process, can lead to people of color facing worse outcomes. We asked Dr. Marina Serper, MD, MS to tell us more and to share the findings of her recent study published in the American Journal of Transplantation.

Business Could you describe some basic facts about psychosocial evaluations?

There is no gold standard for psychosocial evaluations, but it is generally agreed that they should be done in accordance with an internally consistent process that helps the transplant team decide whether a patient is a good transplant candidate.

In many transplant programs in the U.S., the Stanford Integrated Psychosocial Assessment for Transplantation (SIPAT), a questionnaire designed to assess psychosocial risk, is used as part of this process. If patients are found to be at high risk for complications from their answers, they may not be put on the waitlist to receive a transplant, even if they are good candidates physically. Such nonmedical reasons are important and may be valid, but also can introduce bias into the decision-making process.

However, there is little information available nationally on how many candidates are being declined for psychosocial reasons. We do know that transplant center behavior varies widely in what is considered an acceptable level of medical and psychosocial risk.

One factor driving this difference is program size. All transplant hospitals report quality data to the United Network for Organ Sharing (UNOS), but smaller programs are more negatively impacted by a single adverse outcome, which makes them less likely to take on candidates they believe to be riskier.

Another factor driving differences in behavior is competition. Programs in highly competitive areas like the Northeast, which have several transplant centers for patients to choose from, may make different decisions on who to list for transplant than those programs that dominate a given area.

You not only found that Black patients have higher SIPAT scores on average, but they were also more likely not to be waitlisted than comparable white patients. Is race the only difference? Did this surprise you?



We also found that Black patients were more likely to be on Medicaid, to have lower levels of educational attainment, and to live in areas with poorer community health relative to white patients. These differences have unfortunately been previously shown in other settings. In our research, we highlight that upstream determinants of health affect transplant access, which is life-saving for liver disease, and therefore further exacerbating health care disparities.

Business What is unique about your study? How does it break new ground?

Transplant centers are mandated to report data to the Scientific Registry of Transplant Recipients (SRTR) while a patient is on the waitlist or after they have received a transplant, but there are no reporting requirements that track which patients are able to access the waitlist in the first place. We were able to report on a single center’s data over several years to gain information on which patients were waitlisted, representing an important step in filling this knowledge gap.

Business How do you expect that your results would have been different at a smaller center, or in a rural location?

We would expect to see similarities in the type of psychosocial assessments that transplant centers employ and the ways in which transplant centers make decisions on waitlisting. The center that our study looked at was not only large, but also diverse, and it had dedicated resources to improving health equity. I anticipate that if we were to look nationally, we would uncover even more disparities among institutions that did not have an intentional focus on equity.

Business What are the biggest weaknesses in SIPAT scores and in the waitlisting process?

SIPAT scores are supposed to aid centers in being more objective. However, many of the items on the SIPAT are open to interpretation, and there are not agreed upon cutoffs that guide behavior at our center. My team is working on another project looking at the SIPAT tool to see which areas can be improved.

Importantly, issues of implicit bias are not resolved by the SIPAT. Transplant centers must be introspective and examine their decision-making processes.

Business Your prior work shows that higher SIPAT scores are associated with worse post-transplant outcomes. How do we fairly represent Black patients in transplants while ensuring high rates of success?

There are many things transplant centers can do, from providing enhanced patient navigation services, to peer mentoring, to assistance with transportation and copays. By proactively addressing financial, medical, and psychosocial barriers, centers can improve adherence, as we demonstrate in our ongoing National Institutes of Health (NIH)-funded trial.

Transplant centers in particular are well poised to roll out interventions to support patients, because they often have greater resources than other subspecialty practices.

Business What can clinicians do to make the disparities smaller? What are your recommendations for policymakers?

The first step clinicians must take is to recognize that health disparities exist. The second step is to ask what role their center is playing in reinforcing them and to brainstorm how they can reduce them by providing additional support. Group behavior and implicit bias are hard to discuss and disentangle but also have to be tackled.

From a policy standpoint, a good starting point would be to follow the example of the United States Renal Data System (USRDS). This collaborative network funded by the NIH collects information on the population prevalence of end stage renal disease and the proportion of patients on dialysis who have been added to the transplant waitlist. This type of detailed population data does not currently exist for either cirrhosis or primary liver cancer, which are both major indications for liver transplantation.

Gathering this information is a major prerequisite to determining the scope of the problem to tackle health care disparities in liver transplants.