Introduction

Although kidney transplantation (KT) is the optimal treatment for patients with kidney failure, there are well-documented barriers that prevent otherwise eligible patients from obtaining KT (Alexander & Sehgal, 2001; Schold et al., 2021). These barriers occur throughout the KT process including access to referral, completion of pre-transplant evaluation, being wait-listed, and receipt of KT. These multiple steps, and potential associated barriers, contribute to long-standing racial/ethnic and socioeconomic disparities in KT receipt (Navaneethan & Singh, 2006; Patzer et al., 2012; Wesselman et al., 2021). The first step following referral is initiating a kidney transplant evaluation (KTE), which traditionally requires many tests conducted by multiple specialists and several follow-up visits. (Crenesse-Cozien et al., 2019) A majority of patients referred for KT who begin the evaluation process do not make it through to receipt of transplant, suggesting significant barriers navigating the KT process following a referral (Kucirka et al., 2015; Patzer et al., 2015). Several cross-sectional and retrospective studies identified factors associated with those never attending a KTE appointment; these include perceived medical disqualifications, fear about transplant, logistical barriers (e.g., lack of transportation), and financial concerns (Dageforde et al., 2015; Kazley et al., 2012; Kucirka et al., 2015).

Interventions addressing clinic non-attendance in medical settings often focus on clinic led efforts including overbooking and appointment reminders (LaGanga & Lawrence, 2007; Parikh et al., 2010). For patients seeking KT, efforts to streamline the KTE process into a single initial visit with multiple providers instead of individual appointments are designed, in part, to address non-attendance (Bornemann et al., 2017). Even with these interventions, there could be multiple medical and non-medical factors, including social determinants of health, that make it difficult for patients to begin the KT evaluation process (Crenesse-Cozien et al., 2019). Given that existing studies have relied on obtaining retrospective patient reports about KTE attendance (Dageforde et al., 2015), it is important to collect prospective data to be able to determine which factors predict KTE non-attendance. A better understanding of the bio-psycho-social factors that prospectively predict which patients do not initiate KTE could better inform healthcare delivery interventions that increase access to care. In this study, we aim to identify the frequency of KTE clinic non-attendance (e.g. never presenting to KTE) and characterize the demographic, medical, and socio-cultural factors that predict KTE clinic non-attendance.

Methods and Measures

Study Design and Procedures

We recruited patients who were scheduled for KTE at the Starzl Transplant Institute at the University of Pittsburgh Medical Center (UPMC) between May, 2015 and June, 2018. Since 2015, UPMC has performed the fifth largest number of KT procedures of the 42 transplant centers in UNOS Region Two). (OPTN Organ Procurement and Transplantation Network, n.d.) We conducted a research study interview with these patients to assess the relationship of demographic, medical, and sociocultural facts with subsequent KTE non-attendance. Participants completed their KTE appointment an average of 33 days after the study interview. However, the time between the study interview and the KTE appointment varied based on clinic wait times, cancelations and rescheduling. The majority of the 45-min structured interviews were conducted by telephone (n = 1073; 96%). Another 44 interviews (4%) were collected with paper versions with respect for participant preference. This interview was part of a larger longitudinal study that included a quasi-experimental design to determine the efficacy of a fast-track KTE process (Bornemann et al., 2017).

Study Sample

Patient inclusion criteria were: (1) scheduled for a KT appointment; (2); English speaking; (3) 18 or older; (4) no history of KT and; (5) not accepted for KT at another transplant center. During the recruitment timeframe, 1472 people were eligible for the study, 1315 consented to participate (89% consent rate), and 1288 completed the pre-transplant interview. This study includes data from 1119 of the total 1288 sample; those who completed the study interview after their KTE (n = 67) were excluded as were those who reported race as other than Black or White (n = 102) due to small numbers (7.9%) and significant heterogeneity within the “other” group. Assessment of worry about post-KT outcomes (see Predictors section) was added to the study interview after the start of data collection.

Predictors

Potential predictors included demographic (e.g., income, education), medical (e.g., dialysis, co-morbidities), transplant knowledge, cultural (e.g., medical mistrust), and psychosocial factors (e.g., social support, depression), as well as worry about post-KT outcomes. See Table 1 for a full description of potential predictors of KTE clinic non-attendance. We included all the factors assessed in the interview from the parent study as potential predictors of clinic non-attendance (Fig. 1).

Table 1 Description of study variables
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Fig. 1
figure 1

Forest plot of predictors of clinic non-attendance in adjusted model

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Outcome Variables

The primary outcome variable in this study was KTE clinic non-attendance, defined as a patient referred to and scheduled for initial KTE who never attended the initial appointment or any re-scheduled appointments during the study period. This includes patients who were no-shows, canceled, and/or re-scheduled appointments in any combination but ultimately never attended a clinic appointment by the end of the study period in August 2019.

Statistical Analyses

We performed descriptive analyses of baseline characteristics using median and interquartile range for numerical variables, and frequency and percentage for categorical variables. Using Wilcoxon Rank Sum Tests, we compared medians of continuous variables between patients who attended an initial KTE appointment and patients who did not attend an initial KTE appointment. For categorical variables, we used Chi-Square Tests (or Fisher’s Exact Test when expected cell sizes were very small) to assess the association between KTE non-attendance and each categorical variable.

To examine the relationship between baseline characteristics and clinic non-attendance, we performed bivariate logistic regression analyses, modeling each baseline characteristic with clinic non-attendance. We then assessed variables with p values less than .10 [or significant odds ratios (OR < .5 or OR > 2)] for multicollinearity. After verifying that none of the statistically significant predictors exhibited multicollinearity, we entered these variables into a final multiple logistic regression model to account for potential demographic, medical, psychosocial, cultural, and transplant-specific predictors of KTE non-attendance. The multiple regression analysis used case-wise deletion for missing data to ensure that all factors were equally weighted. We also conducted a sensitivity analysis using a multiple regression model that excluded the variable that caused a majority of the case-wise missingness, and found the results to be virtually identical (results listed in Supplementary Table). We performed all data analyses in SAS.

Results

In Table 2, we detail the baseline characteristics and outcomes of study participants who completed the initial interview (n = 1119). Because we found virtually no difference between mode of interview completion (phone vs paper), we present all results across the complete cohort.Footnote 1 The window for attendance for patients enrolled at the end of the data collection period (August 2019) was between one and four years. The overwhelming majority (95%) of those who attended clinic did so within four months of survey completion. The cohort included those who subsequently attended an initial KTE appointment (n = 977), and those who never attended an initial KTE (n = 142). Patients who attended KTE were more likely to be married, had a higher number of potential donors in their social network, and a higher frequency of having identified potential living donor (all p values ≤ .05) compared to the group of patients who did not attend KTE. Among patients who did not attend KTE, there was a higher frequency of being on dialysis, higher levels of perceived racism and medical mistrust, higher frequency of experienced discrimination, lower social support, higher frequency of moderate or greater depression, and a higher likelihood of reporting worry that KT could be harmful.

Table 2 Baseline and comparison of characteristics and outcomes of complete KTFT cohort and subgroups
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The univariable logistic regression, summarized in Supplementary Table 1, yielded the ten variables individually associated with KTE non-attendance. Because none of these variables exhibited high variance inflation factors nor high inter-correlations, we used all of them in the final multiple logistic regression model presented in Table 3. The multiple logistic regression model (Table 3) showed that being on dialysis was associated with 76% higher odds of clinic non-attendance [OR (95% CI) 1.76 (1.10–2.82), p value = .02]. Trending variables included not having a living donor [OR (95% CI) 1.48 (.98–2.22), p value = .06] and experiencing discrimination in healthcare settings [OR (95% CI) 1.42 (.94–2.16), p value = .09]. To explore why dialysis may have been the only significant predictor in the multivariable model, we conducted a follow-up analysis of demographic differences between those on dialysis and not (see Supplemental Table S1). We found that patients who were on dialysis were more likely to be Black, unmarried, insured by public insurance only, have income below federal poverty level, and a lower status occupation.

Table 3 Adjusted odds ratios for predictors of clinic non-attendance
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Discussion

To our knowledge, this is the first prospective study of patients referred to and scheduled for KTE who never attended an evaluation appointment. More than ten percent of those in our sample never attended their scheduled KTE appointment. After comparing multiple individually significant predictors, dialysis status was the sole statistically significant predictor of KTE non-attendance. These results (other than our finding that race/ethnicity was non-significant in all of our analyses) are broadly consistent with previous cross-sectional pilot studies, and may have important implications for increasing access to KT (Dageforde et al., 2015).

A strength of this study is the prospective collection of predictors that are richer than could be obtained with medical record review alone. By having the research team call patients ahead of their appointment to conduct the baseline interview, patients received at least one and sometimes several additional reminders of their initial KTE appointment. Although this approach may be perceived as a limitation with the unintended consequence of reducing non-attendance, we believe this approach only served to underestimate non-attendance. We hypothesize that without this approach, non-attendance rates would be even higher in our sample, matching results from other studies of clinic non-attendance (Parikh et al., 2010).

Even when much of the KTE process is streamlined into a single visit as was the case in this sample, there are unique challenges for dialysis patients scheduled to attend KTE. For those with kidney failure, there are well-documented deleterious physical and psychological side effects associated with being on dialysis (Unruh et al., 2008). Furthermore, the experience of traditional thrice-weekly hemodialysis is logistically burdensome, making it difficult for patients to attend additional medical appointments on days between dialysis sessions (Tong et al., 2017). The combination of these medical, psychological, and logistical burdens would likely lead to greater difficulty in attending a scheduled KTE. Importantly, the effect of being on dialysis is so strong, that it even eclipsed the effect of race/ethnicity, a factor often found significant in research on non-attendance (Alexander & Sehgal, 2001; Navaneethan & Singh, 2006; Schold et al., 2021). We believe this finding supports previous work arguing that race/ethnicity is a proxy of other social determinants of health (Patzer et al., 2012, 2015; Wesselman et al., 2021).

Early referral to KTE prior to initiating dialysis (i.e., preemptive listing) may be an important intervention in increasing KT access. As with other transplant outcomes, racial and ethnic disparities persist for those who are referred to and approved for listing prior to initiating dialysis (King et al., 2019). Despite changes to the Kidney Allocation System (KAS), the proportion of patients who have been on dialysis for years without transplant remains high (Kadatz et al., 2022). A follow-up analysis of demographic differences between those on dialysis versus those not on dialysis in our study yielded results consistent with well-known disparities between those who are pre-emptively referred for transplant and those referred after initiating dialysis. (King et al., 2019) Patients who were on dialysis were more likely to be Black, unmarried, and have lower SES (public insurance only, income below federal poverty level, lower status occupation). In this way dialysis status, which is strongly influenced by social determinants of health, eclipsed other potential predictors of attendance. Those who are referred for KTE prior to initiating dialysis may have other advantages that help ensure they are moving along the process. Advantages may include a greater likelihood of having a living donor, having a proactive medical team, and having greater access to resources including choice of healthcare facility.

The findings from our study suggest several implications for dialysis and transplant teams, working to improve KT access to increase equity. Clinical psychologists, already established as part of transplant teams in the KTE screening process, could play an important upstream role on dialysis units in improving the quality of life of those on dialysis through addressing barriers to transplant. The use of psychological interventions for those with end-stage kidney disease is an active area of research which has demonstrated feasibility, acceptability and modest improvement in dialysis patient mental health symptoms (Jakubowski et al., 2020; Mehrotra et al., 2019). The work of clinical psychology within dialysis units could be extended to screen for and target patient ambivalence related to the transplant process. Ambivalence is a well-documented part of medical decision-making and identified as relevant to patient behavior in previous qualitative analyses of those awaiting transplant (Tong et al., 2015; Venkataraman & Kendrick, 2020). Several variables in the current study may be considered proxy measures to ambivalence of initiating the KT process. These included expressing transplant worry (i.e., “I worry that transplant will do more harm than good”), not having a potential living donor, and having an experience of discrimination in health care. Expressing transplant worry may most directly reflect patient’s ambivalence related to possible negative outcomes of a KT. Those who have not initiated discussions with potential living donors, a possible behavioral reflection of ambivalence, may be less ready to initiate the KTE process (Waterman et al., 2006). Finally, having an experience of discrimination in healthcare, a cultural contributor to ambivalence regarding healthcare utilization, may also contribute to reluctance of patients to initiate the KTE process. Although we found that these variables were not significant in our combined multi-variable model, they did matter when evaluated individually, and thus serve as potential factors to explore in subsequent research.

The association of patient ambivalence with several factors related to KTE non-attendance also indicates the potential utility of developing brief screeners for transplant ambivalence. Psychological screening for those on dialysis could include assessment of biopsychosocial factors, including ambivalence, that might affect influence the trajectory of KT outcomes. Identifying ambivalence in other health domains has been useful in improving access to care (e.g., medication adherence, see (Pringle et al., 2014)) and could be used to identify those at risk of non-attendance after referral for KTE. Furthermore, clinical psychologists as well as other medical providers may consider behavioral interventions, especially motivational Interviewing (MI), which have been successfully used to address behavior change in patients with end-stage kidney disease (García-Llana et al., 2014). MI, which can be facilitated by medical and mental health providers, as well as MI-trained peers, may be particularly useful for addressing KT ambivalence (Andersen et al., 2022; Sullivan et al., 2012).

Finally, given that there are multiple reasons for non-attendance at the patient, provider, and system level, there are also several potential interventions to improve patient access to the transplant clinic (Venkataraman & Kendrick, 2020). To address logistical challenges of scheduling dialysis patients for evaluation, working to change where and how kidney transplant evaluations are performed may be an appropriate target (Axelrod et al., 2010). There has been evidence for tele-health access to aid in facilitating initial screening visits ultimately leading to reduced time to complete a full evaluation for transplant (Concepcion & Forbes, 2020; Forbes et al., 2018). The acceleration of telehealth access during the public health crisis of COVID-19 may serve to increase these opportunities (Yadav et al., 2020).

Limitations

Although the current study had a number of strengths including a prospective design, a racially diverse sample, and a very high survey completion rate (1288/1315, 98%), there are also several limitations to consider. There may have been relevant medical data related to calculating medical co-morbidity scores that were not included as part of the EMR at the study hospital. There was also a significant minority of patients administered the post-KT worry questions who did not answer a question related to concerns about affording future transplant costs; we note this limitation as it may reflect either true missingness or an inability to answer this question if they did not know what future costs would be. Another important concern was that we found several predictors that were associated with KTE non-attendance, yet none were uniquely predictive in the multiple logistic regression model (although some trended toward significance). This result tells us that each of these variables is important individually, however when considered together they explained factors common to non-attenders. When considering ways to increase attendance, clinics should consider focusing on multiple factors, but this study cannot specifically recommend one predictor more than another, other than being on dialysis. Finally, although there was a racially diverse sample reflective of the transplant center’s location, this was a single-site study that may not be generalizable to all patients with kidney failure.

Conclusion

Increasing access to KT begins with making sure that those referred for KT evaluation, attend their initial evaluation appointment. Our study prospectively identified salient factors in predicting those who did not end up attending an initial evaluation appointment and thus never initiated the KT process. Being on dialysis was the single most important factor after considering multiple potential predictors, all of which predict KTE non-attendance individually. Because many patients on dialysis face medical and logistical challenges in attending appointments, there are novel opportunities to make the existing system better fit the needs of those being served. There may also be utility in developing brief screeners for transplant ambivalence and using behavioral interventions within dialysis clinics to address important factors impacting patient behavior and clinic resources. Ultimately, increasing equity and KT access to care will take a multilevel approach to address a significant public health need.