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Racial and economic disparities in transplant outcomes: The not-so-hidden morbidities
Article first published online: 20 DEC 2013
© 2013 American Association for the Study of Liver Diseases
Volume 20, Issue 1, pages 4–6, January 2014
How to Cite
Shemesh, E., Kleinman, L. C., Howell, E. A. and Annunziato, R. (2014), Racial and economic disparities in transplant outcomes: The not-so-hidden morbidities. Liver Transpl, 20: 4–6. doi: 10.1002/lt.23801
Eyal Shemesh is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (grant 1R01DK080740-01A209 to Eyal Shemesh), the Agency for Healthcare Research and Quality (grant U18 HS020518-01 to Lawrence Kleinman), and the National Institute of Allergy and Infectious Diseases (grant 2U01AI077810-06 to Sweet). Lawrence Kleinman is supported by the Agency for Healthcare Research and Quality (grant 1U18HS020518 to Lawrence Kleinman) and the National Center for Advancing Translational Sciences (grant UL1TR000067 to Sampson). Elizabeth Howell is supported by the National Institute of Child Health and Human Development (grant R21HD068765-01 to Elizabeth Howell), the Agency for Healthcare Research and Quality (grant 1U18HS020518 to Lawrence Kleinman), and the National Cancer Institute (grant R01 CA157176A to Bickell). Rachel Annunziato is supported by the National Institute of Diabetes and Digestive and Kidney Diseases (grant 1R01DK080740-01A209 to Eyal Shemesh).
- Issue published online: 20 DEC 2013
- Article first published online: 20 DEC 2013
- Accepted manuscript online: 29 NOV 2013 01:55AM EST
- Manuscript Accepted: 21 NOV 2013
- Manuscript Received: 20 NOV 2013
The Institute of Medicine has noted that equity is fundamental to the quality of health care. In this issue of Liver Transplantation, Thammana et al. present us with an important and challenging article. They have undertaken careful analyses to document racial/ethnic inequities in liver transplant outcomes. As with any empirical analysis, the optimal conclusion is related both to the methods and to the underlying conceptual frame. This article reports differences in outcomes and shows that several variables may attenuate the magnitude of such differences. How best should we understand this important contribution?
In this article, Thammana et al. address disparate outcomes. Their focus is not potential differences in the actual provision of medical care. They do explore other covariates in their very careful analysis of survival (graft survival and all-cause mortality) for pediatric and young adult liver transplant recipients at 1 center in the state of Georgia. For reasons of sample size and clarity, using retrospective chart analyses, the study team used 3 broad categories for race: black, white, and other. The study's primary finding—white children have better outcomes than black children or children of other races—is an all too familiar and yet still deeply disturbing observation. This finding is not surprising: as the authors point out, in the United States, infant mortality rates and mortality rates across the lifespan are significantly higher for blacks versus whites.
The World Health Organization defines disparities as “differences in health which are not only unnecessary and avoidable but, in addition, are considered unfair and unjust.” The Institute of Medicine's 2003 report on unequal treatment defines health care disparities more narrowly as “racial or ethnic differences in the quality of healthcare that are not due to access-related factors or clinical needs, preferences, and appropriateness of intervention.” Therefore, the Institute of Medicine focuses on the provision of the same level of health care to everyone, the World Health Organization goes one step further and suggests that the health care system is charged not only with the provision of an adequate level of care to everyone but also with the alleviation of remediable health differences. Disparities in health care may cause or exacerbate disparities in health. This article is unable to characterize clearly the presence or absence of disparities in the ways in which care is delivered to different patients, and so it is limited in its capacity to clearly identify the causes of outcome differences.
Clinicians and policymakers increasingly are coming to understand the extent to which pediatric and adult outcomes reflect the cumulative insults and benefits of the encounters and exposures experienced during a lifetime. The life course perspective, as this view has come to be known, holds that health insults in the prenatal and childhood period can alter life trajectories. Such insults may be varied and include medical, social, and environmental factors as well as psychological and sociological ones. The life course perspective supports the idea that the failure to optimize health or health care in early life can have profound consequences.[5-10] This perspective, also cited by the article's authors, leads us toward the broader framing of disparities that is championed by the World Health Organization. If inequitable exposures to social disadvantages, racial discrimination, or even genetic disadvantages lead to poorer outcomes, then equal care may not be equitable care.
When outcome differences are being interpreted in finer detail, it may be useful to think through potential early causes of differences in light of the literature. We list here a dozen causes that may be relevant in the current context. They are not in any order or mutually exclusive, and we could readily have added to this list:
- Premorbid life course.
- Biology of a specific liver disease.
- Treatment received for liver disease before the transplant is known to be necessary.
- Treatment received for end-stage liver disease before the transplant is planned.
- Pretransplant care while the patient is on the transplant list.
- Source and quality of the graft.
- Transplant care quality.
- Posttransplant care quality.
- Patient adherence.
- Environmental factors or exposures [including those due to socioeconomic status (SES) or race].
- Existing comorbidities.
Treatment differences may occur at any of these. True causal modeling would require far more data than were available for the current study.[12-14] However, the authors did examine several important covariates, such as those grouped under the generic title of SES, which included income, insurance status, and place of residence. As expected, the authors found that SES variables attenuated the observed magnitude of the racial differences. As illustrated in Fig. 1, the meaning of this latter finding is unclear because controlling for SES factors that are related to race may represent statistical overadjustment; this depends on the underlying causal model. Many SES variables are closely correlated with race, and this makes the interpretation of their distinctions challenging. In addition, as the authors acknowledge, they were not able to measure many relevant SES variables. Insurance status is unquestionably important and was measured in this study. However, parents (especially maternal) education,[16, 17] and mental health are also important variables, for example, and they were not measured.
The authors are on uncertain ground in their examination of the potential effects of nonadherence to the medical regimen on observed differences in outcomes. We advise readers not to interpret the reported results to mean that blacks are less adherent to their liver transplantation regimens than whites because the present study's methods are not capable of a valid examination of the relationship between race and adherence. The authors found that whites are less likely to have notes in their medical charts that mention nonadherence. However, the low reliability of physicians' assessment of adherence has been documented in many settings of care, including the pediatric liver transplant setting. It is particularly unreliable in the context of the present study; An equally plausible interpretation of their findings is that differential reports of nonadherence themselves represent a disparity: physicians are more likely to record nonadherence among black patients than white patients. The authors attempted to mitigate such concerns with an analysis that looked for an out-of-range blood level in a small subsample of patients. There are 2 significant problems with their approach. First, they did this only with a small subsample. Because the availability of a recorded level is likely to be associated with adherence (less adherent patients will be less likely to have a level recorded in the first place), a selection bias is almost certain: the sample used for the subanalysis is not a true representation of the study population as a whole. Second, the authors seem to suggest that their subanalysis establishes that clinicians' notes about nonadherence were accurate because those notes were corroborated by the existence of out-of-range blood levels in many of those cases. However, these are not independent measures of the same construct. In our view, a more likely explanation of the correlation between the two is that physicians who see an out-of-range level (which may be related to a variety of causes, of which nonadherence is only one) are likely to assume that the patient is nonadherent, whether or not this is true.
In addition, the study's results hint that the chart entry did not, in fact, reflect true adherence at all. In Table 4 of their article, the authors report that chart indicators of nonadherence were somewhat (not significantly) lower for deceased patients (nonadherence was mentioned in the chart for 38.2%) versus survivors (nonadherence was mentioned for 42.5%). To accept this result would mean that we would have to believe either that poor adherence is not associated with poor transplant outcomes (which would make this analysis irrelevant for the purposes of this article) or that adherence is improved when patients' outcomes are worse (a highly unlikely assumption).
We, therefore, believe that the idea of black participants showing the highest proportion of nonadherence is not supported by the findings in this study. A more accurate characterization may be that doctors in this study were more likely to suspect nonadherence in patients belonging to a minority group. However, even that conclusion may not be well justified because of the lack of statistical adjustments for things such as SES in this analysis. Regardless, the fact that so many patients had chart notes documenting a suspicion of nonadherence ought to stimulate activities to enhance the capacities of families to adhere to these challenging regimens.
This important study documents racial disparities in pediatric liver transplant outcomes. The higher graft failure and mortality rates among black children are both alarming and unacceptable. Although this study's findings may not be surprising, they are a reminder of the need for research to uncover racial/ethnic disparities in pediatric health and health care because these disparities can have large repercussions for a person's health status across his or her life course. The study's primary finding is sufficient to represent an important call for the liver transplantation community to both monitor and reduce disparities. Quality improvement and other implementation research strategies may simultaneously generate improvements and knowledge that can help us to understand the causes of the observed disparities. To the extent that race, SES, and other nonclinical factors may increase the challenges for medical management, resources for treating these at-risk children may need to be increased above the baseline considered appropriate for liver transplantation. Early targets for intervention may be enhanced services to support the coordination of care and routine objective assessments of adherence to drug regimens (and interventions when needed). A transplant is a highly valuable and scarce resource; the goal of preserving this resource more than justifies the additional investment.
- 1Committee on Quality of Health Care in America of the Institute of Medicine. Crossing the Quality Chasm: A New Health System for the 21st Century. Washington, DC: National Academies Press; 2001.
- 3The concepts and principles of equity and health. Health Promot Int 1991;6:217-228..
- 4Committee on Understanding and Eliminating Racial and Ethnic Disparities in Health Care of the Institute of Medicine. Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care. Washington, DC: National Academies Press; 2003.
- 5Health disparities beginning in childhood: a life-course perspective. Pediatrics 2009;124(suppl 3):S163-S175., .
- 6What is health equity: and how does a life-course approach take us further toward it? Matern Child Health J 2013:1-7..
- 8Perspectives on the life course. In: Elder GH , ed. Life Course Dynamics: Trajectories and Transitions, 1968-1980. Ithaca, NY: Cornell University Press; 1985:23-49.
- 12Causes and explanations: a structural-model approach. Part I: causes. Br J Philos Sci 2005;56:843-887., .
- 14Rothman KJ, ed. Causal Inference. Chestnut Hill, MA: Epidemiology Resources; 1988.
- 15What is Medicaid's impact on access to care, health outcomes, and quality of care? Setting the record straight on the evidence. http://kff.org/report-section/what-is-medicaids-impact-on-access-to-care-health-outcomes-and-quality-of-care-setting-the-record-straight-on-the-evidence-issue-brief. Published August 2, 2013. Accessed November 2013., .
- 18Maternal postnatal mental health and later emotional-behavioural development of children: the mediating role of parenting behaviour. Child Care Health Dev; doi:10.1111/cch.12028., , , , .