The aim of the present research was to examine racial inequality in admission to, length of stay in, and survival after hospitalization. Although the unadjusted relative risk of admission was about 12 percent higher for white adults, we found no racial difference in the frequency of admission after adjusting for status characteristics. Some of the antecedents of admission, however, differed by race. In comparison to white adults, black adults who were admitted had more morbidity and poorer health ratings. Also, they were about a year younger than white adults at the time of their first admission.
Unlike many studies that examine hospital patients only and/or aggregate information across stays, the NHEFS permits examining individual admissions and stays for a community-based sample from the start of the study. Moreover, the current study is not cohortcentric, such as those studying Medicare beneficiaries only.
To our knowledge, this is the first longitudinal study to systematically examine black/ white differences in LOS by isolating each admission over such a long period of observation. The analyses revealed that black adults generally had longer stays than did their white counterparts. This occurred in three out of the four hospital stays analyzed. The longer length of stay may initially seem counterintuitive, but these results are consistent with those of other studies (e.g., Kahn et al. 1994
; Shi 1996
) and are best seen in light of a chain of risk. Moreover, there is evidence of how major episodes in health care are related to subsequent outcomes: Prior recent hospital stays were associated with greater LOS. Temporally proximal stays reveal medical need that is often addressed by a longer stay.
Isolating each stay separately also revealed that the black/white difference in LOS was greater for the first admission than for the second one. We interpret this pattern as partially reflecting an institutional response to address the earlier inequality—the longer stay helps to offset the accumulated health problems. The institutional response, however, is one that is in many ways insufficient. Thus, by the second stay there are diminishing returns for a hospital stay to undo the accumulated risks. For those who survived to experience four hospital admissions, the black/white gap in LOS widened to roughly the same level as the first admission.
The final link in the analysis of this chain of risk is average age at death by race, and the findings here vividly illustrate the consequences of enduring racial inequality. Findings from event history models of post-hospital mortality reveal that black adults were more likely than white adults to die after hospital admission, and the racial difference increased across the life course. There have been many studies of post-hospital mortality among Medicare beneficiaries (Walter et al. 2001
; Wen and Christakis 2005
), but the NHEFS permits a more cohort-inclusive view of hospitalization and mortality. Whether in middle age or later life, black adults suffer higher post-hospital mortality. Indeed, as one ponders the timing of death after a hospitalization, one finds that black people died about four years sooner than their white counterparts after their first hospitalization. The difference shrinks somewhat for the second and subsequent hospitalizations, but this must be seen against a backdrop of increasing selectivity. The analyses also show that black adults are more likely than white adults to have long hospital stays, and long stays, in turn, are associated with higher mortality.
The findings of the present research, drawn from longitudinal data, show the utility of an approach to analyzing life course data based on a chain of risk. Aggregating hospitalizations over the years is useful for many analyses, but isolating each hospitalization with these data revealed important variability in the sequence of hospitalizations. The analyses imply that the sequence of risk is distinct for black and white adults. It also helps one to see how the timing of life course events is important. Black people generally have poorer health, arrive at the hospital later in the course of their illness, have longer stays, and are at greater risk of mortality.
Although much can be gained from studying any of the outcomes herein, we believe that the analyses help identify the pathways by which disparities develop in health and health care. Stated differently, how might the conclusions be different by considering only one outcome? What would longer stays for black adults mean if not in the context of differences in health status and higher post-hospital mortality risk? It may be misleading to consider hospitalization outcomes in isolation. Inequalities develop over the life course, and these analyses illustrate the utility of a chain-of-risk model for assessing racial disparities.
The overwhelming evidence from the present analyses reflects scarring or cumulative inequality and is consistent with what Hart (1971)
described as the inverse care law (Fiscella and Shin 2005
). Black adults had critical health needs, but they received care that in many ways was insufficient to ameliorate their health disadvantage relative to white adults (Bach et al. 1999
Accumulated disadvantage among hospitalized black people is manifested in greater morbidity: Black adults were more likely than white adults to have hypertension, heart trouble, and diabetes. Black adults were also disadvantaged in socioeconomic status, access to a regular physician, and health ratings. Status resources were important predictors of the outcomes, but income, medical insurance, and even having a regular physician were insufficient to eliminate the racial disparity. Socioeconomic status represents a cluster of risk factors, but white adults with limited resources still fared better on multiple outcomes than did black adults.
Although we believe the present study contributes to our understanding of black/white inequality, it is limited in several ways that temper conclusions and suggest fruitful lines of research. First, as noted earlier, NHEFS does not include information on physician visits or waiting time. We adjusted models for whether or not the subject had a regular source of care, but we were unable to see the specific processes leading up to the hospitalization. As such, our hypotheses about delays in accessing care should be considered tentative, at least until others can make use of data that examine these processes in detail. Delays in medical care may occur for a variety of reasons including inability to pay for services, distrust of the medical system, discrimination by practitioners, and both lay and professional referral systems. The aim here was to examine the long-term processes of inequality over two decades, but other studies are needed to discern if the delay mechanism occurs as suggested here.
Second, the NHEFS data do not have official hospital records for all reported stays. More than 75 percent of the reported stays have abstracted records, but the possibility remains that the absence of matching reported and recorded hospital stays may influence the conclusions.
Finally, the NHEFS provides an exceptional opportunity to conduct a long-term analysis of racial inequality in health and hospitalization, but some of the conclusions rest in a historical period. Our aim was primarily hypothesis-testing derived from applying a chain-of-risk model, but the conclusions may be different if current hospitalization patterns are studied. As sociologists, we think it is very unlikely that social change has eliminated racial/ethnic inequality in health and health care. At the same time, it is possible that some of the disparity has been reduced. We controlled for changes induced by the prospective payment system, but the racial differences remained. Nevertheless, to address current public policy, analyses of more recent data are needed.
Despite these limitations, the findings from the present study are helpful for developing a chain-of-risk approach to health and health care. The results favor a model of the chain of risk with independent effects for the accumulation of disadvantage (Kuh et al. 2003
). One conception of risk accumulation is the trigger or tipping-point model, where risks accumulate but the disadvantage is not apparent until there is a confluence of a set of risks. Rather, we observed black/white differences in morbidity, having a regular physician, several LOS measures, and average age at death by race; these differences reflect both direct and indirect effects of race on desired outcomes when facing health problems. Trajectories may be altered by exposure to deleterious or salubrious events and processes, and the evidence is clear that these trajectories were distinct for black and white adults. To better understand how inequality accumulates, we will need additional studies to examine other chains of risk such as tracing the occurrence of the same or closely-related health problems across episodes of care.
To advance an interpretation of racial disparities in health based on a chain of risk, one must also make explicit the role of selective survival. Mortality was an outcome in this study and thereby received explicit attention. For any study of a chain of risk, however, mortality selection merits attention because non-random mortality may give the appearance of decreasing inequality over the life course (Fiscella 2004
; Kelley-Moore and Ferraro 2004
). For adulthood and later life, mortality is the obvious form of selection. Even if one is studying income differentials or wealth, mortality for selected groups will shape the outcomes. For adolescents and young adults, there may be other forms of selection such as foster care and incarceration. The point is that scholars must attend to sample composition and selection effects when offering conclusions about life course inequalities (Ferraro, Shippee, and Schafer Forthcoming). Failure to consider these influences will likely lead to conclusions that minimize inequalities.
The overall portrait of health and health care for black people that emerges from these analyses is one of enduring and accumulated disadvantage. Higher morbidity, no difference in admission rates, and generally longer stays reveal a racial disparity. Moreover, higher mortality for black adults after their first hospitalization highlights the pernicious effects of the disparity.