Appendiceal rupture (AR) was much more burdensome than appendectomy without rupture. The mean total hospital charges were 97% higher for AR cases, while mean length of hospital stay was 175% longer. These additional burdens fell disproportionately on minority children. Results for the first regression model in Table show unadjusted racial/ethnic disparities in acute appendicitis outcome. However, the second regression model is more relevant to the national goal of reducing disparities, because it includes adjustments for factors that are not amenable to changes in health policy, social policy or medical practice – patient age and gender. Disparities revealed in this model should be targeted for elimination. African American children have approximately 38% greater odds of appendicitis rupture (AR) compared to whites, and the relative odds are not much better for Hispanic or Asian children – 24% and 32% higher, respectively.
These national disparity estimates differ somewhat from findings reported for other samples. Among 1997 California pediatric discharges Guagliardo et al. [9
] found that African American and white children had indistinguishable AR rates, while Hispanic and Asian children had higher odds of AR – 45% and 30%, respectively. They found a different pattern of disparities among 1995 New York discharges. There, white and Hispanic children were indistinguishable, while African American children had 47% higher odds and Asian children had 116% higher odds of AR. In a sample of discharges from children's hospitals Ponsky et al. [10
] found that African American children had 13% higher odds and Asian children had 66% higher odds of AR compared to white children. However, they could not identify Hispanic children in their sample, and they used different adjustment variables.
In spite of the incomparability of the samples studied to date, a pattern is emerging. White children have never been found to be at greater odds of AR than any minority group, while minority children are usually found to have poorer appendicitis outcomes than white children. The key question remains. Why is there racial/ethnic disparity in acute appendicitis outcomes?
To explore this question it is helpful to view acute appendicitis as a "delay-sensitive" condition [28
]. Once its clock starts then rupture, broader infection, bleeding and death are inevitable without surgery. Lacking evidence to the contrary, it is generally assumed that the disease progresses at the same average rate for all social groups. Therefore inter-group differences in average delay of key milestones in the disease course must account for the disparities. The milestones include first complaint of abdominal pain, parental recognition of urgency, initial seeking of professional care, performance of diagnostic procedures and/or referrals to other healthcare facilities, eventual correct diagnosis, and finally surgical intervention. Reductions in time between any of these milestones will reduce the chance of rupture. Research suggests that in the U.S. there is little or no delay between correct diagnosis and surgery [12
]. Children get to the operating room quickly once the diagnosis is made. Therefore, the disparities we have discovered are probably due to longer average delays for minorities prior to correct diagnosis.
Factors that can delay care seeking and timely diagnosis include family health beliefs and economic condition, insurance coverage, physician quality and distance to healthcare provider. We expected that our fuller regression models would provide insight into the effects of some of these factors. Two of the covariates used are taken from major domains generally involved in the production of racial/ethnic disparities in health and healthcare – income [29
] and insurance type [30
]. As mediators of disparity such as these are added to regression models, apparent race/ethnicity differences should decrease and eventually disappear if all explanatory factors could be included. Yet our fullest model in Table has not achieved this ideal. In it all minority groups still have higher odds of AR relative to white children. This could be because our covariables are imperfect representatives of their domains. For example, insurance type may be too coarse of a measure of insurance quality, e.g. privately insured white children were in better plans than privately insured minority children. It is also possible that administratively derived data sets such as KID 2000 do not contain proxies for important disparity-producing factors. Two prime examples are language and cultural differences between patients and their healthcare providers [31
], and level of geographic availability of local care providers [33
]. Including more and better covariables might have accounted for all race/ethnic disparities. Furthermore, the behavior of these covariables in regression models could point out socioeconomic, demographic and health services factors to be targeted to achieve better outcomes and less disparity. However, finding a fully explanatory model could not excuse the disparities revealed in our second model (Table ). The disparities revealed in that model should remain as the national indicators of disparity and should be targeted for reduction [34
The disparity differences found between California, New York and the current national sample suggest that local sociocultural factors are at play. Guagliardo et al. [9
] suggested a link between odds of being foreign-born in the two states and odds of AR. They hypothesized that general degree of acculturation could be a major precipitator of disparities, acting through language barriers, preferences for traditional healing and concern among undocumented immigrants for engaging the healthcare system.
A definitive understanding of the causes of disparity in pediatric AR rates will require prospective, primary data collection, including family interviews and in depth case reviews with special attention to the timing of the aforementioned milestones to discover the social, economic, provider and health systems circumstances associated with delayed surgery. However, that the precise causes of disparities remain unclear should not detract from the major thrust of this report. The disparities are real, occur on a national scale, and are most likely due to socioeconomic, cultural and healthcare system factors.
While the covariates in the fuller models do not account for all of the disparities and are not the main focus of this study, their effects are nonetheless noteworthy. The negative effect of lower income is consistent with a large literature on income, wealth and health [35
]. As found in previous studies [9
], admission from the emergency department (ED) of the hospital that performed the appendectomy reduces the odds of AR. In contrast, patients who go to other healthcare settings before referral to the surgical facility tend to have poorer outcomes, ostensibly due to the additional delay. There are similar findings in the acute myocardial infarction and stroke literature [37
]. Patients with chest pains or stroke symptoms should go immediately to the nearest ED. Yet it would be premature to recommend that all children with abdominal pain report immediately to the nearest ED. Abdominal pain has many causes [8
], and such a recommendation would fly in the face of decades of efforts to reduce unnecessary ED utilization [38
]. Careful and thorough research is required to developed optimal recommendations to reduce both AR rates and unnecessary ED utilization [38
Teaching hospitals have a reputation for lower patient satisfaction but better medical outcomes than non-teaching hospitals [19
]. Findings for AR have been mixed. Braveman et al. [15
] reported better outcomes for adults discharged from teaching hospitals, while Guagliardo et al. [9
] found poorer outcomes for children discharged from teaching hospitals. Here, adjusted odds of AR are estimated to be 6% higher for children discharged from teaching hospitals, although the difference is not statistically significant. Still, future AR studies should consider hospital teaching status as a covariable.
Of all the covariables, pediatric discharge volume yielded the most surprising results. Contrary to the "practice makes perfect" maxim [21
], neither of the previous large-sample pediatric studies [9
] found a relationship between volume and outcome. The current analysis actually showed the reverse effect. Hospitals in the highest volume group had significantly higher AR rates. This is difficult to explain. It is possible that high-volume hospitals have unfavorable staff-to-patient ratios, leading to additional delays in care. It might also be that these hospitals are located in underserved areas, and hence more of their patients must travel farther for service, which might delay diagnosis. We know of no published studies that test these hypotheses. It is interesting to note that Smink et al. [22
] found significantly higher rates of negative
appendectomy in low-volume hospitals. (A negative appendectomy is an unnecessary surgery resulting from an incorrect diagnosis.) Smink et al. analyzed the 1997 version of KID. Comparing their nationally representative results with ours, it appears that two kinds of error might be in effect. Low-volume facilities might have excessive rates of misdiagnosis and premature surgery, while high-volume facilities might have excessive rates of delayed diagnosis and delayed surgery. We are planning another study to explore these questions. Recommendations are not possible at this time.