When stratifying by the top 10 causes of death, the percentage difference in the AAMR pre- to post-IHS records linkage ranged from a 15.2% increase (chronic liver disease and cirrhosis) to 40.1% increase (chronic lower respiratory disease) in the AAMR for AI/ANs (Table 3). For whites, the AAMR decreased from 1.6% (cerebrovascular disease) to 4.1% (unintentional injuries and chronic liver disease and cirrhosis). Preceding the IHS record linkage, the white population had a higher AAMR for chronic lower respiratory disease, cerebrovascular disease, and suicide compared with AI/ANs. However, after the IHS linkage, the data now reflect a more accurate burden of death due to disease and injury for AI/ANs (Table 3).
Mortality data are a primary source of information used in public health to understand the population burden of disease and injury, identify disparities among population subgroups, monitor trends over time, and prioritize programs and resource allocation. With many decisions relying on the assumption of accurate data, misclassification of race on death certificates is a significant problem when describing health disparities in Oklahoma and throughout the United States. Although this most recent study shows that racial misclassification on death certificates has improved through time, it continues to be a problem in Oklahoma with 30% more deaths among AI/AN residents being identified through linkage with IHS records. Misclassification remains high in all regions of Oklahoma and in most disease categories. Furthermore, we know that there is still misclassification for which the process of IHS linkage does not account, as not all AI/ANs seek care at I/T/Us. Other mortality linkage studies2,43 and commentaries3 have previously described the limitations of using IHS-linked data to correct for racial misclassification, particularly in places where IHS services are less accessible and for AI/ANs who were eligible for but never accessed IHS services.
Oklahoma has invested in continued IHS linkage to improve mortality data and, to our knowledge, is the only state that makes these misclassified data available on a public Web query site (OK2SHARE). The Centers for Disease Control and Prevention makes its IHS-linked cancer incidence data publicly available through Wide-ranging ONline Data for Epidemiologic Research (CDC WONDER); however, the unlinked data are not available to examine misclassification. Publicly available IHS-linked data have been very important for tribal epidemiology centers, tribes, and researchers and even more important for program managers and policy makers who are unable to measure the extent of conditions or the impacts of their programs.
Health measures must be accurate for states and health care systems to plan for the use and costs of health care services. Accurate data are needed to evaluate the trends related to the quality and delivery of health care services, as well as the capacity of various components of health care. Although the corrected data are available in OK2Share, not all health care providers are familiar with or access these data source when planning service delivery. This also demonstrates the need to educate health care providers on the impacts of racial misclassification in Oklahoma and on data sources, such as OK2Share, where they can obtain the adjusted mortality rates.
There are several limitations in this study. One limitation is the change in reporting quality over time. During the reporting period, there have been changes in the quality of some variables collected by the Oklahoma Vital Records. There have also been changes to categorization within certain variables, one of which is how race is collected. In particular, we observed that after 2000, when multiple race categories could be reported, we observed dramatic improvement in racial misclassification. Furthermore, there continues to be misclassification in the AI/AN population in Oklahoma. Not all AI/ANs seek care through IHS or I/T/U facilities during their life and may still have their race reported as another race as opposed to AI/AN. A final limitation was the lack of tribal specific data. Because of the large number of tribal headquarters and tribal heterogeneity in the state, tribal members live throughout the state not just in tribal jurisdictional areas. The geographic dispersion of the AI/AN population leads to an additional challenge in reviewing any health data for AI/AN populations in Oklahoma.
This analysis highlights the need for several additional studies and recommendations. Estimates of the number of racially misclassified cases among individuals who do not use IHS services are necessary. The use of geographic information systems analysis could be implemented to determine accuracy of coding by tribal boundaries. The most important recommendation from this analysis is to continue the enhancement systems that support IHS linkages with surveillance systems throughout the United States. Finally, we recommend public access to linked data so that the data remain accessible. The linkage projects are of no value to program planners, evaluators, and researchers if the data are not accessible. As a final point, it is important to determine how to handle the adjusted race variable and determine whether we provide dual estimates (as in OK2Share) or whether there is a more appropriate method. In addition, tribal nations need AI/AN-specific information to plan health services and outreach. Strides cannot be made to improve the health status of a population when inaccurate information prevents effective health planning. Public and private entities require this information so that the conditions that most profoundly affect the health of AI/ANs can effectively be targeted to provide higher quality of care; improve access, targeted health facilities, and cost containment; and allow the pursuit of more resources for prevention and treatment. A final issue that needs to be made clear is that these data reflect statewide population-based information. They do not represent tribal health services or the IHS user population and thus do not reflect the quality of care provided by tribal health services, tribal programs, or IHS.
As mentioned previously, an important result of this study is that misclassification is improving; however, this effort needs to be maintained and further improved. Continued linkage efforts and public access to linked data are essential throughout the United States to better understand the burden of chronic disease in the AI/AN population. Accurately recorded mortality and morbidity records can also allow for better understanding of acute causes of illness (ie, influenza), injuries, and newly emerging epidemics such as the current opioid crisis. Having more accurate data for AI/ANs will help inform health care providers and funders about the true burden of disease and other health outcomes to ultimately improve the health of AI/ANs.
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