Using Record Linkage to Improve Race Data Quality for American Indians and Alaska Natives in Two Pacific Northwest State Hospital Discharge Databases

American Indians and Alaska Natives (AI/AN) have worse physical and mental health status than other racial and ethnic groups in the United States, and they face barriers in receiving adequate and timely health services (Roberts and Jones 2004; Barnes, Adams, and Powell-Griner 2010). The Indian Health Service (IHS) is the federal agency charged with providing health care to members of federally recognized AI/AN tribes, corporations, and villages. In the Pacific Northwest states of Idaho, Oregon, and Washington, these services are provided by IHS-operated clinics, tribally operated clinics, and Urban Indian Health Organizations. However, a sizeable proportion of the estimated 344,600 AI/AN in the Northwest do not receive health care from the IHS; in 2013, the IHS had 197,188 patients registered within the three-state area, and 60 percent of these had at least one patient encounter in the past 3 years (Indian Health Service 2014). Further, there are no inpatient hospital facilities within the Indian health system in these states. Therefore, all inpatient hospital services for Northwest AI/AN are provided through nonfederal hospitals. Hospital discharge data are used in a wide variety of public health and health care applications and provide valuable information on health care utilization and health disparities (Schoenman et al. 2005). However, information on the race and ethnicity of patients may not be systematically or accurately collected in these datasets. AI/AN are frequently misclassified in surveillance and administrative data systems, with misclassification ranging from 30 to 70 percent (Kressin et al. 2003; Puuka, Stehr-Green, and Becker 2005; Johnson et al. 2009; Hoopes et al. 2010). Compared with other race groups, AI/AN have the lowest levels of agreement (approximately 60 percent) between self-reported race and race assigned in medical records (Boehrmer et al. 2002; Kressin et al. 2003; Gomez et al. 2005). Data quality issues compound other statistical challenges surrounding small population/cell size and make it difficult to accurately measure AI/AN health disparities at the state and local levels, where actions to address disparities are most likely to occur (Bilheimer and Klein 2010). Record linkage of datasets with IHS, tribal, and urban clinic registration data is an effective strategy for reducing AI/AN misclassification in administrative datasets (Becker et al. 2002; Puuka, Stehr-Green, and Becker 2005; Foote et al. 2007; Johnson et al. 2009; Hoopes, Vinson, and Lopez 2012). Since 1999, the Improving Data and Enhancing Access—Northwest (IDEA-NW) project, part of the Northwest Tribal Epidemiology Center and Northwest Portland Area Indian Health Board, has conducted record linkage studies with state health datasets in Idaho, Oregon, and Washington. The current study evaluates AI/AN misclassification within Oregon and Washington’s hospital discharge data with the aim of providing more reliable measurements of AI/AN hospitalizations.