Racial and Ethnic Descriptors

In response to the lack of easily retrievable clinical data to address health services and medical effectiveness questions, especially as they relate to racial/ethnic minorities, the Center for Information Technology (CIT), Agency for Health Care Policy and Research (AHCPR) recently sponsored a project on record linkage methodology applied to automated medical administrative datasets containing racial and ethnic identifiers (Contract 282-94-2005). The primary objectives of the project were to: link patient-level related datasets that contain racial and ethnics descriptors; and assess the value of the linked data to address medical effectiveness research questions that focus on the quality, effectiveness, and outcomes from care for minority populations. KAI, AHCPR's contractor, received approval from the State of New York's Department of Health to utilize the Statewide Planning and Research Cooperative System (SPARCS) files Discharge Data Abstract (DDA) and Uniform Billing files (UBF), which contain all acute hospital discharge and claims data, the SPARCS Ambulatory Surgical files, and the Cardiac Surgery Reporting System (CSRS) files, a research dataset. KAI received files for the 1991, 1992, and 1993 time periods. The files were successfully linked by patient, "visits" across the time periods. While the linked data appear to be of high quality, the process of obtaining and linking the data is lengthy. Additionally, these administrative health care data sets contain millions of records that document all hospital stays and thus, identifying appropriate subpopulations for a particular research question is a time and resource-consuming effort. While the administrative health care datasets may be useful in answering questions about charges, length of stay, and other health service issues, their current utility may be less useful in answering clinical questions for minority populations. These datasets can be used to explore potential associations among diagnoses, treatment, and outcome variables. However, understanding the mediating factors and the decision-making variables that result in patient care may not be possible. For example, the results of diagnostic tests such as angiograms are not generally recorded in these datasets, thus limiting the ability to carefully subgroup patients by disease severity. With consideration for the potential utility of these datasets, however, there are several recommendations that emanate from the study. This talk will briefly describe the research questions posed, linkage process, findings, and recommendations for additional action and policy considerations. Chapter 10 Record Linkage Methods Applied to Health Related Administrative Data Sets Containing Racial and Ethnic Descriptors Selma C. Kunitz, Clara Lee, and Rene C. Kozloff, Kunitz and Associates, Inc. Harvey Schwartz, Agency for Health Care Policy and Research Kunitz, Lee, Kozloff, and Schwartz