The goal of eliminating disparities in health care in the United States remains elusive. Even as quality improves on specific measures, disparities often persist. Addressing these disparities must begin with the fundamental step of bringing the nature of the disparities and the groups at risk for those disparities to light by collecting health care quality information stratified by race, ethnicity and language data. Then attention can be focused on where interventions might be best applied, and on planning and evaluating those efforts to inform the development of policy and the application of resources. A lack of standardization of categories for race, ethnicity, and language data has been suggested as one obstacle to achieving more widespread collection and utilization of these data. Race, Ethnicity, and Language Data identifies current models for collecting and coding race, ethnicity, and language data; reviews challenges involved in obtaining these data, and makes recommendations for a nationally standardized approach for use in health care quality improvement.Aetna was the first national, commercial plan to start collecting race and ethnicity data for all of its members. ... The data may be updated at any point of contact, including at enrollment, when members speak to customer service or patient management representatives, ... (Personal communication, L. Doo, Office of E- Health Standards and Services, Centers for Medicare aamp; Medicaid Services, July 14, 2009).
|Title||:||Race, Ethnicity, and Language Data:|
|Author||:||Subcommittee on Standardized Collection of Race/Ethnicity Data for Healthcare Quality Improvement, Board on Health Care Services, Institute of Medicine|
|Publisher||:||National Academies Press - 2009-11-30|