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The existence of disparities in healthcare due to race, ethnicity, and language (R/E/L) is well documented. Tracking and reducing disparities requires accurate measurement using complete and reliable data. States wishing to improve R/E/L data face many challenges; among them are geography, policy, budget, population size, public awareness, and governmental priorities. When pursuing data improvement, no single solution is ideal. The Agency for Healthcare Research and Quality (AHRQ) has awarded three 3-year American Recovery and Reinvestment Act grants to promote the enhancement of race/ethnicity information in statewide hospital encounter databases. Each recipient has unique objectives, has faced unique challenges and is employing distinctive solutions to improve data.
METHODS:
Investigators from University of California, Los Angeles and the California Office of Statewide Health Planning and Development (OSHPD) are improving reliability, validity, and completeness of self-reported R/E/L in OSHPD databases; the project will improve hospital data via development of standardized materials, educational intervention, auditing, and followup, making substantial, sustainable improvements to R/E/L data reported by California hospitals. The New Mexico Department of Health is improving race and ethnicity data quality in hospital discharge databases by revising the New Mexico administrative code to mandate R/E and tribal data reporting and employing direct intervention with every hospital in the state; the grant team has developed tools, procedures and training that are improving patient race, ethnicity and tribal data in the New Mexico Hospital Inpatient Discharge Data. The Improving Data & Enhancing Access–Northwest (IDEA–NW) Project of the Northwest Portland Area Indian Health Board is using the most complete roster of Northwest American Indian/Alaska Native people available to conduct record linkages with an array of health-related data systems in Oregon, Washington and Idaho to identify racial misclassification and improve disease/mortality estimates in the three-state region.
RESULTS:
Each grant initiative is realizing results. California created and disseminated tools to improve collection quality and consistency, and conducted webinars for more than 350 hospital representatives. New Mexico developed a systematic method to identify and target factors influencing data collection and have increased awareness at the hospital level through presentations and webinars. IDEA–NW identified racial misclassification in the data systems of three state health departments and is engaged in meaningful discussion with state data managers about race data quality.
CONCLUSIONS:
This multi-grant panel presentation will allow participants to experience and assess three distinct strategies for improving R/E/L data. AHRQ plans to share lessons learned with their state data partners and other organizations.