Abstract B33: Who am I? Improving quality of data collection for race/ethnicity and language

Introduction: Disparities in the quality of care provided to minorities has been documented in the literature. Reliable racial/ethnic reporting is critical, as initiatives to address healthcare disparities remain priorities on the national agenda. Hispanic children have been cited as having a higher incidence of leukemia/lymphoma but poorer survival rates. Accurate attribution of disease incidence and outcome to specific populations is central to ensuring appropriate access to care, family communication, resource distribution and funding for research. Analysis of 2000-2010 Hematology/Oncology data at Rady Children's Hospital San Diego (RCHSD) found a 13.02% discrepancy rate for race/ethnicity accuracy and 21% self-report rate. RCHSD is a pediatric medical center serving San Diego, Imperial, and southern Riverside counties in California, where Hispanic children comprise 42% of the population. While there is consensus regarding the importance of self-reporting of race/ethnicity, we identified both significant lack of self-reported race/ethnicity data and varied forms used to collect patient demographics at our site. Research has shown that most observers including administrative staff will accurately identify individuals as white or black, but Hispanic and multiracial individuals are often misidentified. Purpose: The Global Aim of this study was to improve resource allocation, patient-provider engagement and access to race/ethnicity and language data for research through correct race/ethnicity/language attribution. Our SMART aim was to implement a uniform and accurate system for data collection on race/ethnicity and language for the hematology/oncology population at our hospital with a reduction of missing and discrepant data to