title: Harnessing Data to Assess Equity of Care by Race, Ethnicity and Language.
abstract: OBJECTIVE
  Determine any disparities in care based on race, ethnicity and language (REaL) by utilizing inpatient (IP) core measures at Texas Health Resources, a large, faith-based, non-profit health care delivery system located in a large, ethnically diverse metropolitan area in Texas. These measures, which were established by the U.S. Centers for Medicare and Medicaid Services (CMS) and The Joint Commission (TJC), help to ensure better accountability for patient outcomes throughout the U.S. health care system.
  
  
  METHODS
  Sample analysis to understand the architecture of race, ethnicity and language (REaL) variables within the Texas Health clinical database, followed by development of the logic, method and framework for isolating populations and evaluating disparities by race (non-Hispanic White, non-Hispanic Black, Native American/Native Hawaiian/Pacific Islander, Asian and Other); ethnicity (Hispanic and non-Hispanic); and preferred language (English and Spanish). The study is based on use of existing clinical data for four inpatient (IP) core measures: Acute Myocardial Infarction (AMI), Congestive Heart Failure (CHF), Pneumonia (PN) and Surgical Care (SCIP), representing 100% of the sample population. These comprise a high number of cases presenting in our acute care facilities. Findings are based on a sample of clinical data (N = 19,873 cases) for the four inpatient (IP) core measures derived from 13 of Texas Health's wholly-owned facilities, formulating a set of baseline data.
  
  
  RESULTS
  Based on applied method, Texas Health facilities consistently scored high with no discernable race, ethnicity and language (REaL) disparities as evidenced by a low percentage difference to the reference point (non-Hispanic White) on IP core measures, including: AMI (0.3%-1.2%), CHF (0.7%-3.0%), PN (0.5%-3.7%), and SCIP (0-0.7%).
authors.affiliation: Cinco Strategy Group, 937 Kessler Parkway, Dallas, TX 75208, USA. agracia@cincostrategy.com.
authors.forename: Amber
authors.initials: A
authors.lastname: Gracia
authors.affiliation: Presbyterian Heart &amp; Vascular Group, 8440 Walnut Hill Lane, #610, Dallas, TX 75231, USA. jorgecheirif@texashealth.org.
authors.forename: Jorge
authors.initials: J
authors.lastname: Cheirif
authors.affiliation: Texas Health Resources, 612 E. Lamar Blvd, Suite 1000, Arlington, TX 76011, USA. juanaveliz@texashealth.org.
authors.forename: Juana
authors.initials: J
authors.lastname: Veliz
authors.affiliation: Texas Health Resources, 612 E. Lamar Blvd, Suite 1000, Arlington, TX 76011, USA. melissareyna@texashealth.org.
authors.forename: Melissa
authors.initials: M
authors.lastname: Reyna
authors.affiliation: Texas Health Research &amp; Education Institute, 8400 Walnut Hill Lane, Suite 220, Dallas, TX 75231, USA. maravecchio@texashealth.org.
authors.forename: Mara
authors.initials: M
authors.lastname: Vecchio
authors.affiliation: Department of Biostatistics and Epidemiology, University of North Texas Health Science Center, 3500 Camp Bowie Blvd, Fort Worth, TX 76107, USA. subhash.aryal@unthsc.edu.
authors.forename: Subhash
authors.initials: S
authors.lastname: Aryal
mesh_terms: D001741:Black or African American / Q000706:statistics & numerical data; D003625:Data Collection; D005006:Ethnicity / Q000706:statistics & numerical data*; D000069576:Health Equity / Q000706:statistics & numerical data*; D054625:Healthcare Disparities / Q000706:statistics & numerical data*; D006630:Hispanic or Latino / Q000706:statistics & numerical data; D006801:Humans; D013781:Texas; D014481:United States; D044465:White People / Q000706:statistics & numerical data
keywords: disparities; ethnicity; language; populations; race