John D Cowden1, Gabriela Flores2, Tiffany Chow2, Patricia Rodriguez3, Tracy Chamblee3, Megan Mackey4, Anne Lyren5, Michael F Gutzeit6. 1. Children's Mercy Kansas City, 2401 Gillham Road, Kansas City, MO, 64108, USA. jdcowden@cmh.edu. 2. Children's Mercy Kansas City, 2401 Gillham Road, Kansas City, MO, 64108, USA. 3. Children's Medical Center Dallas, 1935 Medical District Drive, Mailstop K4.01, Dallas, TX, 75235, USA. 4. Central Connecticut State University, 1615 Stanley St, New Britain, CT, 06053, USA. 5. UH Rainbow Babies and Children's Hospital, 11100 Euclid Avenue, Cleveland, OH, 44106, USA. 6. Children's Hospital of Wisconsin, 8915 W. Connell Court, Milwaukee, WI, 53226, USA.
Abstract
OBJECTIVE: To describe how pediatric hospitals across the USA and Canada collect race/ethnicity and language preference (REaL) data and how they stratify quality and safety metrics using such data. METHODS: Pediatric hospitals from the Solutions for Patient Safety network (125 US, 6 Canadian) were surveyed between January and March 2018 on collection and use of patient/family race/ethnicity data and patient/family language preference data. The study team created the survey using a formal process including pre-testing. Responses were analyzed using descriptive statistics. RESULTS: Ninety-three of 131 (71%) hospitals completed the survey (87/125 [70%] US, 6/6 [100%] Canadian). Patient race/ethnicity was collected by 95%, parent/guardian race/ethnicity was collected by 31%, and 5/6 Canadian hospitals collected neither. Minimum government race/ethnicity categories were used without modification/addition by 68% of US hospitals. Eleven hospitals (13%) offered a multiracial/multiethnic option. Most hospitals reported collecting language preferences of parent/guardian (81%) and/or patient (87%). A majority provided formal training on data collection for race/ethnicity (70%) and language preferences (70%); fewer had a written policy (41%, 51%). Few hospitals stratified hospital quality and safety measures by race/ethnicity (20% readmissions, 20% patient/family experience, 16% other) or language preference (21% readmissions, 21% patient/family experience, 8% other). CONCLUSIONS: The variability of REaL data collection practices among pediatric hospitals highlights the importance of examining the validity and reliability of such data, especially when combined from multiple hospitals. Nevertheless, while improvements in data accuracy and standardization are sought, efforts to identify and eliminate disparities should be developed concurrently using existing data.
OBJECTIVE: To describe how pediatric hospitals across the USA and Canada collect race/ethnicity and language preference (REaL) data and how they stratify quality and safety metrics using such data. METHODS: Pediatric hospitals from the Solutions for Patient Safety network (125 US, 6 Canadian) were surveyed between January and March 2018 on collection and use of patient/family race/ethnicity data and patient/family language preference data. The study team created the survey using a formal process including pre-testing. Responses were analyzed using descriptive statistics. RESULTS: Ninety-three of 131 (71%) hospitals completed the survey (87/125 [70%] US, 6/6 [100%] Canadian). Patient race/ethnicity was collected by 95%, parent/guardian race/ethnicity was collected by 31%, and 5/6 Canadian hospitals collected neither. Minimum government race/ethnicity categories were used without modification/addition by 68% of US hospitals. Eleven hospitals (13%) offered a multiracial/multiethnic option. Most hospitals reported collecting language preferences of parent/guardian (81%) and/or patient (87%). A majority provided formal training on data collection for race/ethnicity (70%) and language preferences (70%); fewer had a written policy (41%, 51%). Few hospitals stratified hospital quality and safety measures by race/ethnicity (20% readmissions, 20% patient/family experience, 16% other) or language preference (21% readmissions, 21% patient/family experience, 8% other). CONCLUSIONS: The variability of REaL data collection practices among pediatric hospitals highlights the importance of examining the validity and reliability of such data, especially when combined from multiple hospitals. Nevertheless, while improvements in data accuracy and standardization are sought, efforts to identify and eliminate disparities should be developed concurrently using existing data.