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This study aims to support the improvement of ethnicity recording in emergency care data by (a) investigating variation in unknown ethnicity records, (b) exploring patterns of missingness between ethnicity and other variables and (c) identifying the variables most important in the recording of an unknown ethnicity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>Secondary analysis of the Emergency Care Data Set (ECDS).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Setting and participants<\/jats:title>\n                    <jats:p>National Health Service (NHS) and independent sector organisations who provide emergency care services in England. Includes all anonymised ECDS records from the financial year 2023\/2024, excluding those with a \u2018Null\u2019 anonymised pseudo-NHS number or those patients announced as dead on arrival (24\u2009167\u2009154 records after exclusions).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Differences in the percentage of unknown ethnicity records were seen across ages, organisation types and attendance characteristics. An increase in the percentage of missing values was observed for 62 variables when ethnicity was unknown, with the largest increases shown by variables related to investigations and treatments received by the patient (15.31% and 14.74%). Provider site code was identified as the most important variable in recording ethnicity as unknown. Further analysis highlighted a subset of acute trusts and independent sector organisations that disproportionately contributed to unknown ethnicity records.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This study has improved understanding of unknown ethnicity recording by exploring variation across demographics and organisation types and demonstrating an increase in missingness across other ECDS variables when ethnicity is unknown. Unknown ethnicity recording appears to be a site-specific problem, which should be addressed through improvements to the data collection processes of individual providers. These insights should be used to improve the quality of ethnicity coding within emergency care data, necessary for tackling health inequalities.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1136\/bmjopen-2026-118200","type":"journal-article","created":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T12:25:22Z","timestamp":1786969522000},"page":"e118200","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Using classification and regression trees (CART) to investigate unknown ethnicity records in NHS emergency care data"],"prefix":"10.1136","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-6063-9327","authenticated-orcid":false,"given":"Grace","family":"Dean","sequence":"first","affiliation":[{"name":"NHS England, Leeds, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8662-8103","authenticated-orcid":false,"given":"Roy A","family":"Ruddle","sequence":"additional","affiliation":[{"name":"School of Computing and Leeds Institute for Data Analytics, University of Leeds, Leeds, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2026,8,17]]},"reference":[{"key":"2026081705250969000_16.8.e118200.1","doi-asserted-by":"crossref","first-page":"e966","DOI":"10.1016\/S2468-2667(22)00223-7","article-title":"COVID-19 mortality and deprivation: pandemic, syndemic, and endemic health inequalities","volume":"7","author":"McGowan","year":"2022","journal-title":"Lancet Public Health"},{"key":"2026081705250969000_16.8.e118200.2","doi-asserted-by":"publisher","DOI":"10.1111\/phn.12959"},{"key":"2026081705250969000_16.8.e118200.3","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1177\/0020731421993939","article-title":"Health Inequalities in the Time of COVID-19: The Globally Reinforcing Need to Strengthen Health Inequalities Research Capacities","volume":"51","author":"Cash-Gibson","year":"2021","journal-title":"Int J Health Serv"},{"key":"2026081705250969000_16.8.e118200.4","doi-asserted-by":"crossref","first-page":"E34","DOI":"10.1001\/amajethics.2025.34","article-title":"What Are High-Quality Race and Ethnicity Data and How Are They Used in Health Equity Research?","volume":"27","author":"Rentsch","year":"2025","journal-title":"AMA J Ethics"},{"key":"2026081705250969000_16.8.e118200.5","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph192315874","article-title":"A Scoping Review of Approaches to Improving Quality of Data Relating to Health Inequalities","volume":"19","author":"Moorthie","year":"2022","journal-title":"Int J Environ Res Public Health"},{"key":"2026081705250969000_16.8.e118200.6","doi-asserted-by":"crossref","DOI":"10.3390\/ijerph20085530","article-title":"The Lack of Race and Ethnicity Data in Australia-A Threat to Achieving Health Equity","volume":"20","author":"Renzaho","year":"2023","journal-title":"Int J Environ Res Public Health"},{"key":"2026081705250969000_16.8.e118200.7","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/j.amjsurg.2023.05.011","article-title":"The accuracy of race & ethnicity data in US based healthcare databases: A systematic review","volume":"226","author":"Johnson","year":"2023","journal-title":"Am J Surg"},{"key":"2026081705250969000_16.8.e118200.8","doi-asserted-by":"crossref","first-page":"832","DOI":"10.1007\/s43678-022-00388-9","article-title":"Collection of patient race, ethnicity, and language data in emergency departments: a national survey","volume":"24","author":"Velmurugiah","year":"2022","journal-title":"CJEM"},{"key":"2026081705250969000_16.8.e118200.9","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/s10691-020-09437-z","article-title":"COVID-19 Highlighting Inequalities in Access to Healthcare in England: A Case Study of Ethnic Minority and Migrant Women","volume":"28","author":"Germain","year":"2020","journal-title":"Fem Leg Stud"},{"key":"2026081705250969000_16.8.e118200.10","doi-asserted-by":"publisher","DOI":"10.1111\/jan.15233"},{"key":"2026081705250969000_16.8.e118200.11","doi-asserted-by":"crossref","first-page":"e145","DOI":"10.1016\/S2468-2667(20)30287-5","article-title":"Ethnic inequalities in health-related quality of life among older adults in England: secondary analysis of a national cross-sectional survey","volume":"6","author":"Watkinson","year":"2021","journal-title":"Lancet Public Health"},{"key":"2026081705250969000_16.8.e118200.12","unstructured":"NHS England . 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