ArticleApplied clinical informatics2020
Accuracy of the Preferred Language Field in the Electronic Health Records of Two Canadian Hospitals.
Article in Applied clinical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between language discordance and unplanned hospital readmissions or emergency department revisits: a systematic review and meta-analysis.BMJ quality & safety · 2024Pooled it
- Language Preference and Antibiotic Use Among Hospitalized Older Adults With Dementia.Journal of the American Geriatrics Society · 2026Article
- Improving Accurate Documentation of Limited English Proficiency Patients at a Tertiary Affiliated Urgent Care Center in New York City.Journal of patient experience · 2026Article
- Extracting language information from clinical notes using large language models.International journal of medical informatics · 2026Article
- Evaluating sociodemographic bias in a deployed machine-learned patient deterioration model.JAMIA open · 2025Article
- Article
- Accuracy of preferred language data in a multi-hospital electronic health record in Toronto, Canada.PLOS digital health · 2025Article
- A mixed-methods study on the recruitment of patients from ethnic minority groups to clinical trials in a central London teaching hospital.Contemporary clinical trials communications · 2025Article
- Factors associated with language concordant cognitive testing among linguistically diverse older adults.Journal of the American Geriatrics Society · 2025Article
- Languages other than English in a pediatric ED: Documentation, extended stays, and revisits.The American journal of emergency medicine · 2024Article
- Predictors of Concordance between Patient-Reported and Provider-Documented Symptoms in the Context of Cancer and Multimorbidity.Applied clinical informatics · 2024Article
- Clinical evaluation of a machine learning-based early warning system for patient deterioration.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2024Article
- Leveraging Novel Clinical Decision Support to Improve Preferred Language Documentation in a Neonatal Intensive Care Unit.Applied clinical informatics · 2024Article
- The Impact of Limited English Proficiency on Healthcare Access and Outcomes in the U.S.: A Scoping Review.Healthcare (Basel, Switzerland) · 2024Article
- Area-Based Sociodemographic Factors Associated with Latent Tuberculosis Infection in a Low-Prevalence Setting.The American journal of tropical medicine and hygiene · 2023Article
- Assessing the accuracy of electronic health record gender identity and REaL data at an academic medical center.BMC health services research · 2023Article
- Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe collection of race, ethnicity, and language (REaL) data from patients is advocated as a first step to identify, monitor, and improve health inequities. As a result, many health care institutions collect patients' preferred languages in their electronic health records (EHRs). These data may be used in clinical care, research, and quality improvement. However, the accuracy of EHR language data are rarely assessed.
objectivesThis study aimed to audit the accuracy of EHR language data at two academic hospitals in Toronto, Ontario, Canada.
methodsThe EHR language was compared with a patient's stated preferred language by interview. Language was dichotomized to English or non-English. Agreement between language documented in the EHR and patient-reported preferred language was calculated using sensitivity, specificity, and positive predictive value (PPV).
resultsA total of 323 patients were interviewed, including 96 with a stated non-English preferred language. The sensitivity of the EHR for English-language preference was high at both hospitals: 100% at hospital A with a PPV of 88%, and 99% at hospital B with a PPV of 85%. However, the sensitivity of the EHR for non-English preference differed greatly between the two hospitals. The sensitivity was 81% with a PPV of 100% at hospital A and the sensitivity was 12% with a PPV of 60% at hospital B.
conclusionThe accuracy of the EHR for identifying non-English language preference differed greatly between the hospitals studied. Language data must be accurate for it to be used, and regular quality assurance is required.
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