Leveraging Ethnic Backgrounds to Improve Collection of Race, Ethnicity, and Language Data.

INTRODUCTION: Healthcare disparities may be exacerbated by upstream incapacity to collect high-quality and accurate race, ethnicity, and language (REaL) data. There are opportunities to remedy these data barriers. We present the Denver Health (DH) REaL initiative, which was implemented in 2021. METHODS: Denver Health is a large safety net health system. After assessing the state of REaL data at DH, we developed a standard script, implemented training, and adapted our electronic health record to collect this information starting with an individual's ethnic background followed by questions on race, ethnicity, and preferred language. We analyzed the data for completeness after REaL implementation. RESULTS: A total of 207,490 patients who had at least one in-person registration encounter before and after the DH REaL implementation were included in our analysis. There was a significant decline in missing values for race (7.9%-0.5%, p < .001) and for ethnicity (7.6%-0.3%, p < .001) after implementation. Completely of language data also improved (3%-1.6%, p < .001). A year after our implementation, we knew over 99% of our cohort's self-identified race and ethnicity. CONCLUSIONS: Our initiative significantly reduced missing data by successfully leveraging ethnic background as the starting point of our REaL data collection.

Improving Atraumatic Chest Pain Evaluation in an Urban, Safety-net Hospital Through Incorporation of a Modified HEART Score.

Atraumatic chest pain is a common emergency department (ED) presentation and the American College of Cardiology and American Heart Association recommends stress testing within 72 hours. The HEART score predicts major adverse cardiac events (MACE) in ED populations and does not require universal stress testing. An evaluation based solely on history, electrocardiography, and biomarkers, therefore, is an attractive approach to risk stratification in resource-limited settings. The HEART score has not been previously evaluated in a safety net hospital setting. We therefore implemented an interdisciplinary clinical care guideline utilizing the HEART score to stratify patients presenting to our inner-city hospital. During a 6-month study period, 1170 patients were evaluated (521 before and 649 after implementation). Among the 998 patients with confirmed follow-up 6-weeks after the index ED encounter, the prevalence of MACE (all-cause mortality, acute myocardial infarction, or coronary revascularization) was 0% [95% confidence interval (CI), 0%-1%] for low, 9% (95% CI, 7%-12%) for moderate, and 52% (95% CI, 39%-65%) for high-risk groups. Guideline implementation significantly increased admissions (+12%, 95% CI, 7%-17%) primarily in the moderate risk group (+38%, 95% CI, 29%-47%), but significantly decreased median ED length of stay (-37 minutes, 95% CI, 17-58). It also led to an increase in stress testing among moderate and high-risk patients (+10%, 95% CI, 0%-19%). In conclusion, the HEART score effectively stratified risk of MACE in a safety net population, improved evaluation consistency, and decreased ED length of stay. However, implementation was associated with an increase in hospitalizations and stress testing. Although the American Heart Association/American College of Cardiology guideline regarding atraumatic chest pain in the ED recommends universal noninvasive testing, the value of this approach, particularly in conjunction with the HEART score is uncertain in safety net hospitals. Further evaluation of the costs and clinical advantages of this approach are warranted.