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.

The neighborhood built environment and COVID-19 hospitalizations.

Research on the associations between the built environment and COVID-19 outcomes has mostly focused on incidence and mortality. Also, few studies on the built environment and COVID-19 have controlled for individual-level characteristics across large samples. In this study, we examine whether neighborhood built environment characteristics are associated with hospitalization in a cohort of 18,042 individuals who tested positive for SARS-CoV-2 between May and December 2020 in the Denver metropolitan area, USA. We use Poisson models with robust standard errors that control for spatial dependence and several individual-level demographic characteristics and comorbidity conditions. In multivariate models, we find that among individuals with SARS-CoV-2 infection, those living in multi-family housing units and/or in places with higher particulate matter (PM2.5) have a higher incident rate ratio (IRR) of hospitalization. We also find that higher walkability, higher bikeability, and lower public transit access are linked to a lower IRR of hospitalization. In multivariate models, we did not find associations between green space measures and the IRR of hospitalization. Results for non-Hispanic white and Latinx individuals highlight substantial differences: higher PM2.5 levels have stronger positive associations with the IRR of hospitalization for Latinx individuals, and density and overcrowding show stronger associations for non-Hispanic white individuals. Our results show that the neighborhood built environment might pose an independent risk for COVID-19 hospitalization. Our results may inform public health and urban planning initiatives to lower the risk of hospitalization linked to COVID-19 and other respiratory pathogens.

Reducing Interruptive Alert Burden Using Quality Improvement Methodology.

BACKGROUND: Increased adoption of electronic health records (EHR) with integrated clinical decision support (CDS) systems has reduced some sources of error but has led to unintended consequences including alert fatigue. The "pop-up" or interruptive alert is often employed as it requires providers to acknowledge receipt of an alert by taking an action despite the potential negative effects of workflow interruption. We noted a persistent upward trend of interruptive alerts at our institution and increasing requests for new interruptive alerts. OBJECTIVES: Using Institute for Healthcare Improvement (IHI) quality improvement (QI) methodology, the primary objective was to reduce the total volume of interruptive alerts received by providers. METHODS: We created an interactive dashboard for baseline alert data and to monitor frequency and outcomes of alerts as well as to prioritize interventions. A key driver diagram was developed with a specific aim to decrease the number of interruptive alerts from a baseline of 7,250 to 4,700 per week (35%) over 6 months. Interventions focused on the following key drivers: appropriate alert display within workflow, clear alert content, alert governance and standardization, user feedback regarding overrides, and respect for user knowledge. RESULTS: A total of 25 unique alerts accounted for 90% of the total interruptive alert volume. By focusing on these 25 alerts, we reduced interruptive alerts from 7,250 to 4,400 per week. CONCLUSION: Systematic and structured improvements to interruptive alerts can lead to overall reduced interruptive alert burden. Using QI methods to prioritize our interventions allowed us to maximize our impact. Further evaluation should be done on the effects of reduced interruptive alerts on patient care outcomes, usability heuristics on cognitive burden, and direct feedback mechanisms on alert utility.

Multidrug-Resistant Bovine Salmonellosis Predisposing for Severe Human Clostridial Myonecrosis.

BACKGROUND The overuse of antibiotics in animals promotes the development of multidrug-resistance predisposing for severe polymicrobial human infections. CASE REPORT We describe a case of spontaneous clostridial myonecrosis due to ulcerative colonic infection with multidrug-resistant Salmonella enterica subsp. enterica, serotype 4,[5],12: i: -. Serotyping of the colonic Salmonella isolate in the index case and the bovine farm outbreak isolates from where the patient worked indicated they were both serotype I 4,[5],12: i: -, which is linked with a multitude of large reported disease outbreaks. Further analysis revealed that they are highly genetically related and antibiotic susceptibility testing indicated that they are phenotypically identical. CONCLUSIONS Enteritis due to human acquisition of multidrug-resistant Salmonella from cattle led to the invasion and dissemination of Clostridium septicum resulting in devastating myonecrotic disease. This highlights the ramifications of co-existence and evolution of pathogenic bacteria in animals and humans and lends support to reducing the use of antibiotics in animals.

A Novel Rapidly Growing Mycobacterium Species Causing an Abdominal Cerebrospinal Fluid Pseudocyst Infection.

Nontuberculous mycobacteria (NTM) are a rare cause of ventriculoperitoneal shunt infections. We describe the isolation and identification of a novel, rapidly growing, nonpigmented NTM from an abdominal cerebrospinal fluid pseudocyst. The patient presented with fevers, nausea, and abdominal pain and clinically improved after shunt removal. NTM identification was performed by amplicon and whole-genome sequencing.