The National Institute on Minority Health and Health Disparities (NIMHD) has developed a framework to guide and orient research into health disparities and minority health. The framework depicts different domains of influence (such as biological and behavioral) and different levels of influence (such as individual and interpersonal). Here, influenced by the “One Health” approach, we propose adding two new levels of influence – interspecies and planetary – to this framework to reflect the interconnected nature of human, animal, and environmental health. Extending the framework in this way will help researchers to create new avenues of inquiry and encourage multidisciplinary collaborations. We then use the One Health approach to discuss how the COVID-19 pandemic has exacerbated health disparities, and show how the expanded framework can be applied to research into health disparities related to antimicrobial resistance and obesity.

Objective: To evaluate the impact of implementing clinical decision support (CDS) tools for outpatient antibiotic prescribing in the emergency department (ED) and clinic settings. Design: We performed a before-and-after, quasi-experimental study that employed an interrupted time-series analysis. Setting: The study institution was a quaternary, academic referral center in Northern California. Participants: We included prescriptions for patients in the ED and 21 primary-care clinics within the same health system. Intervention: We implemented a CDS tool for azithromycin on March 1, 2020, and a CDS tool for fluoroquinolones (FQs; ie, ciprofloxacin, levofloxacin, and moxifloxacin) on November 1, 2020. The CDS added friction to inappropriate ordering workflows while adding health information technology (HIT) features to easily perform recommended actions. The primary outcome was the number of monthly prescriptions for each antibiotic type, by implementation period (before vs after). Results: Immediately after azithromycin-CDS implementation, monthly rates of azithromycin prescribing decreased significantly in both the ED (−24%; 95% CI, −37% to −10%; P < .001) and outpatient clinics (−47%; 95% CI, −56% to −37%; P < .001). In the first month after FQ-CDS implementation in the clinics, there was no significant drop in ciprofloxacin prescriptions; however, there was a significant decrease in ciprofloxacin prescriptions over time (−5% per month; 95% CI, −6% to −3%; P < .001), suggesting a delayed effect of the CDS. Conclusion: Implementing CDS tools was associated with an immediate decrease in azithromycin prescriptions, in both the ED and clinics. CDS may serve as a valuable adjunct to existing antimicrobial stewardship programs.

Objective: We evaluated the effect of a behaviorally enhanced quality improvement intervention in reducing the number of antibiotic prescriptions written for antibiotic nonresponsive acute respiratory infections (ARIs). A secondary objective was identifying whether a reduction in inappropriate antibiotic prescriptions, if present, persisted after the immediate implementation of the intervention. Design: Nonrandomized, quasi-experimental study conducted from January 2017 through February 2020. Setting: University of California, Davis Health outpatient clinics. In total, 21 pediatric, family, and internal medicine practices in 10 cities and towns were included. Patients: Patients evaluated by a participating physician at an enrolled practice site during the study period with diagnoses (primary and secondary) from the International Classification of Diseases, Tenth Revision codes consistent with antibiotic nonresponsive ARI diagnoses. Intervention: A behaviorally enhanced quality improvement intervention to reduce inappropriate prescribing for antibiotic nonresponsive ARI. Results: In total, 63,028 eligible patient visits across 21 locations were included in the analysis. The most frequently prescribed antibiotic for antibiotic nonresponsive ARI was azithromycin (n = 3,551), followed by amoxicillin (n = 924). Overall, the intervention was associated with an immediate 46% reduction in antibiotic prescriptions for antibiotic nonresponsive ARI (P = .001) following the intervention. We detected no significant change in the month-to-month trend after the intervention was implemented (P = .87), indicating that the reduction was sustained throughout the postintervention period. Conclusion: Our findings demonstrate that a behaviorally enhanced quality improvement intervention to reduce inappropriate prescribing for antibiotic nonresponsive ARI in ambulatory care encounters was successful in reducing potentially inappropriate prescriptions for presumed antibiotic nonresponsive ARI.

Background: Where surveillance data are limited, nationally representative electronic health records allow for geographic, temporal, and demographic characterization of the fungal diseases blastomycosis and histoplasmosis. Methods: We identified incident blastomycosis and histoplasmosis cases from 2013 to 2023 within Oracle EHR Real-World Data, which comprises 1.6 billion healthcare encounters nationally. To characterize spatiotemporal incidence trends, we used generalized estimating equations weighted for nonrepresentativeness of electronic health record–reporting facilities. We computed standardized incidence rate ratios (sIRRs), which relay relative differences in standardized incidence rates between regions, race/ethnicity, gender, and age subgroups and the national population. Results: National incidence rates in 2023 were 2.4 (95% confidence interval [CI]: 1.6–3.5) and 1.9 times (95% CI: 1.6–2.2) rates in 2013, for blastomycosis and histoplasmosis, respectively. Blastomycosis incidence rates among Hispanic or Latino and non-Hispanic Black individuals were 60% (sIRR: 1.6 [95% CI: 1.0–2.4]) and 30% (sIRR: 1.3 [95% CI: 1.0–1.6]) higher than the standardized national incidence rate. Histoplasmosis incidence rates were elevated among non-Hispanic White patients (sIRR: 1.05 [95% CI: 1.02–1.08]). Standardized incidence rates of both diseases were higher among older and male patients, were consistently elevated in the Upper Midwest and Ohio Valley regions, and increased greatly in the Northern Rockies and Plains from 2013 to 2023. We estimated high incidence in states (blastomycosis: Illinois, Kentucky, and West Virginia; histoplasmosis: Missouri, Iowa, and Oklahoma) that do not report to surveillance. Conclusions: This analysis revealed increasing incidence rates of blastomycosis and histoplasmosis, with increasing diagnoses outside of historically endemic regions, and notable differences in incidence by race/ethnicity, gender, and age.

Poverty is an often-cited driver of health disparities, and associations between poverty and community-acquired Methicillin-resistant Staphylococcus aureus (CA-MRSA) infection are well documented. However, the pathways through which poverty influences infection have not been thoroughly examined. This project aims to identify mediating variables, or mechanisms, explaining why area-level poverty is associated with CA-MRSA infection in Californians. Bayesian multilevel models accounting for spatial confounding were developed to test whether the association between area-level poverty and CA-MRSA infection is mediated by living in a primary care shortage area (HCSA), living near an adult correctional facility, and residential environmental degradation. The association between area-level poverty and CA-MRSA infection can be partially explained by spatial autocorrelation, living in an HCSA, and environmental degradation in the neighborhood. Combined, the mediators explain approximately 6% of the odds of CA-MRSA infection for individuals living in neighborhoods with high poverty rates and 50% of the statistical association between area-level poverty and CA-MRSA infection. The statistical association between area-level poverty and infection was completely explained by the mediators for individuals living in neighborhoods with low poverty rates.

Weaned dairy heifers are a relatively understudied production group. Bovine respiratory disease (BRD) is the most common cause of antimicrobial drug (AMD) use, morbidity, and mortality in this production group. The study of antimicrobial resistance (AMR) is complicated because many variables that may affect AMR are related. This study generates hypotheses regarding the farm- and animal-level variables (e.g., vaccination, lane cleaning, and AMD use practices) that may be associated with AMR in respiratory isolates from weaned dairy heifers. A cross-sectional study was performed using survey data and respiratory isolates (Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni) collected from 341 weaned dairy heifers on six farms in California. Logistic regression and Bayesian network analyses were used to evaluate the associations between farm- and animal-level variables with minimum inhibitory concentration (MIC) classification of respiratory isolates against 11 AMDs. Farm-level variables associated with MIC classification of respiratory isolates included the number of source farms of a calf-rearing facility, whether the farm practiced onsite milking, the use of lagoon water for flush lane cleaning, and respiratory and pinkeye vaccination practices. Animal-level variables associated with a MIC classification included whether the calf was BRD-score-positive and time since the last phenicol treatment.