As antibiotic resistance transformed into a global public health emergency, resources based on real world electronic health record (EHR) data were essential for the development of tools that can identify clinical intervention opportunities. We developed the Antimicrobial Resistance Microbiological Dataset (ARMD-UTSW), a standardized, deidentified collection of records from a large, urban, quaternary health system. ARMD-UTSW includes longitudinal microbiological culture results, patient demographics, diagnoses and comorbidities, medications, infections, and laboratory results from over 200,000 patients from 2005 to 2025. By standardizing data values such as gender, age ranges, organisms, culture types, and medication names, researchers can apply a variety of analytic methods with minimal data transformation. Details surrounding the deidentification and standardization of the dataset are included in the accompanying documentation. The goal of this paper is to share our dataset with others as the dissemination of our real-world clinical data will advance understanding of the growing problem of antibiotic resistance and ways to combat it.

To investigate the association between social determinants of health (SDoH), mental health history, and the propensity of firearm usage in suicide in the United States from 2003 to 2022. Using retrospective data from the National Violent Death Reporting System, we analyzed 348,112 suicide deaths, identifying differences in circumstantial, sociodemographic and mental health characteristics across those who used firearms versus other lethal methods. Documentation of any adverse health care access SDoH or adverse social context-related SDoH was significantly associated with increased odds of suicide by firearm (adjusted odds ratio [aOR] = 1.88 and 1.45, respectively) while any adverse neighborhood and built environment SDoH was inversely associated (aOR = 0.49). Decedents of suicide by firearm were less likely to have documented mental health problems (aOR = 0.83), to have recently received mental health treatment or have a prior suicide attempt (aOR = 0.50) compared to non-firearm suicides, though rates of depressed mood were similar (32.86

BACKGROUND:Carbapenem-resistant Enterobacterales (CRE) present a threat to global public health systems, yet the environmental contribution to antibiotic resistance prevalence has been understudied. The risk of antibiotic-resistant bacterium proliferating may be greater in neighborhoods experiencing environmental injustice (e.g., contaminated water, housing density). We examine spatial correlations between CRE detection rates and the Environmental Justice Index (EJI) across census tracts in an urban county. METHODS:We analyzed data from electronic health records of two major health systems from 2015-2020. Using global spatial autocorrelation tests (i.e., Global Moran's Index) and bivariate spatial lag regression models we analyzed the association of EJI components and local CRE rates. FINDINGS:The overall EJI exhibited significant clustering in the study area (Moran's I = 0.51) and a strong positive association with local CRE positive culture rates (β = 0.44, SE = 0.10). The health vulnerability domain of the EJI (e.g., chronic disease burden) demonstrated the strongest association with CRE rates (β = 0.75, SE = 0.13). Measures of built environment (β = 0.42, SE = 0.16), water pollution (β = 0.41, SE = 0.11), housing type (β = 0.34, SE = 0.13) and housing characteristics (β = 0.41, SE = 0.10) displayed significantly strong associations with local CRE positive culture rates. INTERPRETATION:These findings highlight the complex interplay between environmental conditions, social determinants, and health outcomes, indicating that areas with poor environmental quality and higher social vulnerability exhibited elevated CRE positive rates. This emphasizes the potential relevance of environmental and social disparities to antibiotic-resistant organism burden such as CRE.

The Centers for Disease Control and Prevention has raised national alarm over five Antimicrobial Resistant Organisms (AMROs) considered urgent or serious threats to public safety. Understanding the prevalence and distribution of AMROs at a local level can inform the unique infection risks facing our communities. We conducted a retrospective, spatiotemporal analysis of AMRO prevalence across Tarrant County, Texas from 2010-2019. Using spatial autocorrelation tests, we identified that across five different AMRO subtypes, the Western half of Tarrant County experienced more hot spots than the Eastern half. Our Space-Time Permutation Models identified 35 unique AMRO clusters. Using logistic regression models, we found significant associations between Area Deprivation Index, a measure of socioeconomic disparity, and most AMRO clusters. These findings underscore the importance of residency location and temporal trends when treating and preventing AMRO infections.

We developed machine learning models to predict the presence of AMR organisms in blood cultures obtained at the first patient encounter, offering a new and inspiring direction for antimicrobial resistance management. Three supervised machine learning classifiers were used: penalized logistic regression, random forest, and XGBoost, which were used to classify five AMR organisms: ESBL, CRE, AmpC, MRSA, and VRE. The random forest and XGBoost models performed best, with AUC-ROC values of 0.70 and 92.9% negative predictive value, respectively. The multi-class random forest model's AUC-ROC values ranged from 0.80-0.95. Our models highlight how the combination of ADI and SVI increased the predictive power. This approach could reduce costs and mitigate the global public health threat posed by antibiotic-resistant infections. Machine learning techniques can predict antimicrobial-resistant infections in suspected cultures using patient data from EHRs, enabling clinicians to make targeted prescribing decisions and mitigate resistance development.

According to the uncertain geographic context problem, a lack of temporal information can hinder measures of bias in mortgage lending. This study extends previous methods to: (1) measure the persistence of racial bias in mortgage lending for Black Americans by adding temporal trends and credit scores, and (2) evaluate the continuity of bias in discriminatory areas from 1990 to 2020. These additions create an indicator of persistent structural housing discrimination. We studied the Boston-Cambridge-Newton and Dallas-Fort Worth metropolitan statistical areas to examine distinct historical trajectories and urban development. We estimated the odds of mortgage denial for census tracts. Overall, all tracts in Boston-Cambridge-Newton (N = 1003) and Dallas-Fort Worth (N = 1312) displayed significant change, with greater odds of bias over time in Dallas-Fort Worth and lower odds in Boston-Cambridge-Newton. Historically redlined areas displayed the strongest persistence of bias. Results suggest that temporal data can identify persistence and improve sensitivity in measuring neighborhood bias. Understanding the temporality of residential exposure can increase research rigor and inform policy to reduce the health effects of racial bias.

Background The increased prevalence of antimicrobial-resistant (AMR) infections is a significant global health threat, resulting in increased disease, deaths, and costs. The drivers of AMR are complex and potentially impacted by socioeconomic factors. We investigated the relationships between geographic and socioeconomic factors and AMR.Methods We collected select patient bacterial culture results from 2015 to 2020 from electronic health records of 2 expansive healthcare systems within the Dallas-Fort Worth, Texas, metropolitan area. Among individuals with electronic health records who resided in the 4 most populous counties in Dallas-Fort Worth, culture data were aggregated. Case counts for each organism studied were standardized per 1000 persons per area population. Using residential addresses, the cultures were geocoded and linked to socioeconomic index values. Spatial autocorrelation tests identified geographic clusters of high and low AMR organism prevalence and correlations with established socioeconomic indices.Results We found significant clusters of AMR organisms in areas with high levels of deprivation, as measured by the area deprivation index (ADI). We found a significant spatial autocorrelation between ADI and the prevalence of AMR organisms, particularly for AmpC beta-lactamase and methicillin-resistant Staphylococcus aureus, with 14% and 13%, respectively, of the variability in prevalence rates being attributable to their relationship with the ADI values of the neighboring locations.Conclusions We found that areas with a high ADI are more likely to have higher rates of AMR organisms. Interventions that improve socioeconomic factors such as poverty, unemployment, decreased access to healthcare, crowding, and sanitation in these areas of high prevalence may reduce the spread of AMR. Antimicrobial resistance (AMR) and its spread poses a significant threat to health worldwide. By identifying locations with high AMR prevalence through geospatial analyses, we discovered patterns of co-occurrence between socioeconomic factors, indicated by the area deprivation index, and AMR prevalence.

Background and Aims: The two most common interventions used to treat painless jaundice from pancreatic cancer are endoscopic retrograde cholangiopancreatography (ERCP) and percutaneous transhepatic biliary drainage (PTBD). Our study aimed to characterize the geographic distribution of ERCP-performing hospitals among patients with pancreatic cancer in the United States and the association between geographic accessibility to ERCP-performing hospitals and biliary interventions patients receive. Methods: This is a retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER)-Medicare database for pancreatic cancer from 2005 to 2013. Multilevel models were used to examine the association between accessibility to ERCP hospitals within a 30- and 45-min drive from the patient's residential ZIP Code and the receipt of ERCP treatment. A two-step floating catchment area model was used to calculate the measure of accessibility based on the distribution across SEER regions. Results: 7464 and 782 patients underwent ERCP and PTBD, respectively, over the study period. There were 808 hospitals in which 8246 patients diagnosed with pancreatic cancer in SEER regions from 2005 to 2013 received a procedure. Patients with high accessibility within both 30- and 45-min drive to an ERCP-performing hospital were more likely to receive an ERCP (30-min adjusted odds ratio [aOR]: 1.53, 95% confidence interval [CI]: 1.17-2.01; 45-min aOR: 1.31, 95% CI: 1.01-1.70). Furthermore, in the adjusted model, Black patients (vs. White) and patients with stage IV disease were less likely to receive ERCP than PTBD. Conclusions: Patients with pancreatic cancer and high accessibility to an ERCP-performing hospital were more likely to receive ERCP. Disparities in the receipt of ERCP persisted for Black patients regardless of their access to ERCP-performing hospitals.

BACKGROUND:Firearm-related injury represents a significant public health problem in the USA. Firearm purchasing has risen nationwide and there has been increased efforts to deploy injury prevention initiatives within gun establishments. However, firearm-related risks and harms that may occur inside these high-exposure settings are not well characterized. METHODS:This secondary analysis leveraged Gun Violence Archive data to quantify firearm injury prevalence rates within different types of gun establishments from 1 January 2015 to 31 December 2022. Data were restricted to incidents that occurred in gun ranges, gun shops, and public and private ranges. The following incident characteristics were available in the individual-level data: date, location, injury count, fatality count, victim demographics (age, sex), shooting intent (suicide/self-inflicted, assault/homicide, unintentional, undetermined) and establishment type. RESULTS:Over 7 years, 445 non-fatal and 183 fatal shooting events occurred across 576 unique establishments. Non-fatal, unintentional injuries predominated in stand-alone firing ranges whereas fatal, self-inflicted injuries concentrated in retail shops with accompanying firing ranges. Firearm-related assaults were prevalent among stand-alone retail shops. CONCLUSION:Overall, this secondary analysis underscores that the prevalence of firearm injury in gun establishments across the USA is low, and these settings should continue to be studied as important contexts for intervention. Interweaving public health interventions into gun establishments presents an opportunity to potentially reduce associated harms to consumers interacting within these environments.

Minority populations will continue to grow in the United States. Such pluralism necessitates iterative, geospatial measurements of cultural contexts. Our objective in this study was to create a measure of social determinants of health in geographic areas with varying ethnic, linguistic, and religious diversity in the United States. We extracted geographic information systems data based on community characteristics that have known associations with population health disparities from 2015 to 2019. We used principal component analysis to construct a Cultural Context Index (CCI). We created the CCI for 73,682 census tracts across 50 states and five inhabited territories. We identified hot and cold spots that are the highest and lowest CCI quintile, respectively. Hot spots census tracts were mostly located in metropolitan areas (84.8%), in the Southern census region (41.5%), and also had larger Black and Hispanic populations. The census tracts with the greatest need for culturally competent health care also had the sickest populations. Census tracts with a CCI rank of 5 (‘greatest need’) had higher prevalences of self-reported poor physical health (17.2%) and poor mental health (17.4%), compared to either the general population (13.9% and 14.5%) or to CCI rank of 1 (‘lowest need’) (11.9% and 10.8%). The CCI can pinpoint census tracts with a need for culturally competent health care and inform supply-side policy planning as healthcare and social service providers will inevitably come in contact with consumers from different backgrounds.

INTRODUCTION:The purpose of this study is to examine the associations of neighborhood socioeconomic status, ethnic enclaves, and residential Black segregation with screening for breast, cervical, and colorectal cancers across the state of Texas. METHODS:Using an ecologic study design, spatial clustering of low breast, cervical and colorectal cancer screening rates were identified across Texas census tracts using local Moran's I statistics. Binomial spatial probit regression was used to estimate the associations between nSES, Hispanic/Latino and Asian American ethnic enclave neighborhoods and residential Black segregation with geospatial clusters of low screening, adjusting for behavioral characteristics. Analysis was conducted in 2024. RESULTS:Of 5,186 tracts, 5.4%, 4.6%, and 8.7% tracts were in low screening clusters for colorectal, cervical, and breast cancer, respectively. Medium and high neighborhood socioeconomic status tracts had reduced odds of being part of low cervical cancer screening clusters. Medium neighborhood socioeconomic status tracts and Hispanic enclave tracts had increased odds of being within a low breast cancer screening cluster. Asian American enclave tracts displayed an increased odds of being in low colorectal cancer and low cervical cancer screening clusters. Tracts with high residential Black segregation demonstrated reduced odds of being in low colorectal cancer and low breast cancer screening clusters. CONCLUSIONS:Geospatial clusters of screening uptake are associated with neighborhood socioeconomic status and racial and ethnic neighborhood characteristics. This indicates a need for place-based culturally sensitive interventions to address the specific assets and needs of communities with low screening uptake.

Differences in violent victimization and screening implementation across demographic groups expand the health disparities gap for persons of color. This study evaluated disparities across racial/ethnic identities and languages by comparing the prevalence of types of violence against persons (VAP) and assessing screening/referral patterns of a safety-net patient population. The sample included patients with an emergency department visit during VAP screening protocol implementation in January-July, 2021. Electronic health records were used to assess screening rates and victim services utilization with univariate and bivariate statistics across patient characteristics. Seventy-one percent (71.19%) of encounters (n = 45,376) across 63,737 unique adults were screened for VAR Most patients screened were Hispanic (52.02%) and English was the most common language spoken (65.74%). Two percent of encounters had a positive screen for VAP (n = 1,312). Spanish-speaking patients were more likely to agree to engage in victim services. Hispanic and Spanish-speaking patients had the greatest odds of screening positive across all types of victimization compared to NonHispanic white. Black patients had higher odds of nursing staff indicating an appearance-based (OR = 3.42) and injury-based (OR = 2.14) sign of abuse. Addressing disparities in screening/ referral processes can aid in identifying missed victims and improving access to services amongst diverse communities within healthcare settings.

Background Social connectedness decreases human mortality, improves cancer survival, cardiovascular health, and body mass, results in better-controlled glucose levels, and strengthens mental health. However, few public health studies have leveraged large social media data sets to classify user network structure and geographic reach rather than the sole use of social media platforms. Objective The objective of this study was to determine the association between population-level digital social connectedness and reach and depression in the population across geographies of the United States. Methods Our study used an ecological assessment of aggregated, cross-sectional population measures of social connectedness, and self-reported depression across all counties in the United States. This study included all 3142 counties in the contiguous United States. We used measures obtained between 2018 and 2020 for adult residents in the study area. The study’s main exposure of interest is the Social Connectedness Index (SCI), a pair-wise composite index describing the “strength of connectedness between 2 geographic areas as represented by Facebook friendship ties.” This measure describes the density and geographical reach of average county residents’ social network using Facebook friendships and can differentiate between local and long-distance Facebook connections. The study’s outcome of interest is self-reported depressive disorder as published by the Centers for Disease Control and Prevention. Results On average, 21% (21/100) of all adult residents in the United States reported a depressive disorder. Depression frequency was the lowest for counties in the Northeast (18.6%) and was highest for southern counties (22.4%). Social networks in northeastern counties involved moderately local connections (SCI 5-10 the 20th percentile for n=70, 36% of counties), whereas social networks in Midwest, southern, and western counties contained mostly local connections (SCI 1-2 the 20th percentile for n=598, 56.7%, n=401, 28.2%, and n=159, 38.4%, respectively). As the quantity and distance that social connections span (ie, SCI) increased, the prevalence of depressive disorders decreased by 0.3% (SE 0.1%) per rank. Conclusions Social connectedness and depression showed, after adjusting for confounding factors such as income, education, cohabitation, natural resources, employment categories, accessibility, and urbanicity, that a greater social connectedness score is associated with a decreased prevalence of depression.

First responders are routinely exposed to traumatic events that can affect their mental health to the extent of suicidal ideation and suicide completion. The purpose of our study is to inform the comparability of predictors of suicidality across first responder types to elucidate the most efficacious targets for intervention and clinical intercession. Clients (N = 224) sought counseling services between 2015 and 2020 at a not-for-profit organization. We conducted a matched study with cases defined as those with suicidality at baseline and those without suicidality at baseline (controls). First responder types were law enforcement officers (LEOs), firefighters, and emergency medical technicians. Clients were mostly LEOs (41.5%), followed by firefighters (29.9%) and emergency medical technicians (28.6%). Logistic regression models tested the relationship between mental health measures and suicidality. All measures of mental health constructs varied significantly across those with or without suicidality and differed across first responder subtype. Depression and posttraumatic stress disorder were significant predictors of suicidality for both LEOs and firefighters. Alcohol/substance misuse was only a significant predictor among LEOs. Resilience was a protective factor for both LEOs and emergency medical technicians. Specific differences in predictors of suicidality across first responder subtypes may enable occupation-specific targets for mental healthcare.

Background Law enforcement officers (LEOs) are exposed to chronic stress throughout the course of their shift, which increases the risk of adverse events. Although there have been studies targeting LEO safety through enhanced training or expanded equipment provisions, there has been little attempt to leverage personal technology in the field to provide real-time notification of LEO stress. This study tests the acceptability of implementing of a brief, smart watch intervention to alleviate stress among LEOs. Methods We assigned smart watches to 22 patrol LEOs across two police departments: one suburban department and one large, urban department. At baseline, we measured participants’ resting heart rates (RHR), activated their watches, and educated them on brief wellness interventions in the field. LEOs were instructed to wear the watch during the entirety of their shift for 30 calendar days. When LEO’s heart rate or stress continuum reached the predetermined threshold for more than 10 min, the watch notified LEOs, in real time, of two stress reduction interventions: [1] a 1-min, guided breathing exercise; and [2] A Calm app, which provided a mix of guided meditations and mindfulness exercises for LEOs needing a longer decompression period. After the study period, participants were invited for semi-structured interviews to elucidate intervention components. Qualitative data were analyzed using an immersion-crystallization approach. Results LEOs reported three particularly useful intervention components: 1) a vibration notification when hearts rates remained high, although receipt of a notification was highly variable; 2) visualization of their heart rate and stress continuum in real time; and, 3) breathing exercises. The most frequently reported type of call for service when the watch vibrated was when a weapon was involved or when a LEO was in pursuit of a murder suspect/hostage. LEOs also recollected that their watch vibrated while reading dispatch notes or while on their way to work. Conclusions A smart watch can deliver access to brief wellness interventions in the field in a manner that is both feasible and acceptable to LEOs.

Background: During the COVID-19 pandemic possible substance use disorders (SUD) were exacerbated from increased stress and isolation. Experiences of symptomology differ widely by occupations.Objectives: The objectives were to determine if there is a temporal relationship between COVID-19 vulnerability and possible SUDs among first responders, and to examine the association with neighborhood vulnerability.Methods: We conducted an analysis with two distinct cohorts dependent on time of entry: 1) First responders that began counseling prior to COVID-19 and 2) First responders that began counseling after the start of COVID-19. Data were collected at intake from first responders seeking mental health services between 2017 and 2021 at an organization in Dallas/Fort Worth, Texas. The study sample included 195 mostly male (75%) first responders (51% law enforcement officers; 49% emergency medical technicians/firefighters). Bivariate models tested unadjusted relationships between covariates and possible SUD. Adjusted models consisted of a two-level multivariable logistic regression models.Results: Nearly 40% (n = 77) screened positive for a possible SUD. Those beginning counseling after COVID-19 did not have higher odds of SUDs. For every unit increase in neighborhood Severe COVID-19 Health Risk Index at a first responder's residential location there was an increase in the odds of a possible SUD (AOR = 3.14, 95% CI: 1.47, 6.75).Conclusions: Our study highlights the degree to which personal and residential vulnerability to COVID-19 impacted first responders. The increased occupational stress of this population, and an established pattern of maladaptive coping, elucidates the need for preventative and clinical approaches to strengthen the resilience of this population.

OBJECTIVE:Law enforcement officers (LEOs) are exposed to high levels of occupational trauma and face added stress from heightened public scrutiny and COVID-19, which may result in suicide. It is crucial to understand differences between LEOs who seek treatment and those who do not.METHOD:We compared LEOs from the same greater metropolitan area who sought treatment with those who did not. Participants completed validated measures assessing posttraumatic stress disorder, generalized anxiety, depression, and suicidality.RESULTS:The treatment-seeking sample scores were higher on all standardized assessments. Bivariate logistic regression results indicated that the non-treatment-seeking sample's odds of experiencing suicidality were 1.76 times the odds for the treatment seeking sample. Conclusions: This suggests that many LEOs experiencing suicidality may not be seeking treatment and highlights the role that posttraumatic stress disorder may play in determining whether LEOs seek treatment or not.

Statement of PurposeTo compare the prevalence of violence against persons (VAP) across racial/ethnic and primary language among patients seeking care at an integrated, safety-net hospital system.Methods/ApproachIn 2021, the largest safety-net emergency department (ED) in the United States implemented a trauma informed care model, which included systematic VAP screening (physical, sexual, psychological victimization, control of food/money, and observational signs of abuse [explicit, contextual, appearance, injury]) and strengthening referral pathways for victims. Patients who screened positive were referred to the Victim Intervention Program (VIP). Analysis of electronic health records used univariate and bivariate statistics to assess screening rates across sample characteristics.ResultsBetween January 1 to July 30, 2021, 66,125 encounters with 43,318 unique adults were screened for VAP. Of the patients screened, 52% were Hispanic and 33% were primary Spanish speakers. Two percent of encounters had a positive screen for VAP (n=1,265) and, of those seen by VIP 85.8% (n=1,175) received services. Of the positive screens, (76.4%) were physical victimization, followed by psychological (41.4%), sexual (33.5%) and control (19.9%). Hispanic patients and Spanish speakers had the greatest odds for any racial/ethnic group of screening positive for all types of victimization as well as all signs of abuse compared to NH white. Black patients had higher odds of appearance (OR=3.42) and injury-based (OR=2.14) signs of abuse. Among patients with multiple encounters, consistent positivity ranged from 1.7% to 100% (mean= 88.4%).ConclusionTrauma informed care implementation had the greatest benefit of detection among Hispanic ethnicity and Spanish speaking populations for all types of VAP. Victimization disparities across racial/ethnic groups is disproportionately identified in health systems.SignificanceAddressing disparities in screening processes can aid in identifying missed victims and improving access to services amongst our diverse communities.

OBJECTIVE To examine the prevalence and predictors of screening for violence against persons and victim service utilization within an integrated safety-net health system. STUDY SETTING Emergency Department (ED) at Parkland Hospital -- Dallas County's largest safety-net provider of services for minority and under-/un-insured patients. STUDY DESIGN Prospective, longitudinal study during the first six-months of a universal violence against persons screener. DATA COLLECTION Health records were extracted for all patients with a visit to the ED between January - July, 2021. Modeling described the patient population across screening (screened vs. not screened) and, among those screened, the results (positive vs. negative), average time spent in the ED, and referral patterns for victim services. PRINCIPAL FINDINGS 65,563 unique patients with 95,555 encounters occurred during the study period. Seventy-one percent (n= 67,535) were screened for violence against persons and, of those, 2% screened positive (n= 1,349). Of patients that screened positive, 1,178 (87%) were referred to and 806 (60%) received care at victim services. Implementing screening did not increase ED length of stay. CONCLUSIONS Systematic implementation of comprehensive violence screening at a safety-net system can result in a robust identification and timely referrals to victim services.

To evaluate how social stressors, organizational stressors, and physical strains are related to suicidal ideation (SI) at an urban police department. Data was gathered between January–February 2020. Each case of SI was matched to 4 controls based on age, gender and military experience for a total sample size of 110 officers. Conditional logistic regression models assessed the relationship between stress domains and SI. Five percent (5%) of the officers surveyed (n = 22) reported SI. After adjustment for sociodemographic characteristics, high levels of organizational stress, versus low organizational stress, were associated with 9.2 (95% CI: 1.1–75.8) times the odds of SI compared to no SI. In the fully adjusted model (i.e., sociodemographics and other stressors), medium and high levels of social stress showed 5.1 (95% CI: 1.1–23.5) and 3.8 (95% CI: 1.0–14.5) higher odds of SI compared to no SI. The likelihood of SI increased incrementally as higher number of stressors were reported, suggesting a significant dose-response relationship. This study found organizational and social stress were the strongest predictors of SI for law enforcement officers, as opposed to physical strain. This study serves to further inform the multi-dimensionality of police stress pathways to advise department psychological prevention efforts.