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Objective: To evaluate random effects of volume (patient days or device days) on healthcare-associated infections (HAIs) and the standardized infection ratio (SIR) used to compare hospitals. Design: A longitudinal comparison between publicly reported quarterly data (2014–2020) and volume-based random sampling using 4 HAI types: central-line–associated bloodstream infections, catheter-associated urinary tract infections, Clostridioides difficile infections, methicillin-resistant Staphylococcus aureus infections. Methods: Using 4,268 hospitals with reported SIRs, we examined relationships of SIRs to volume and compared distributions of SIRs and numbers of reported HAIs to the outcomes of simulated random sampling. We included random expectations into SIR calculations to produce a standardized infection score (SIS). Results: Among hospitals with volumes less than the median, 20%–33% had SIRs of 0, compared to 0.3%–5% for hospitals with volumes higher than the median. Distributions of SIRs were 86%–92% similar to those based on random sampling. Random expectations explained 54%–84% of variation in numbers of HAIs. The use of SIRs led hundreds of hospitals with more infections than either expected at random or predicted by risk-adjusted models to rank better than other hospitals. The SIS mitigated this effect and allowed hospitals of disparate volumes to achieve better scores while decreasing the number of hospitals tied for the best score. Conclusions: SIRs and numbers of HAIs are strongly influenced by random effects of volume. Mitigating these effects drastically alters rankings for HAI types and may further alter penalty assignments in programs that aim to reduce HAIs and improve quality of care.

Background Long-term symptoms following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are a major concern, yet their prevalence is poorly understood. Methods We conducted a prospective cohort study comparing adults with SARS-CoV-2 infection (coronavirus disease-positive [COVID+]) with adults who tested negative (COVID−), enrolled within 28 days of a Food and Drug Administration (FDA)-approved SARS-CoV-2 test result for active symptoms. Sociodemographic characteristics, symptoms of SARS-CoV-2 infection (assessed with the Centers for Disease Control and Prevention [CDC] Person Under Investigation Symptom List), and symptoms of post-infectious syndromes (ie, fatigue, sleep quality, muscle/joint pains, unrefreshing sleep, and dizziness/fainting, assessed with CDC Short Symptom Screener for myalgic encephalomyelitis/chronic fatigue syndrome) were assessed at baseline and 3 months via electronic surveys sent via text or email. Results Among the first 1000 participants, 722 were COVID+ and 278 were COVID−. Mean age was 41.5 (SD 15.2); 66.3% were female, 13.4% were Black, and 15.3% were Hispanic. At baseline, SARS-CoV-2 symptoms were more common in the COVID+ group than the COVID− group. At 3 months, SARS-CoV-2 symptoms declined in both groups, although were more prevalent in the COVID+ group: upper respiratory symptoms/head/eyes/ears/nose/throat (HEENT; 37.3% vs 20.9%), constitutional (28.8% vs 19.4%), musculoskeletal (19.5% vs 14.7%), pulmonary (17.6% vs 12.2%), cardiovascular (10.0% vs 7.2%), and gastrointestinal (8.7% vs 8.3%); only 50.2% and 73.3% reported no symptoms at all. Symptoms of post-infectious syndromes were similarly prevalent among the COVID+ and COVID− groups at 3 months. Conclusions Approximately half of COVID+ participants, as compared with one-quarter of COVID− participants, had at least 1 SARS-CoV-2 symptom at 3 months, highlighting the need for future work to distinguish long COVID. Clinical Trials Registration NCT04610515.

Electronic health records (EHRs) offer opportunities for research and improvements in patient care. However, challenges exist in using data from EHRs due to the volume of information existing within clinical notes, which can be labor intensive and costly to transform into usable data with existing strategies. This case report details the collaborative development and implementation of the postencounter form (PEF) system into the EHR at the Road Home Program at Rush University Medical Center in Chicago, IL to address these concerns with limited burden to clinical workflows. The PEF system proved to be an effective tool with over 98% of all clinical encounters including a completed PEF within 5 months of implementation. In addition, the system has generated over 325,188 unique, readily-accessible data points in under 4 years of use. The PEF system has since been deployed to other settings demonstrating that the system may have broader clinical utility.

Long-term sequelae after symptomatic SARS-CoV-2 infection may impact well-being, yet existing data primarily focus on discrete symptoms and/or health care use.To compare patient-reported outcomes of physical, mental, and social well-being among adults with symptomatic illness who received a positive vs negative test result for SARS-CoV-2 infection.This cohort study was a planned interim analysis of an ongoing multicenter prospective longitudinal registry study (the Innovative Support for Patients With SARS-CoV-2 Infections Registry [INSPIRE]). Participants were enrolled from December 11, 2020, to September 10, 2021, and comprised adults (aged ≥18 years) with acute symptoms suggestive of SARS-CoV-2 infection at the time of receipt of a SARS-CoV-2 test approved by the US Food and Drug Administration. The analysis included the first 1000 participants who completed baseline and 3-month follow-up surveys consisting of questions from the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29; 7 subscales, including physical function, anxiety, depression, fatigue, social participation, sleep disturbance, and pain interference) and the PROMIS Short Form-Cognitive Function 8a scale, for which population-normed T scores were reported.SARS-CoV-2 status (positive or negative test result) at enrollment.Mean PROMIS scores for participants with positive COVID-19 tests vs negative COVID-19 tests were compared descriptively and using multivariable regression analysis.Among 1000 participants, 722 (72.2%) received a positive COVID-19 result and 278 (27.8%) received a negative result; 406 of 998 participants (40.7%) were aged 18 to 34 years, 644 of 972 (66.3%) were female, 833 of 984 (84.7%) were non-Hispanic, and 685 of 974 (70.3%) were White. A total of 282 of 712 participants (39.6%) in the COVID-19-positive group and 147 of 275 participants (53.5%) in the COVID-19-negative group reported persistently poor physical, mental, or social well-being at 3-month follow-up. After adjustment, improvements in well-being were statistically and clinically greater for participants in the COVID-19-positive group vs the COVID-19-negative group only for social participation (β = 3.32; 95% CI, 1.84-4.80; P .001); changes in other well-being domains were not clinically different between groups. Improvements in well-being in the COVID-19-positive group were concentrated among participants aged 18 to 34 years (eg, social participation: β = 3.90; 95% CI, 1.75-6.05; P .001) and those who presented for COVID-19 testing in an ambulatory setting (eg, social participation: β = 4.16; 95% CI, 2.12-6.20; P .001).In this study, participants in both the COVID-19-positive and COVID-19-negative groups reported persistently poor physical, mental, or social well-being at 3-month follow-up. Although some individuals had clinically meaningful improvements over time, many reported moderate to severe impairments in well-being 3 months later. These results highlight the importance of including a control group of participants with negative COVID-19 results for comparison when examining the sequelae of COVID-19.

Finding, accessing, sharing, and analyzing patient data from a clinical setting for collaborative research has continually proven to be a challenge in healthcare organizations. The human and technological architecture required to perform these services exist at the largest academic institutions but are usually under-funded. At smaller, less academically focused healthcare organizations across the United States, where the majority of care is delivered, they are generally absent. Here we propose a solution called the Learning Healthcare System Data Commons where cost is usage-based and the most basic elements are designed to be extensible, allowing it to evolve with the changing landscape of healthcare. Herein we also discuss our reference implementation of this platform tailored specifically for operational sustainability and governance using the data generated in a hospital setting for research, quality, and educational purposes.

Objective We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing COVID-19 pandemic. Materials and Methods Our application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from seven COVID-19 models, customize 23 parameters, examine trends in testing and hospitalization, and download forecast data. Results Our application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others. Discussion Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study. Conclusion Empowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need. Lay Summary Hospitals have been continually faced with anticipating the resurgent spread of COVID-19 and its effects on visits, admissions, bed needs, and crucial supplies. However, few open source tools are available to aid hospitals in planning. We developed a web application (https://rush-covid19.herokuapp.com/) for US states and territories to predict the spread of COVID-19 and to provide forecasts for hospital visits, admissions, discharges and to anticipate needs for ICU and non-ICU beds, ventilators, and personal protective equipment. Users can choose from a suite of models to predict the spread of COVID-19, some of which explain > 99% of variation in COVID-19 cases within states. Users can modify a large set of inputs to obtain forecasts for their institution, examine variability in forecasts over time, download forecast data for further analysis, and explore trends in hospitalization and testing. We designed our application to be interactive, insightful, and easy to use for hospital leaders, healthcare workers, and government officials. However, specialists can use our models, open source code, and aggregated data for deeper study. As the dynamics of COVID-19 change, our application will also change to meet emerging needs of the healthcare community.

Background Disease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards. Objective We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources. Methods Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems—a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds. Results Data from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. Conclusions We described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.

Methicillin-resistant Staphylococcus aureus (MRSA) is a leading cause of health care-associated (HA) and community-associated (CA) infections. USA300 strains are historically CA-MRSA, while USA100 strains are HA-MRSA. Here, we update an antibiotic prediction rule to distinguish these two genotypes based on antibiotic resistance phenotype using whole-genome sequencing (WGS), a more discriminatory methodology than pulsed-field gel electrophoresis (PFGE). MRSA clinical isolates collected from 2007 to 2017 underwent WGS; associated epidemiologic data were ascertained. In developing the rule, we examined MRSA isolates that included a population with a history of incarceration. Performance characteristics of antibiotic susceptibility for predicting USA300 compared to USA100, as defined by WGS, were examined. Phylogenetic analysis was performed to examine resistant USA300 clades. We identified 275 isolates (221 USA300, 54 USA100). Combination susceptibility to clindamycin or levofloxacin performed the best overall (sensitivity 80.7%, specificity 75.9%) to identify USA300. The average number of antibiotic classes with resistance was higher for USA100 (3 versus 2, P < 0.001). Resistance to ≤2 classes was predictive for USA300 (area under the curve (AUC) 0.84, 95% confidence interval 0.78 to 0.90). Phylogenetic analysis identified a cluster of USA300 strains characterized by increased resistance among incarcerated individuals. Using a combination of clindamycin or levofloxacin susceptibility, or resistance to ≤2 antibiotic classes, was predictive of USA300 as defined by WGS. Increased resistance was observed among individuals with incarceration exposure, suggesting circulation of a more resistant USA300 clade among at-risk community networks. Our phenotypic prediction rule could be used as an epidemiologic tool to describe community and nosocomial shifts in USA300 MRSA and quickly identify emergence of lineages with increased resistance. IMPORTANCE Methicillin-resistant Staphylococcus aureus (MRSA) is an important cause of health care-associated (HA) and community-associated (CA) infections, but the epidemiology of these strains (USA100 and USA300, respectively) now overlaps in health care settings. Although sequencing technology has become more available, many health care facilities still lack the capabilities to perform these analyses. In this study, we update a simple prediction rule based on antibiotic resistance phenotype with integration of whole-genome sequencing (WGS) to predict strain type based on antibiotic resistance profiles that can be used in settings without access to molecular strain typing methods. This prediction rule has many potential epidemiologic applications, such as analysis of retrospective data sets, regional monitoring, and ongoing surveillance of CA-MRSA infection trends. We demonstrate application of this rule to identify an emerging USA300 strain with increased antibiotic resistance among incarcerated individuals that deviates from the rule.

Background Jails may facilitate spread of methicillin-resistant Staphylococcus aureus (MRSA) in urban areas. We examined MRSA colonization upon entrance to a large urban jail to determine if there are MRSA transmission networks preceding incarceration. Methods Males incarcerated in Cook County Jail (Chicago) were enrolled, with enrichment for people living with human immunodeficiency virus (PLHIV), within 72 hours of intake. Surveillance cultures assessed prevalence of MRSA colonization. Whole-genome sequencing (WGS) identified preincarceration transmission networks. We examined methicillin-resistant Staphylococcus aureus (MRSA) isolates to determine if there are transmission networks that precede incarceration. A large proportion of individuals enter jail colonized with MRSA. Molecular epidemiology and colonization risk factors provide clues to community reservoirs for MRSA. Results There were 718 individuals (800 incarcerations) enrolled; 58% were PLHIV. The prevalence of MRSA colonization at intake was 19%. In multivariate analysis, methamphetamine use, unstable housing, current/recent skin infection, and recent injection drug use were predictors of MRSA. Among PLHIV, recent injection drug use, current skin infection, and HIV care at outpatient clinic A that emphasizes comprehensive care to the lesbian, gay, bisexual, transgender community were predictors of MRSA. Fourteen (45%) of 31 detainees with care at clinic A had colonization. WGS revealed that this prevalence was not due to clonal spread in clinic but rather to an intermingling of distinct community transmission networks. In contrast, genomic analysis supported spread of USA500 strains within a network. Members of this USA500 network were more likely to be PLHIV (P < .01), men who have sex with men (P < .001), and methamphetamine users (P < .001). Conclusions A large proportion of individuals enter jail colonized with MRSA. Molecular epidemiology and colonization risk factors provide clues to identify colonized detainees entering jail and potential community reservoirs of MRSA.

BackgroundUS hospital safety is routinely measured via patient safety indicators (PSIs). Receiving a score for most PSIs requires a minimum number of qualifying cases, which are partly determined by whether the associated diagnosis-related group (DRG) was surgical and whether the surgery was elective. While these criteria can exempt hospitals from PSIs, it remains to be seen whether exemption is driven by low volume, small numbers of DRGs, or perhaps, policies that determine how procedures are classified as elective.MethodsUsing Medicare inpatient claims data from 4,069 hospitals between 2015 and 2017, we examined how percentages of elective procedures relate to numbers of surgical claims and surgical DRGs. We used a combination of quantile regression and machine learning based anomaly detection to characterize these relationships and identify outliers. We then used a set of machine learning algorithms to test whether outliers were explained by the DRGs they reported.ResultsAverage percentages of elective procedures generally decreased from 100% to 60% in relation to the number of surgical claims and the number of DRGs among them. Some providers with high volumes of claims had anomalously low percentages of elective procedures (5% – 40%). These low elective outliers were not explained by the particular surgical DRGs among their claims. However, among hospitals exempted from PSIs, those with the greatest volume of claims were always low elective outliers.ConclusionSome hospitals with relatively high numbers of surgical claims may have classified procedures as non-elective in a way that ultimately exempted them from certain PSIs.

The prevention of unplanned 30-day readmissions of patients discharged with a diagnosis of heart failure (HF) remains a profound challenge among hospital enterprises. Despite the many models and indices developed to predict which HF patients will readmit for any unplanned cause within 30 days, predictive success has been meager. Using simulations of HF readmission models and the diagnostics most often used to evaluate them (C-statistics, ROC curves), we demonstrate common factors that have contributed to the lack of predictive success among studies. We reveal a greater need for precision and alternative metrics such as partial C-statistics and precision-recall curves and demonstrate via simulations how those tools can be used to better gauge predictive success. We suggest how studies can improve their applicability to hospitals and call for a greater understanding of the uncertainty underlying 30-day all-cause HF readmission. Finally, using insights from sampling theory, we suggest a novel uncertainty-based perspective for predicting readmissions and non-readmissions.

Key Points Question What risk factors are associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among health care personnel (HCP) inside and outside the workplace? Findings In this cross-sectional study of 24 749 HCP in 3 US states, contact with an individual with known coronavirus disease 2019 (COVID-19) exposure outside the workplace was the strongest risk factor associated with SARS-CoV-2 seropositivity, along with living in a zip code with higher COVID-19 incidence. None of the assessed workplace factors were associated with seropositivity. Meaning In this study, most risk factors associated with SARS-CoV-2 infection among HCP were outside the workplace, suggesting that current infection prevention strategies in health care are effective in preventing patient-to-HCP transmission in the workplace., This cross-sectional study evaluates the risk factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seropositivity among health care personnel., Importance Risks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection among health care personnel (HCP) are unclear. Objective To evaluate the risk factors associated with SARS-CoV-2 seropositivity among HCP with the a priori hypothesis that community exposure but not health care exposure was associated with seropositivity. Design, Setting, and Participants This cross-sectional study was conducted among volunteer HCP at 4 large health care systems in 3 US states. Sites shared deidentified data sets, including previously collected serology results, questionnaire results on community and workplace exposures at the time of serology, and 3-digit residential zip code prefix of HCP. Site-specific responses were mapped to a common metadata set. Residential weekly coronavirus disease 2019 (COVID-19) cumulative incidence was calculated from state-based COVID-19 case and census data. Exposures Model variables included demographic (age, race, sex, ethnicity), community (known COVID-19 contact, COVID-19 cumulative incidence by 3-digit zip code prefix), and health care (workplace, job role, COVID-19 patient contact) factors. Main Outcome and Measures The main outcome was SARS-CoV-2 seropositivity. Risk factors for seropositivity were estimated using a mixed-effects logistic regression model with a random intercept to account for clustering by site. Results Among 24 749 HCP, most were younger than 50 years (17 233 [69.6%]), were women (19 361 [78.2%]), were White individuals (15 157 [61.2%]), and reported workplace contact with patients with COVID-19 (12 413 [50.2%]). Many HCP worked in the inpatient setting (8893 [35.9%]) and were nurses (7830 [31.6%]). Cumulative incidence of COVID-19 per 10 000 in the community up to 1 week prior to serology testing ranged from 8.2 to 275.6; 20 072 HCP (81.1%) reported no COVID-19 contact in the community. Seropositivity was 4.4% (95% CI, 4.1%-4.6%; 1080 HCP) overall. In multivariable analysis, community COVID-19 contact and community COVID-19 cumulative incidence were associated with seropositivity (community contact: adjusted odds ratio [aOR], 3.5; 95% CI, 2.9-4.1; community cumulative incidence: aOR, 1.8; 95% CI, 1.3-2.6). No assessed workplace factors were associated with seropositivity, including nurse job role (aOR, 1.1; 95% CI, 0.9-1.3), working in the emergency department (aOR, 1.0; 95% CI, 0.8-1.3), or workplace contact with patients with COVID-19 (aOR, 1.1; 95% CI, 0.9-1.3). Conclusions and Relevance In this cross-sectional study of US HCP in 3 states, community exposures were associated with seropositivity to SARS-CoV-2, but workplace factors, including workplace role, environment, or contact with patients with known COVID-19, were not. These findings provide reassurance that current infection prevention practices in diverse health care settings are effective in preventing transmission of SARS-CoV-2 from patients to HCP.

The rapid spread of the novel coronavirus disease 2019 (COVID-19) has created high demand for medical resources, including personnel, intensive care unit beds, and ventilators. As thousands of patients are hospitalized, the disease has shown remarkable diversity in its manifestation; many patients with mild to no symptoms recover from the disease requiring minimal care, but some patients with severe disease progression require mechanical ventilation support in intensive care units (ICU) with an increased risk of death. Studying the characteristics of patients in these various strata can help us understand the varied progression of this disease, enable earlier interventions for at-risk patients, and help manage medical resources more efficiently. This paper presents a retrospective analysis of 10,123 COVID-19 patients treated at the Rush University Medical Center in Chicago, including their demographics, symptoms, comorbidities, laboratory values, vital signs, and clinical history. Specifically, we present a staging scheme based on discrete clinical events (i.e., admission to the hospital, admission to the ICU, mechanical ventilation, and death), and investigate the temporal trend of clinical variables and the effect of comorbidities in each of those stages. We then developed a prognostic model to predict ventilation demands at an individual patient level by analyzing baseline clinical variables, which entails (1) a least absolute shrinkage and selection operator (LASSO) regression and a decision tree model to identify predictors for mechanical ventilation; and (2) a logistic regression model based on these risk factors to predict which patients will eventually need ventilatory support. Our results indicate that the prognostic model achieves an AUC of 0.823 (95% CI: 0.765–0.880) in identifying patients who will eventually require mechanical ventilation.

Background SARS-CoV-2 is a global pandemic associated with significant morbidity and mortality. However, information from United States cohorts is limited. Understanding predictors of admission and critical illness in these patients is essential to guide prevention and risk stratification strategies. Methods This was a retrospective, registry-based cohort study including all patients presenting to Rush University Medical Center in Chicago, Illinois, with COVID-19 from March 4, 2020 to June 21, 2020. Demographic, clinical, laboratory, and treatment data were obtained from the registry and compared between hospitalized and nonhospitalized patients as well as those with critical illness. We used logistic regression modeling to explore risk factors associated with hospitalization and critical illness. Results A total of 8,673 COVID-19 patients were included in the study, of whom 1,483 (17.1%) were admitted to the hospital and 528 (6.1%) were admitted to the intensive care unit. Risk factors for hospital admission included advanced age, male sex (odds ratio [OR] = 1.69, 95% confidence interval [CI] = 1.44 to 1.98), Hispanic/Latino ethnicity (OR = 1.52, 95% CI = 1.18 to 1.92), hypertension (OR = 1.77, 95% CI = 1.46 to 2.16), diabetes mellitus (OR = 1.84, 95% CI = 1.53 to 2.22), prior CVA (OR = 3.20, 95% CI = 1.99 to 5.14), coronary artery disease (OR = 1.45, 95% CI = 1.03 to 2.06), heart failure (OR = 1.79, 95% CI = 1.23 to 2.61), chronic kidney disease (OR = 2.60, 95% CI = 1.77 to 3.83), end-stage renal disease (OR = 2.22, 95% CI = 1.12 to 4.41), cirrhosis (OR = 2.03, 95% CI = 1.42 to 2.91), fever (OR = 1.43, 95% CI = 1.19 to 1.71), and dyspnea (OR = 4.53, 95% CI = 3.75 to 5.47). Factors associated with critical illness included male sex (OR = 1.45, 95% CI = 1.12 to 1.88), congestive heart failure (OR = 1.45, 95% CI = 1.00 to 2.12), obstructive sleep apnea (OR = 1.58, 95% CI = 1.07 to 2.33), blood-borne cancer (OR = 3.53, 95% CI = 1.26 to 9.86), leukocytosis (OR = 1.53, 95% CI = 1.15 to 2.17), elevated neutrophil-to-lymphocyte ratio (OR = 1.61, 95% CI = 1.20 to 2.17), hypoalbuminemia (OR = 1.80, 95% CI = 1.39 to 2.32), elevated AST (OR = 1.66, 95% CI = 1.20 to 2.29), elevated lactate (OR = 1.95, 95% CI = 1.40 to 2.73), elevated D-Dimer (OR = 1.44, 95% CI = 1.05 to 1.97), and elevated troponin (OR = 3.65, 95% CI = 2.03 to 6.57). Conclusion There are a number of factors associated with hospitalization and critical illness. Clinicians should consider these factors when evaluating patients with COVID-19.

BackgroundDisease surveillance is a critical function of public health, provides essential information about disease burden, clinical and epidemiologic parameters of disease, and is an important element to effective and timely case and contact tracing. The COVID-19 pandemic has demonstrated the essential role these functions have to preserve public health. Syndromic surveillance, electronic laboratory reporting in the meaningful use program, and the growth of the National Healthcare Safety Network (NHSN) have created linkages between hospitals, commercial labs, and public health that can collect and organize data, often through EHR and order workflows, to improve the timeliness and completeness of reporting. In theory, the standard data formats and exchange methods provided by meaningful use should enable rapid healthcare data exchange in the setting of disruptive healthcare events like a pandemic. In reality, access to data remains challenging, and even if available, often lack conformity to regulated standards.ObjectiveWe sought to use regulated interoperability standards already in production to generate regional bed capacity awareness, enhance the capture of epidemiological risk factors and clinical variables among COVID-19 tested patients, and reduce the administrative burden of reporting for stakeholders in a manner that could be replicated by other public health agencies.MethodsFollowing a public health order mandating data submission, we developed technical infrastructure to combine multiple data feeds from electronic health record systems. We measured the completeness of each feed, and the match rate between feeds.ResultsA cloud-based environment was created that received data from electronic lab reporting, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project beginning to aid in consensus and principles for data use. 88,906 total persons from CCDA data among 14 facilities, and 408,741 persons from ELR records among 88 facilities, were submitted. Fields routinely absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. CCDA data provided an improvement in the quality of data available for surveillance and was highly complete with ConclusionsWe describe the development of a city-wide public health data hub for the surveillance of COVID-19 infection. We were able to assess the completeness of existing ELR feeds, augment these feeds with CCDA documents, establish secure transfer methods for data exchange, develop cloud-based architecture to enable secure data storage and analytics, and produced meaningful dashboards for the monitoring of capacity and disease burden. We see this public health and clinical data registry as an informative example of the power of common standards across electronic records, and a potential template for future extension of the use of standards to improve public health surveillance.

BACKGROUNDWhether and to what degree SARS-CoV-2 is spread via the airborne route is unknown. Using data collected from health care worker interactions with hospitalized patients with COVID-19 illness, we calculated the transmissibility of SARS-CoV-2 via the airborne route.OBJECTIVES/METHODSHealthcare worker interaction with SARS-CoV-2 infected patients were tracked using a real time location system between March 18 and March 31. A value for q, the transmissibility expressed as quanta per hour, was estimated using a well-established model for airborne transmission.RESULTSSARS-CoV-2 infection prevalence among tracked HCWs was 2.21% (0.07-4.35). Transmissibility was estimated to be 0.225 quanta per hour, well below other well-characterized airborne pathogens. Simulations demonstrated that risk of infection is substantially reduced with increased ventilation of rooms.CONCLUSIONSOverall, our findings suggest that SARS-CoV-2 is not well transmitted via the airborne route in controlled conditions. We speculate that SARS-CoV-2 may be only opportunistically airborne, with most transmission occurring via droplet methods.One Sentence SummaryWe calculated the airborne transmissibility (q) of SARS-CoV-2 and the impact of masks and ventilation in a hospital setting.

This chapter looks at staphylococci, which are Gram-positive cocci that form clusters, but can occur singly, in pairs, chains, or tetrads. They are classically distinguished from other Gram-positive cocci by presence of catalase, an enzyme that degrades hydrogen peroxide (H2O2). S. aureus is distinguished from other coagulase-negative staphylococci, which are generally less virulent, by the presence of coagulase, an enzyme that coagulates plasma. Many toxins and regulatory elements enhance virulence in staphylococci. Staphylococci are skin commensals. About 20% of adults are persistently colonized by S. aureus, 60% are intermittently colonized, and 20% are never colonized. High-risk groups for S. aureus colonization include infants, insulin-dependent diabetics, intravenous drug users, HIV-infected patients, and renal dialysis patients. Methicillin-resistant Staphylococcus aureus (MRSA) was once predominantly seen in hospitals. However, over the past twenty years the epidemiology of MRSA has significantly changed, with MRSA infections now being observed in community settings.

In the United States, hospital rating system usefulness is limited by heterogeneity and conflicting results. US News Best Hospitals, Vizient Quality and Accountability Study, Centers for Medicare & Medicaid Services (CMS) Star Rating, Leapfrog Hospital Safety Grade, and the Truven Top 100 Hospitals ratings were compared using Spearman correlations. Rank aggregation was used to combine the scores generating a Quality Composite Rank (QCR). The highest correlation between rating systems was shown between the Leapfrog Safety Grade and the CMS Star Rating. In a proportional odds logistic regression, a greater discordance between the CMS Star Rating, Vizient rank, US News, and Leapfrog was associated with a lower overall rank in the QCR. Lack of transparency and understanding about the differences and similarities for these hospital ranking systems complicates use of the measures. By combining the results of these ranking systems into a composite, the measurement of hospital quality can be simplified.

In patients undergoing regadenoson SPECT myocardial perfusion imaging (MPI), the prognostic value of ischemic ST-segment depression (ST↓) and the optimal ST↓ threshold have not been studied. A retrospective cohort study of consecutive patients referred for regadenoson stress MPI was conducted. Patients with uninterpretable ECG were excluded. Two diagnostic thresholds of horizontal or downsloping ST↓ were studied, ≥ 0.5 mm and ≥ 1.0 mm. The primary endpoint was the composite major adverse cardiac events (MACE) of cardiac death, myocardial infarction, or coronary revascularization. Among 8615 subjects (mean age 62 ± 13 years; 55% women), 89 (1.0%) had ST↓ ≥ 1.0 mm and 133 (1.5%) had ST↓ ≥ 0.5 mm. Regadenoson-induced ST↓ was more common in women (P

BACKGROUNDMethicillin-resistantStaphylococcus aureus(MRSA) infections due to USA300 have become widespread in community and healthcare settings. It is unclear whether risk factors for bloodstream infections (BSIs) differ by strain type.OBJECTIVETo examine the epidemiology ofS. aureusBSIs, including USA300 and non-USA300 MRSA strains.DESIGNRetrospective observational study with molecular analysis.SETTINGLarge urban public hospital.PATIENTSIndividuals withS. aureusBSIs from January 1, 2007 through December 31, 2013.METHODSWe used electronic surveillance data to identify cases ofS. aureusBSI. Available MRSA isolates were analyzed by pulsed-field gel electrophoresis. Poisson regression was used to evaluate changes in BSI incidence over time. Risk factor data were collected by medical chart review and logistic regression was used for multivariate analysis of risk factors.RESULTSA total of 1,015 cases ofS. aureusBSIs were identified during the study period; 36% were due to MRSA. The incidence of hospital-onset (HO) MRSA BSIs decreased while that of community-onset (CO) MRSA BSIs remained stable. The rate of CO– and HO– methicillin-susceptibleS. aureusinfections both decreased over time. More than half of HO-MRSA BSIs were due to the USA300 strain type and for 4 years, the proportion of HO-MRSA BSIs due to USA300 exceeded 60%. On multivariate analysis, current or former drug use was the only epidemiologic risk factor for CO- or HO-MRSA BSIs due to USA300 strains.CONCLUSIONSUSA300 MRSA is endemic in communities and hospitals and certain populations (eg, those who use illicit drugs) may benefit from enhanced prevention efforts in the community.Infect. Control Hosp. Epidemiol.2015;36(12):1417–1422

BACKGROUND In a community, it is unknown what factors account for transmission of methicillin-resistant Staphylococcus aureus (MRSA). We integrated whole genome sequencing (WGS) and epidemiologic data to identify factors associated with MRSA transmission networks in an urban community. METHODS WGS was performed on colonizing USA300 MRSA isolates from 74 individuals within 72 hours of admission to a public hospital in Chicago, IL. Single nucleotide variants (SNVs) were used to reconstruct the phylogeny of sequenced isolates, and epidemiologic data was overlaid to identify factors associated with transmission networks. RESULTS The maximum within-patient SNV difference for an individual with multisite colonization was 41 SNVs, with no systematic divergence among body sites. We observed a minimum of 7 SNVs and maximum of 153 SNVs between isolates from different individuals. We identified 4 pairs of individuals whose isolates were within 40 SNVs of each other. Putting our isolates in the context of previously sequenced USA300 isolates from other communities, we identified a 13-member group and two 4-member groups that represent samples from putative local transmission networks. Individuals in these groups were more likely to be African American, to be human immunodeficiency virus-infected, to reside in high detainee release areas, and to be current users of illicit drugs. CONCLUSIONS Using WGS, we observed potential transmission networks in an urban community and that certain epidemiologic factors were associated with inclusion in these networks. Future work with contact tracing and advanced molecular diagnostics may allow for identification of MRSA "epicenters" in the community where interventions can be targeted.

Idiopathic inflammatory myopathies (IIM) are a rare group of autoimmune diseases characterized by muscle inflammation. High-dose corticosteroids are conventionally used as the first-line therapy for IIM, but early introduction of noncorticosteroid immunosuppressive agents has become increasingly common in recent years despite a paucity of compelling evidence to support this. Here, we systematically analyze therapeutic practice patterns of IIM in a large municipal safety net medical center. We conducted a retrospective chart review of all adult patients attending rheumatology clinics at the Cook County Health and Hospital Systems from 2006 to 2011 with a diagnosis of IIM. Data collected included patient demographics, diagnosis, immunosuppressive therapies, serial serum creatine kinase (CK) measurements, and serial muscle strength testing. One hundred eight patients fulfilled eligibility criteria. The mean duration of follow-up was 62 months (range, 1-351 months). At presentation, the mean strength in the weakest muscle group was rated as 3.6 out of 5 (range, 1-5; SD 0.9), the mean initial CK was 4720 U/L (range, 23-38, 461; SD 6, 795), and initial mean prednisone dosage was 48 mg/d (range, 0-100, SD 22). At the end of the follow-up period, mean strength in the weakest muscle group was 4.6 out of 5 (range, 2-5; SD 0.7), mean peak CK was 412 (24-7533; SD 875), and the mean prednisone dosage was 12.7 mg (0-80; SD 17.5). Only 15 patients (14%) received exclusively corticosteroid monotherapy during the follow-up period. Ninety-three patients (86%) received additional immunosuppressive agents. Over the course of their illness, only a minority of patients in our cohort of IIM patients was treated with corticosteroids alone. It is unlikely we will determine optimal therapy in the absence of a large controlled study comparing corticosteroids versus a combination regimen, but it seems that rheumatologists favor addition of second-line immunosuppressive agents.

Objective To design and implement a tool that creates a secure, privacy preserving linkage of electronic health record (EHR) data across multiple sites in a large metropolitan area in the United States (Chicago, IL), for use in clinical research. Methods The authors developed and distributed a software application that performs standardized data cleaning, preprocessing, and hashing of patient identifiers to remove all protected health information. The application creates seeded hash code combinations of patient identifiers using a Health Insurance Portability and Accountability Act compliant SHA-512 algorithm that minimizes re-identification risk. The authors subsequently linked individual records using a central honest broker with an algorithm that assigns weights to hash combinations in order to generate high specificity matches. Results The software application successfully linked and de-duplicated 7 million records across 6 institutions, resulting in a cohort of 5 million unique records. Using a manually reconciled set of 11 292 patients as a gold standard, the software achieved a sensitivity of 96% and a specificity of 100%, with a majority of the missed matches accounted for by patients with both a missing social security number and last name change. Using 3 disease examples, it is demonstrated that the software can reduce duplication of patient records across sites by as much as 28%. Conclusions Software that standardizes the assignment of a unique seeded hash identifier merged through an agreed upon third-party honest broker can enable large-scale secure linkage of EHR data for epidemiologic and public health research. The software algorithm can improve future epidemiologic research by providing more comprehensive data given that patients may make use of multiple healthcare systems.

Clinician education and prospective audit and feedback interventions, deployed separately and concurrently, did not reduce antimicrobial use errors or rates compared to a control group of general medicine inpatients at our public hospital. Additional research is needed to define the optimal scope and intensity of hospital antimicrobial stewardship interventions.Infect Control Hosp Epidemiol2017;38:857–859

Background We examined whether disparities existed in hospital-onset (HO) Staphylococcus aureus bloodstream infections (BSIs) and used whole-genome sequencing (WGS) to identify factors associated with USA300 transmission networks. Methods We evaluated HO methicillin-susceptible S. aureus (MSSA) and HO methicillin-resistant S. aureus (MRSA) BSIs for 2009-2013 at 2 hospitals and used an adjusted incidence for modeling. WGS and phylogenetic analyses were performed on a sample of USA300 BSI isolates. Epidemiologic data were analyzed in the context of phylogenetic reconstructions. Results On multivariate analysis, male sex, African-American race, and non-Hispanic white race/ethnicity were significantly associated with HO-MRSA BSIs whereas Hispanic ethnicity was negatively associated (rate ratio, 0.41; P = .002). Intermixing of community-onset and HO-USA300 strains on the phylogenetic tree indicates that these strains derive from a common pool. African-American race was the only factor associated with genomic clustering of isolates. Conclusions In a multicenter assessment of HO-S. aureus BSIs, African-American race was significantly associated with HO-MRSA but not MSSA BSIs. There appears to be a nexus of USA300 community and hospital transmission networks, with a community factor being the primary driver. Our data suggest that HO-USA300 BSIs likely are due to colonizing strains acquired in the community before hospitalization. Therefore, prevention efforts may need to extend to the community for maximal benefit.

The Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) represents an unprecedented collaboration across diverse healthcare institutions including private, county, and state hospitals and health systems, a consortium of Federally Qualified Health Centers, and two Department of Veterans Affairs hospitals. CAPriCORN builds on the strengths of our institutions to develop a cross-cutting infrastructure for sustainable and patient-centered comparative effectiveness research in Chicago. Unique aspects include collaboration with the University HealthSystem Consortium to aggregate data across sites, a centralized communication center to integrate patient recruitment with the data infrastructure, and a centralized institutional review board to ensure a strong and efficient human subject protection program. With coordination by the Chicago Community Trust and the Illinois Medical District Commission, CAPriCORN will model how healthcare institutions can overcome barriers of data integration, marketplace competition, and care fragmentation to develop, test, and implement strategies to improve care for diverse populations and reduce health disparities.

Background USA300 is endemic in the community, with congregate settings potentially facilitating spread. The impact of community MRSA transmission networks on importation of MRSA into urban jails is unknown. We examined MRSA colonization isolates entering the jail and determined whether there are community transmission networks for MRSA that precede incarceration. Methods HIV-infected and HIV-negative males incarcerated at the Cook County Jail were enrolled within 72 hours of intake. Surveillance cultures (nares, throat, and groin) were collected to determine prevalence of MRSA colonization. A survey was administered to identify predictors of colonization. Whole-genome sequencing (WGS) and phylogenetic analysis were integrated with epidemiologic data to identify community transmission networks. Results A total of 800 males were enrolled (83% AA and 9% Hispanic); 58% were HIV-infected. The prevalence of MRSA colonization at intake was 19%. In multivariate analysis, methamphetamine use (METH), unstable housing, and prior jail incarceration were significant predictors of MRSA. Among HIV patients, injection drug use and HIV care at outpatient Clinic A that emphasize comprehensive care to the LGBTQ community were significant predictors of MRSA. Of the 31 (45%) patients with care at Clinic A, 14 had MRSA colonization. We sequenced 145 isolates from unique individuals, with 102 and 13 closely related to USA300 and USA500 reference genomes, respectively. USA300 strains from intake were diverse (median pairwise SNV distance = 109), with several small clusters noted. WGS revealed the high prevalence of MRSA in Clinic A was not due to clonal spread but rather an intermingling of distinct community transmission networks (strains were highly diverse; median pairwise SNV distance = 410). We did identify a 13-member community transmission network underlying spread of USA500 (figure). Members of this network were more likely to be HIV-infected (P < 0.004), MSM (P < 0.001), and METH (P < 0.001). Conclusion A high proportion of individuals enter jail already colonized with MRSA and colonization risk factors provide clues to community reservoirs for MRSA. WGS extended epidemiologic analysis and revealed community transmission networks that could be a potential focus for an intervention. Disclosures All authors: No reported disclosures.

Article-at-a-Glance Background Differences between the Centers for Medicare & Medicaid Services (CMS)–measured rates of safety events for Rush University Medical Center (RUMC; Chicago) and the U.S. News & World Report (USNWR)–deter­mined patient safety score were evaluated in an attempt to validate the USNWR patient safety score–based ranking. Methods The USNWR findings for Patient Safety Indicators (PSIs) were compared with findings derived from RUMC internal billing data, and sensitivity analyses were conducted using a simulated data set derived from the Healthcare Cost and Utilization Project (HCUP) state inpatient data sets. Results Discrepancies were found for PSIs 3 (Pressure Ulcer Rate), 9 (Perioperative Hemorrhage or Hematoma Rate), and 11 (Postoperative Respiratory Failure Rate)—an excess of 0.72, 0.63, and 0.26 cases/1,000 admissions, in USNWR versus RUMC, respectively). The sensitivity analysis, which included missing present on admission (POA) flags and dates, resulted in an increase of rates by 1.83 (95% confidence interval [CI] = 1.10–2.56) cases/1,000 hospitalizations, 2.72 (CI = 0.00–5.90) cases/1,000 hospitalizations, and 3.89 (CI = 1.60–6.20) cases/1,000 hospitalizations for PSI 3, 9, and 11, respectively. Regression modeling showed that each 1% increase in transfers was associated with an increase of 0.06 cases of PSI 3/1,000 admissions; each 1,000 increase in admissions was associated with an increase of 0.04 cases of PSI 9/1,000 admissions. Conclusion The USNWR data set produced inaccurate PSI rates for RUMC, and false-positive event rates were more common among high-transfer and high-volume hospitals. More transparency and validation is needed for consumer-based benchmarking methods. In response to these findings and concerns raised by others, in 2016 USNWR made changes to its methodology and data sources and ­reported them in announcing its 2016–17 Best Hospitals.

Background The optimal timing of surgical treatment for infective endocarditis complicated by cerebrovascular events is controversial, largely due to the perceived risk of perioperative intracranial bleeding. Current guidelines suggest waiting 2 weeks between the diagnosis of stroke and surgery. The aim of this study was to investigate the clinical and neurological outcomes of early surgery following a stroke. Methods This was a single-center retrospective analysis of 12 consecutive patients requiring surgery for infective endocarditis between 2011 and 2014 at Rush University Medical Center, with either ischemic ( n = 6) and/or hemorrhagic ( n = 6) cerebrovascular complications. All underwent computed tomographic angiography prior to early valve reconstructive surgery to identify potentially actionable neurological findings. Early valve surgery was performed for ongoing sepsis or persistent emboli. Neurologic risk and outcome were assessed pre- and postoperatively using the National Institutes of Health Stroke Scale and the Glasgow Outcome Scale, respectively. Results All 12 patients underwent surgical treatment within 10 days of the diagnosis of stroke. Mortality in the immediate postoperative period was 8%. Eleven of the 12 patients exhibited good neurological recovery in the immediate postoperative period, with a Glasgow Outcome Scale score ≥ 3. There was no correlation between duration of cardiopulmonary bypass and neurological outcomes. Conclusion Early cardiac surgery in patients with infective endocarditis and stroke maybe lifesaving with a low neurological risk. Comprehensive neurovascular imaging may help in identifying patient-related risk factors.

Objective and Design.Previous work has shown that daily skin cleansing with Chlorhexidine gluconate (CHG) is effective in preventing infection in the medical intensive care unit (MICU). A colorimetric, semiquantitative indicator was used to measure CHG concentration on skin (neck, antecubital fossae, and inguinal areas) of patients bathed daily with CHG during their MICU stay and after discharge from the MICU, when CHG bathing stopped.Patients and Setting.MICU patients at Rush University Medical Center.Methods.CHG concentration on skin was measured and skin sites were cultured quantitatively. The relationship between CHG concentration and microbial density on skin was explored in a mixed-effects model using gram-positive colony-forming unit (CFU) counts.Results.For 20 MICU patients studied (240 measurements), the lowest CHG concentrations (0–18.75 μg/mL) and the highest gram-positive CFU counts were on the neck (median, 1.07 log10CFUs;P= .014). CHG concentration increased postbath and decreased over 24 hours (P< .001). In parallel, median log10CFUs decreased pre- to postbath (0.78 to 0) and then increased over 24 hours to the baseline of 0.78 (P= .001). A CHG concentration above 18.75 μg/mL was associated with decreased gram-positive CFUs (P= .004). In all but 2 instances, CHG was detected on patient skin during the entire interbath (approximately 24-hour) period (18 [90%] of 20 patients). In 11 patients studied after MICU discharge (80 measurements), CHG skin concentrations fell below effective levels after 1–3 days.Conclusion.In MICU patients bathed daily with CHG, CHG concentration was inversely associated with microbial density on skin; residual antimicrobial activity on skin persisted up to 24 hours. Determination of CHG concentration on the skin of patients may be useful in monitoring the adequacy of skin cleansing by healthcare workers.

Objective.To assessClostridium difficileinfection (CDI)-related colectomy rates by CDI surveillance definitions and over time at multiple healthcare facilities.Setting.Five university-affiliated acute care hospitals in the United States.Design and Methods.Cases of CDI and patients who underwent colectomy from July 2000 through June 2006 were identified from 5 US tertiary care centers. Monthly CDI-related colectomy rates were calculated as the number of CDI-related colectomies per 1,000 CDI cases, and cases were categorized according to recommended surveillance definitions. Logistic regression was performed to evaluate risk factors for CDI-related colectomy.Results.In total, 8,569 cases of CDI were identified, and 75 patients underwent CDI-related colectomy. The overall colectomy rate was 8.7 per 1,000 CDI cases. The CDI-related colectomy rate ranged from 0 to 23 per 1,000 CDI episodes across hospitals. The colectomy rate for healthcare-facility-onset CDI was 4.3 per 1,000 CDI cases, and that for community-onset CDI was 16.5 per 1,000 CDI cases (P< .05). There were significantly more CDI-related colectomies at hospitals B and C (P< .05).Conclusions.The overall CDI-related colectomy rate was low, and there was no significant change in the CDI-related colectomy rate over time. Onset of disease outside the study hospital was an independent risk factor for colectomy.

Background. We examined the epidemiology of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) nasal colonization among 3 groups of human immunodeficiency virus (HIV)‐infected and 1 group of HIV-negative outpatients. Methods. We determined prevalence and risk factors associated with MRSA colonization among women, recently incarcerated, and Hispanic HIV-infected patients and HIV-negative patients; isolates were typed by pulsedfield gel electrophoresis. Relative prevalence was calculated using Poisson regression, and logistic regression was used for multivariate analysis. Results. Of 601 patients, 9.3% were colonized with MRSA; 11% of HIV-infected and 4.2% of HIV-negative patients were colonized (relative prevalence, 2.6; 95% confidence interval [CI], 1.12‐6.07; P 5 .03). Among HIVinfected patients, recently incarcerated patients had the highest colonization prevalence (15.6%) followed by women (12%); Hispanic patients had the lowest (2.8%). Eighty percent of confirmed MRSA isolates were identified as USA300. On multivariate analysis, history of incarceration or residence in alternative housing (odds ratio [OR], 2.3; 95% CI, 1.1‐4.7; P 5 .03) was associated with MRSA colonization; Hispanic ethnicity was negatively associated (OR, 0.3; 95% CI, .11‐.98; P 5 .045). There was a trend (OR, 1.6; 95% CI, .9‐3.0; P 5 .097) toward geographic location of residence being associated with colonization. After controlling for incarceration, residence, and geography, HIV status was no longer significantly associated with colonization. Conclusions. The CA-MRSA and HIV epidemics have intersected. Examination of networks of individuals released from incarceration, both HIV positive and negative, is needed to assess the role of social networks in spread of CA-MRSA and inform prevention strategies.

Background USA300 MRSA is endemic in certain communities, with congregate settings such as urban jails potentially facilitating spread. The extent of MRSA transmission in jail is unclear, a controversy that impacts prevention strategies. We determined the prevalence of MRSA colonization at jail entrance and defined the acquisition rate during incarceration. Methods Men incarcerated at the Cook County Jail, one of the largest US single-site jails, were enrolled within 72 hours of intake. Surveillance cultures (nares, throat, groin) were collected to determine prevalence of MRSA colonization. A survey was administered to identify predictors of colonization. Detainees still in jail at Day30 had cultures repeated to determine MRSA acquisition rate. Univariate and multivariate analysis was performed to identify predictors of MRSA colonization. Results A total o 402 men (447 unique incarcerations) have so far been enrolled (77% AA, 11% Hispanic) with 92% previously in jail (20% in past 6 months). The prevalence of MRSA colonization at intake was 18.6% (83/447), with 39% of those colonized solely in the throat or groin. At 30 days: 10% (9/92) of initially negative men acquired MRSA; 14 admission positives remained colonized while 11 lost colonization. On univariate (Table), predictors of MRSA colonization at entrance to the jail were: methamphetamine use (METH), unstable housing, current skin infection, and care at an outpatient Clinic A that emphasizes comprehensive care to the LGBTQ community. In this cohort, METH use was associated with reporting being a man who has sex with men vs. not (35% vs. 9%, P Conclusion We found that a relatively high proportion of individuals enter the jail colonized with MRSA and the jail may amplify rates. Entrance colonization risk factors point to possible community reservoirs. Enrollment is ongoing but results suggest an intervention in jail could impact MRSA rates in the jail and in the surrounding community. Disclosures M. K. Hayden, Sage, Inc: Sage is contributing product to healthcare facilities participating in a regional collaborative on which I am a co-investigator. Neither I nor my hospital receive product., Sage is contributing product to healthcare facilities participating in a regional collaborative on which I am a co-investigator. Neither I nor my hospital receive product.; Clorox, Inc.: I have received funding from Clorox for an investigator-initiated clinical trial., Research support; CDC: Grant Investigator, Research grant

Methicillin-resistant Staphylococcus aureus (MRSA) has emerged over the past 20 years as a cause of infections in community populations, so-called community-associated MRSA (CA-MRSA). By pulsed-field gel electrophoresis (PFGE) subtyping, USA300 is the most common CA-MRSA strain in the US. It has been suggested that the colonization dynamics for CA-MRSA may be different than those for traditional MRSA strains1, with extra-nasal colonization potentially playing a role in CA-MRSA transmission and infection1. Another distinguishing characteristic of USA300 MRSA strains is greater susceptibility to non-β-lactam antibiotics compared to healthcare-associated MRSA strains. However, multi-drug resistant (MDR) USA300 strains have been described, largely among HIV-infected patients and men who have sex with men (MSM)2. Also of concern, resistance to common decolonizing agents such as mupirocin2 and chlorhexidine gluconate (CHG)3 has been reported in CA-MRSA. The objectives of this study were to examine the phenotype of USA300 MRSA strains, the prevalence of the qacA/B gene in this population, and the anatomic sites of colonization by PFGE pattern. We previously reported on the prevalence of nasal and extra-nasal CA-MRSA colonization among inpatients (374 HIV-infected and 371 HIV-negative) at Stroger Hospital of Cook County (CCH), the major safety-net hospital in Chicago, IL4. As described elsewhere, nasal and extra-nasal (throat, axilla, inguinal, peri-rectal, and chronic wound if present) surveillance swab specimens were collected from patients within 72 hours of admission from March 2011-April 2012; cultures were processed with broth enrichment4. Gender was recorded and enrolled men were asked if they identified themselves as MSM. Genotypic analysis with PFGE was performed on all identified MRSA isolates. Results were interpreted as described by McDougal, et al5. Confirmed MRSA isolates had antibiotic susceptibility determined (MicroScan Walkaway System, Siemens Healthcare Diagnostics, West Sacramento, CA). For USA300 MRSA strains, MDR was defined as resistance to four or more non-β lactam antibiotic classes. High-level mupirocin resistance was assessed using disk diffusion6. Carriage of qacA and qacB genes, which code for efflux pumps associated with increased minimum inhibitory concentrations (MICs) of CHG7, was assessed using real-time PCR as described previously8. Chi-square analysis was used to examine the association of PFGE patterns and colonization sites, with Fisher’s exact test used for small samples. SAS software version 9.2 (SAS Institute, Cary, NC) was used for statistical analysis. The study was approved by the Institutional Review Board of CCH and Rush University Medical Center. We observed that following the nares, the peri-rectal area was the second most common site of colonization (58% of colonized individuals). Prevalence of extra-nasal and exclusive extra-nasal colonization was not significantly different between patients colonized with USA300 or non-USA300 strains (Table 1). However, the average number of sites colonized was significantly higher for USA300 versus non-USA300 strains [2.8 (SD 1.51) and 2.2 (1.48), respectively, p=0.049]. Inguinal, peri-rectal, and concomitant inguinal and peri-rectal colonization were all significantly associated with colonization with the USA300 strain type in comparison to non-USA300 MRSA strains (Table 1). Inguinal or peri-rectal MRSA colonization was found more often in men (63/480; 13%)—MSM (OR=2.2; 95% CI, 1.1, 4.2; p=0.02) and heterosexual men (OR=1.8; 95% CI, 1.02, 3.2; p=.04)—than in women (20/265; 8%), OR=1.9 (95% CI, 1.1, 3.1), p=0.02. Table 1 Association of Pattern of Anatomic Site of Colonization and Pulsed-Field Gel Electrophoresis Profile among Individuals Colonized with Community-Associated Methicillin-Resistant Staphylococcus aureus There were 5 individuals who had a MRSA infection at the time of enrollment and they were all found to have colonization with MRSA. Four of these individuals had SSTIs and were colonized with the USA300 strain type and one individual had a bloodstream infection and was colonized with a non-USA300 strain type. Excluding chronic wound cultures, each of these individuals had 3–5 sites of MRSA colonization, suggesting a significant level of extra-nasal colonization and colonization burden for individuals infected with MRSA. 3.4% of colonized individuals carried high-level mupirocin-resistant strains (1 USA100, 2 USA500, 1 USA300). Of the individuals colonized with USA300 MRSA strains, 4 (5%) carried MDR strains. There were 117 MRSA isolates evaluated for the presence of the qacA/B genes; all were negative. We examined colonization and molecular characteristics of CA-MRSA isolates collected from patients seeking care at the major safety-net hospital in Chicago. We found that inguinal and peri-rectal colonization was more common with the USA300 strain type than with non-USA300 MRSA strains. In addition, highly antibiotic resistant USA300 MRSA strains were rare and none of the MRSA isolates collected over a 14 month study period was found to harbor the qacA/B genes. We observed that males—both heterosexual males and MSM—had a higher prevalence of inguinal and peri-rectal MRSA colonization in comparison to females. Similarities observed in colonization patterns between MSM and heterosexual males suggest that perhaps social, hormonal, skin biology, or genetic differences between genders play a role in colonization dynamics rather than sexual orientation9. The absence of qacA/B genes among MRSA isolates in the population we studied is consistent with other reports in the US10. In contrast to reports in San Francisco2, MDR USA300 strains were relatively rare in our population, which comprised a diverse group of HIV-infected and HIV-negative individuals. However, continued surveillance of antibiotic resistance patterns is needed to understand the evolving epidemiology of USA300 strains as well as to inform empiric therapeutic decisions. Our study is limited in that we did not assess frequency of mupirocin or CHG use in our population, although CCH does not have mupirocin on its antibiotic formulary and CHG bathing use has been limited to ICU and pre-operative patients. In addition, we relied on self-report of MSM status which could lead to recall bias. Finally, we performed PFGE on one MRSA colony morphotype per body site and therefore may have failed to detect coexistent minority subpopulations. In summary, our study highlights that inguinal and peri-rectal colonization appears to be more frequent with the USA300 strain type and that gender may play a role in location of extra-nasal CA-MRSA colonization. Patients with clinical MRSA infections appeared to be those with more sites of MRSA colonization. Although mupirocin resistance and presence of qacA/B were uncommon, continued monitoring of MRSA prevalence and resistance is warranted.