Data to Care Pilot Program in Chicago: Experience, Outcomes, and Direction for the Future.

CONTEXT: Data to Care (D2C) involves sharing HIV surveillance data between health care facilities and health departments to improve continuity of care for people living with HIV (PLWH). The Chicago Department of Public Health (CDPH) initiated a D2C pilot program at the University of Chicago Medicine (UCM) from June 2016 to September 2019. OBJECTIVES: To describe the proportion of patients reported by UCM as not in care who were able to be matched to CDPH enhanced HIV/AIDS Reporting System (eHARS) and to report the individual-level factors associated with matching and viral suppression. DESIGN: Retrospective program evaluation. SETTING: UCM, an academic health care center that provides HIV care to adults via a Ryan White clinic on the south side of Chicago. PARTICIPANTS: Adult PLWH who had received care at UCM but did not have current documented HIV care visit(s). MAIN OUTCOME MEASURE: Proportion of matched patients; factors associated with matching and viral suppression. RESULTS: Overall, 72.4% (n = 813/1123) of patients reported by UCM were matched by CDPH to eHARS. Individuals aged 40 to 49 years (odds ratio [OR] = 1.99; 95% confidence interval [CI], 1.10-3.62), 50 to 59 years (OR = 2.47; 95% CI, 1.37-4.47), and 60 years or older (OR = 6.18; 95% CI, 3.18-12.32) were more likely to match in eHARS. People who lived outside of Chicago (OR = 0.09; 95% CI, 0.05-0.15) or with unknown zip codes (OR = 0.08; 95% CI, 0.05-0.12) were less likely to match. Men who have sex with men and persons older than 50 years were more likely to be virally suppressed. CONCLUSIONS: D2C is an evidence-based strategy for reengagement of PLWH; however, program implementation relies on successful data matching. We found that a large proportion of patients from UCM were not matched, particularly those who were younger or lived outside of Chicago. Additional research is needed to understand ways to improve data matching to facilitate reengagement in HIV care.

Measuring Retention in HIV Care in the First Year of the COVID-19 Pandemic: The Impact of Telehealth.

It is unknown how the COVID-19 pandemic impacted traditional measures of retention in HIV care. We calculated six different retention measures at an urban HIV care clinic for two time periods: pre-pandemic, and during the first year of the COVID-19 pandemic, with and without inclusion of telehealth appointments. Spearman rank correlation was used to assess correlation between different measures of retention. For both the pre-pandemic and pandemic time periods, there was strong correlation among measures of missed visits (range 0.857-0.957). More patients were considered retained in care during the pandemic when telehealth appointments were included in the analysis.

Development of a predictive model for identifying women vulnerable to HIV in Chicago.

INTRODUCTION: Researchers in the United States have created several models to predict persons most at risk for HIV. Many of these predictive models use data from all persons newly diagnosed with HIV, the majority of whom are men, and specifically men who have sex with men (MSM). Consequently, risk factors identified by these models are biased toward features that apply only to men or capture sexual behaviours of MSM. We sought to create a predictive model for women using cohort data from two major hospitals in Chicago with large opt-out HIV screening programs. METHODS: We matched 48 newly diagnosed women to 192 HIV-negative women based on number of previous encounters at University of Chicago or Rush University hospitals. We examined data for each woman for the two years prior to either their HIV diagnosis or their last encounter. We assessed risk factors including demographic characteristics and clinical diagnoses taken from patient electronic medical records (EMR) using odds ratios and 95% confidence intervals. We created a multivariable logistic regression model and measured predictive power with the area under the curve (AUC). In the multivariable model, age group, race, and ethnicity were included a priori due to increased risk for HIV among specific demographic groups. RESULTS: The following clinical diagnoses were significant at the bivariate level and were included in the model: pregnancy (OR 1.96 (1.00, 3.84)), hepatitis C (OR 5.73 (1.24, 26.51)), substance use (OR 3.12 (1.12, 8.65)) and sexually transmitted infections (STIs) chlamydia, gonorrhoea, or syphilis. We also a priori included demographic factors that are associated with HIV. Our final model had an AUC of 0.74 and included healthcare site, age group, race, ethnicity, pregnancy, hepatitis C, substance use, and STI diagnosis. CONCLUSIONS: Our predictive model showed acceptable discrimination between those who were and were not newly diagnosed with HIV. We identified risk factors such as recent pregnancy, recent hepatitis C diagnosis, and substance use in addition to the traditionally used recent STI diagnosis that can be incorporated by health systems to detect women who are vulnerable to HIV and would benefit from preexposure prophylaxis (PrEP).

No-show Prediction Model Performance Among People With HIV: External Validation Study.

BACKGROUND: Regular medical care is important for people living with HIV. A no-show predictive model among people with HIV could improve clinical care by allowing providers to proactively engage patients at high risk of missing appointments. Epic, a major provider of electronic medical record systems, created a model that predicts a patient's probability of being a no-show for an outpatient health care appointment; however, this model has not been externally validated in people with HIV. OBJECTIVE: We examined the performance of Epic's no-show model among people with HIV at an academic medical center and assessed whether the performance was impacted by the addition of demographic and HIV clinical information. METHODS: We obtained encounter data from all in-person appointments among people with HIV from January 21 to March 30, 2022, at the University of Chicago Medicine. We compared the predicted no-show probability at the time of the encounter to the actual outcome of these appointments. We also examined the performance of the Epic model among people with HIV for only HIV care appointments in the infectious diseases department. We further compared the no-show model among people with HIV for HIV care appointments to an alternate random forest model we created using a subset of seven readily accessible features used in the Epic model and four additional features related to HIV clinical care or demographics. RESULTS: We identified 674 people with HIV who contributed 1406 total scheduled in-person appointments during the study period. Of those, we identified 331 people with HIV who contributed 440 HIV care appointments. The performance of the Epic model among people with HIV for all appointments in any outpatient clinic had an area under the receiver operating characteristic curve (AUC) of 0.65 (95% CI 0.63-0.66) and for only HIV care appointments had an AUC of 0.63 (95% CI 0.59-0.67). The alternate model we created for people with HIV attending HIV care appointments had an AUC of 0.78 (95% CI 0.75-0.82), a significant improvement over the Epic model restricted to HIV care appointments (P<.001). Features identified as important in the alternate model included lead time, appointment length, HIV viral load >200 copies per mL, lower CD4 T cell counts (both 50 to <200 cells/mm3 and 200 to <350 cells/mm3), and female sex. CONCLUSIONS: For both models among people with HIV, performance was significantly lower than reported by Epic. The improvement in the performance of the alternate model over the proprietary Epic model demonstrates that, among people with HIV, the inclusion of demographic information may enhance the prediction of appointment attendance. The alternate model further reveals that the prediction of appointment attendance in people with HIV can be improved by using HIV clinical information such as CD4 count and HIV viral load test results as features in the model.

Age and Racial Disparities in Telehealth Use Among People with HIV During the COVID-19 Pandemic.

The COVID-19 pandemic resulted in widespread telehealth expansion. To determine telehealth uptake and potential sociodemographic differences in utilization among people with HIV (PwH), we examined HIV care appointments at the University of Chicago Medicine, an urban tertiary hospital. Visits between March 15th and September 9th for 2019 and 2020 were categorized as in-person, telehealth, and within telehealth, video, and phone. Differences in visit types were modeled using logistic regression to examine associations with demographics, insurance type, and HIV risk transmission category. Telehealth appointments were more likely for those aged 46-60 versus those 31-45 [46-60; AOR 1.89 95% CI (1.14, 3.15)]. Black race and participants of other races were less likely to use telehealth compared to whites [Black: AOR 0.33 95% CI (0.16, 0.64), other: AOR 0.10 95% CI (0.02, 0.34)]. Future studies should continue to examine potential disparities in telehealth use among PwH, including age and racial differences.

Multicenter Development and Validation of a Model for Predicting Retention in Care Among People with HIV.

Predictive analytics can be used to identify people with HIV currently retained in care who are at risk for future disengagement from care, allowing for prioritization of retention interventions. We utilized machine learning methods to develop predictive models of retention in care, defined as no more than a 12 month gap between HIV care appointments in the Center for AIDS Research Network of Integrated Clinical Systems (CNICS) cohort. Data were split longitudinally into derivation and validation cohorts. We created logistic regression (LR), random forest (RF), and gradient boosted machine (XGB) models within a discrete-time survival analysis framework and compared their performance to a baseline model that included only demographics, viral suppression, and retention history. 21,267 Patients with 507,687 visits from 2007 to 2018 were included. The LR model outperformed the baseline model (AUC 0.68 [0.67-0.70] vs. 0.60 [0.59-0.62], P < 0.001). RF and XGB models had similar performance to the LR model. Top features in the LR model included retention history, age, and viral suppression.

Association between patient-reported barriers and HIV clinic appointment attendance: A prospective cohort study.

The association between patients' confidence in their ability to attend appointments and future retention in care has not previously been studied in a general HIV clinic. A survey of potential and known risk factors for poor retention was developed using validated screening tools and administered to 105 patients at an HIV clinic. Retention in care was assessed prospectively using two definitions: (1) two appointments at least three months apart within one year ("HRSA/HAB retention") and (2) no missed appointments within one year ("missed visits retention"). Most patients were African American (86%) and male (59%). Although most patients were confident they could keep their HIV appointments (89%), fewer were retained (HRSA/HAB: 73%; missed visits: 56%). Patients' confidence in their ability to keep future appointments was not associated with retention. Employment was associated with lower odds of HRSA/HAB retention (aOR 0.26 [95% CI 0.09-0.77]), and childcare was a common barrier that was associated with lower odds of missed visits retention (aOR 0.06 [95% CI 0.006-0.62]). Other known risk factors for poor retention were inconsistently associated with retention in care.

"When you have an immune disease like HIV and there is a pandemic, you still have to pay your bills": COVID-19-related challenges among people living with HIV and lessons for care delivery.

COVID-19 has disrupted routine medical care and increased psychosocial and economic stressors on a global scale, yet the full impact on people living with HIV (PLWH) and the HIV continuum of care remains unknown. As the pandemic continues to pose a significant threat to PLWH and their care, this research qualitatively aimed to elicit COVID-19-related challenges and perspectives of PLWH during the early phase of the pandemic and to identify lessons learned and impactful strategies for facilitating HIV care. We recruited 32 PLWH who receive care at a large academic medical center for semi-structured remote interviews to assess psychological/structural stressors experienced during the pandemic and to discern strategies for improving care. Most participants identified as Black (91%) and heterosexual (56%). Overall, PLWH reported exacerbated mental health stressors (e.g., anxiety, depression, substance use). Most participants cited no issues with antiretroviral therapy (ART) adherence or retention in care, yet five participants reported appointment cancellations or physician inaccessibility. Participants provided specific feedback for facilitating continued engagement in care during the pandemic, including telemedicine and education/patient empowerment. By seeking participant-provided solutions, this study centered on PLWH's experiences and emphasized proactive HIV care strategies for prioritizing patient empowerment and healthcare adaptability during a rapidly evolving pandemic.

"Even if I'm undetectable, I just feel like I would die": a qualitative study to understand the psychological and socioeconomic impacts of the COVID-19 pandemic on women living with HIV (WLWH) in Chicago, IL.

BACKGROUND: The COVID-19 pandemic has affected the health and well-being of people worldwide, yet few studies have qualitatively examined its cumulative effects on ciswomen living with HIV (WLWH). We aimed to explore how the pandemic has impacted WLWH, including challenges related to HIV care, employment, finances, and childcare. We also investigated how HIV status and different psychosocial stressors affected their mental health. METHODS: We performed 25 semi-structured qualitative interviews with WLWH regarding the ways in which COVID-19 impacted their social determinants of health and physical well-being during the pandemic. 19 WLWH who received care at the University of Chicago Medicine (UCM) and 6 women who received care at Howard Brown Health, a federally qualified health center (FQHC) in Chicago, were interviewed remotely from June 2020 to April 2021. All interviews were audio recorded and transcribed. Interviews were thematically analyzed for commonalities regarding HIV-specific and general experiences of WLWH during the pandemic. RESULTS: The majority of participants reported COVID-19 impacted their HIV care, such as appointment cancellations and difficulties adhering to antiretroviral therapy. In addition to HIV care obstacles, almost all participants described perceived heightened vulnerability to or fear of COVID-19. The pandemic also affected the socioeconomic well-being of participants, with reported financial strains and employment disruptions. Some mothers took on additional childcare responsibilities, such as homeschooling. Increased mental health concerns and negative psychological effects from the social isolation associated with the pandemic were also experienced by most participants. CONCLUSIONS: We gained invaluable insight into how WLWH were challenged by and adapted to the COVID-19 pandemic, including its destabilizing effects on their HIV care and mental health. Women described how they undertook additional childcare responsibilities during the pandemic and how their HIV status compounded their concerns (e.g., perceived heightened vulnerability to COVID-19). Strategies to better support WLWH in maintaining their overall health throughout the pandemic include childcare assistance, access to affordable mental health services, support groups, and education from HIV care providers. These findings have significant implications for examining future health crises through the perspective of potential gender inequalities.

Community-acquired Coinfection in Coronavirus Disease 2019: A Retrospective Observational Experience.

Community-acquired coinfection in coronavirus disease 2019 (COVID-19) is not well defined. Current literature describes coinfection in 0-40% of COVID-19 patients. In this retrospective report, coinfection was identified in 3.7% of patients and 41% of patients admitted to intensive care (P < .005). Despite infrequent coinfection, antibiotics were used in 69% of patients.

A Randomized Controlled Trial of an Electronic Clinical Decision Support Tool for Inpatient Antimicrobial Stewardship.

BACKGROUND: The weighted incidence syndromic combination antibiogram (WISCA) is an antimicrobial stewardship tool that utilizes electronic medical record data to provide real-time clinical decision support regarding empiric antibiotic prescription in the hospital setting. The aim of this study was to determine the impact of WISCA utilization for empiric antibiotic prescription on hospital length of stay (LOS). METHODS: We performed a crossover randomized controlled trial of the WISCA tool at 4 hospitals. Study participants included adult inpatients receiving empiric antibiotics for urinary tract infection (UTI), abdominal-biliary infection (ABI), pneumonia, or nonpurulent cellulitis. Antimicrobial stewardship (ASP) physicians utilized WISCA and clinical guidelines to provide empiric antibiotic recommendations. The primary outcome was LOS. Secondary outcomes included 30-day mortality, 30-day readmission, Clostridioides difficile infection, acquisition of multidrug-resistant gram-negative organism (MDRO), and antibiotics costs. RESULTS: In total, 6849 participants enrolled in the study. There were no overall differences in outcomes among the intervention versus control groups. Participants with cellulitis in the intervention group had significantly shorter mean LOS compared to participants with cellulitis in the control group (coefficient estimate = 0.53 [-0.97, -0.09], P = .0186). For patients with community acquired pneumonia (CAP), the intervention group had significantly lower odds of 30-day mortality compared to the control group (adjusted odds ratio [aOR] .58, 95% confidence interval [CI], .396, .854, P = .02). CONCLUSIONS: Use of WISCA was not associated with improved outcomes for UTI and ABI. Guidelines-based interventions were associated with decreased LOS for cellulitis and decreased mortality for CAP.

Staphylococcus aureus Skin and Soft Tissue Infection Recurrence Rates in Outpatients: A Retrospective Database Study at 3 US Medical Centers.

BACKGROUND: Staphylococcus aureus skin and soft tissue infections (SA-SSTIs) are common in healthcare and community settings, and recurrences occur at variable frequency, even after successful initial treatment. Knowing the exact burden and timing of recurrent disease is critical to planning and evaluating interventions to prevent recurrent SSTIs. METHODS: In this retrospective study, SSTI cases in patients aged ≥18 years at 3 US medical centers (Columbia, Chicago, Vanderbilt) between 2006 and 2016 were analyzed according to a biennial cohort design. Index SSTIs (with or without key comorbidities), either microbiologically confirmed to be SA-SSTI or not microbiologically tested (NMT-SSTI), were recorded within 1 calendar year and followed up for 12 months for recurrent infections. The number of index cases, proportion of index cases with ≥1 recurrence(s), time to first recurrence, and number of recurrences were collected for both SA-SSTI and NMT-SSTI events. RESULTS: In the most recent cohorts, 4755 SSTI cases were reported at Columbia, 2873 at Chicago, and 6433 at Vanderbilt. Of these, 452, 153, and 354 cases were confirmed to be due to S. aureus. Most cases were reported in patients without key comorbidities. Across centers, 16.4%-19.0% (SA-SSTI) and 11.0%-19.2% (NMT-SSTI) of index cases had ≥1 recurrence(s). In patients without key comorbidities, more than 60% of index SSTIs with recurrences had only 1 recurrence, half of which occurred in the first 3 months following primary infection. CONCLUSIONS: SA-SSTI recurrences are common among healthy adults and occur in at least 1 in 6 individuals during the 1 year following the primary event.

Opt-Out, Routine Emergency Department Syphilis Screening as a Novel Intervention in At-Risk Populations.

BACKGROUND: With syphilis rates rising rapidly in the United States, novel means of reaching high-risk populations for screening and treatment are needed. Building on successful models for emergency department (ED) HIV screening, a routine opt-out syphilis screening program was implemented in a large, urban, tertiary care hospital ED in May 2019. This study aims to assess the prevalence of syphilis in this population and to evaluate the routine, opt-out syphilis screening model. METHODS: A retrospective chart review was performed of all patients screened for syphilis in the ED from June to December 2019. Demographic information, HIV status, chief complaint, and follow-up visits were examined. RESULTS: During the study period, 9198 people aged 18 to 64 years were screened for syphilis. Of these, 97 (1.1%) had presumed active syphilis infection (PAI), 354 (3.8%) were presumed not to have active syphilis, and 8747 (95.1%) were negative for infection. Patients with PAI were more likely to be male (67%; adjusted odds ratio, 3.5; 95% confidence interval, 2.3-5.3; P < 0.001), although the percentage of women was considerably higher than the nationally reported rate, and most were non-Hispanic Black (93.8%). Among patients with PAI, 23 (23.7%) were HIV positive. Only 18.6% of patients with PAI presented with complaints related to sexually transmitted infections. CONCLUSIONS: Syphilis rates in this community are very high, and many infections were found in populations traditionally considered at lower risk by demographic or presenting complaint, indicating that universal screening is needed. Routine ED syphilis screening in high-prevalence communities will be critical to addressing the syphilis epidemic.

Machine Learning and Clinical Informatics for Improving HIV Care Continuum Outcomes.

PURPOSE OF REVIEW: This manuscript reviews the use of electronic medical record (EMR) data for HIV care and research along the HIV care continuum with a specific focus on machine learning methods and clinical informatics interventions. RECENT FINDINGS: EMR-based clinical decision support tools and electronic alerts have been effectively utilized to improve HIV care continuum outcomes. Accurate EMR-based machine learning models have been developed to predict HIV diagnosis, retention in care, and viral suppression. Natural language processing (NLP) of clinical notes and data sharing between healthcare systems and public health agencies can enhance models for identifying people living with HIV who are undiagnosed or in need of relinkage to care. Challenges related to using these technologies include inconsistent EMR documentation, alert fatigue, and the potential for bias. Clinical informatics and machine learning models are promising tools for improving HIV care continuum outcomes. Future research should focus on methods for combining EMR data with additional data sources (e.g., social media, geospatial data) and studying how to effectively implement predictive models for HIV care into clinical practice.

Partner Notification Services for Patients with Established and New HIV Infection Leads to Diagnosis and Linkage of HIV-Positive Partners.

Offering people living with HIV the opportunity to refer partners for HIV testing is an efficient way of identifying new HIV diagnoses. This report describes the outcomes of physician-led partner services at an urban academic center. Patients with HIV VL > 1000 copies/mL in both inpatient and outpatient settings were offered partner notification services (PNS). Of referred partners, 8.7% had a new diagnosis of HIV. New HIV+ partners were as likely to be referred by patients with existing HIV diagnoses as new diagnoses (p = 0.61), and as likely to be referred by patients interviewed while hospitalized as those in the clinic (p = 0.61).

"That same stigma...that same hatred and negativity:" a qualitative study to understand stigma and medical mistrust experienced by people living with HIV diagnosed with COVID-19.

BACKGROUND: The COVID-19 and HIV epidemics have exacerbated existing inequities among vulnerable groups and severely impacted communities of color. People living with HIV (PLWH), who may already face stigma or discrimination, are at risk of experiencing further stigma as a result of COVID-19, which can result in medical mistrust. METHODS: We performed qualitative interviews between June and August 2020 among 32 PLWH, including 10 individuals diagnosed with COVID-19. A majority of participants perceived themselves as having an increased risk of contracting COVID-19 due to their HIV status. RESULTS: Of those who tested positive for COVID-19, the majority regarded their HIV diagnosis as having a more profound impact on their lives but found similarities between COVID-19 stigma and HIV-related stigma. Many participants also expressed mistrust. CONCLUSIONS: These results can be used to better understand the perspectives of PLWH during the COVID-19 pandemic and have important implications for potential COVID-19 vaccine hesitancy and future health crises.

Reducing the use of empiric antibiotic therapy in COVID-19 on hospital admission.

BACKGROUND: Empiric antibiotics for community acquired bacterial pneumonia (CABP) are often prescribed to patients with COVID-19, despite a low reported incidence of co-infections. Stewardship interventions targeted at facilitating appropriate antibiotic prescribing for CABP among COVID-19 patients are needed. We developed a guideline for antibiotic initiation and discontinuation for CABP in COVID-19 patients. The purpose of this study was to assess the impact of this intervention on the duration of empiric CABP antibiotic therapy among patients with COVID-19. METHODS: This was a single-center, retrospective, quasi-experimental study of adult patients admitted between 3/1/2020 to 4/25/2020 with COVID-19 pneumonia, who were initiated on empiric CABP antibiotics. Patients were excluded if they were initiated on antibiotics > 48 h following admission or if another source of infection was identified. The primary outcome was the duration of antibiotic therapy (DOT) prior to the guideline (March 1 to March27, 2020) and after guideline implementation (March 28 to April 25, 2020). We also evaluated the clinical outcomes (mortality, readmissions, length of stay) among those initiated on empiric CABP antibiotics. RESULTS: A total of 506 patients with COVID-19 were evaluated, 102 pre-intervention and 404 post-intervention. Prior to the intervention, 74.5% (n = 76) of patients with COVID-19 received empiric antibiotics compared to only 42% of patients post-intervention (n = 170), p < 0.001. The median DOT in the post-intervention group was 1.3 days shorter (p < 0.001) than the pre-intervention group, and antibiotics directed at atypical bacteria DOT was reduced by 2.8 days (p < 0.001). More patients in the post-intervention group were initiated on antibiotics based on criteria consistent with our guideline (68% versus 87%, p = 0.001). There were no differences between groups in terms of clinical outcomes. CONCLUSION: Following the implementation of a guideline outlining recommendations for initiating and discontinuing antibiotics for CABP among COVID-19 inpatients, we observed a reduction in antibiotic prescribing and DOT. The guideline also resulted in a significant increase in the rate of guideline-congruent empiric antibiotic initiation.

Impact of mail order pharmacy use and travel time to pharmacy on viral suppression among people living with HIV.

This study aimed to evaluate the impact of mail order pharmacy services and travel time to pharmacy on HIV viral suppression rates among people living with HIV. For adult patients receiving HIV care from 2010 to 2015 at an urban HIV care clinic, we collected demographics, pharmacy type, viral load, and patient home and pharmacy address. We geocoded addresses and measured travel time to pharmacy by car and public transportation. No difference was observed in recent viral suppression rates based on pharmacy type (p = 0.41), distance to pharmacy (p = 0.16), or travel time to pharmacy by car (p = 0.20) or public transportation (p = 0.15). The only factors significantly associated with sustained viral suppression were number of doses per day of antiretroviral therapy, with patients prescribed twice daily regimens less likely to be virally suppressed than those prescribed once daily regimens (aOR 0.4, 95% CI, [0.1, 0.6]) and average household income in patients' zip code, with patients living in zip codes with average household income <$40,000 per year less likely to be virally suppressed than those living in zip codes with average income >$55,000 per year (aOR 0.2. 95% CI, [0.1, 0.7]).

Decreasing Incidence of Skin and Soft-tissue Infections in 86 US Emergency Departments, 2009-2014.

Background: The incidence of skin and soft-tissue infections (SSTIs), for which human immunodeficiency virus (HIV) is a significant risk factor, in United States emergency departments (EDs) increased dramatically after 2000 with the emergence of community-associated methicillin-resistant Staphylococcus aureus. Few studies have examined SSTI incidence among HIV-infected and non-HIV-infected patients in the United States after 2010. Methods: Data were obtained for patient encounters at all academic medical center EDs affiliated with the Vizient clinical data warehouse assigned an SSTI-associated code based on the International Classification of Diseases, Ninth Revision, between 1 January 2009 and 31 December 2014. The rate was calculated per 1000 ED encounters by year and stratified by SSTI, HIV infection, or both, and by age group, race, payer type, and region of care. Poisson regression was used to assess temporal change over the study period. Results: In 2009-2014, a total of 47317 HIV-associated and 820440 SSTI-associated encounters were recorded among 25239781 ED patient encounters. The rate of SSTIs decreased by 8% among all patients and by 14.6%, among those with HIV infection. The SSTI incidence overall decreased from 32.0 to 29.7 per 1000 ED encounters between 2009 and 2014. HIV-infected patients had a significantly higher rate of SSTIs than HIV-uninfected patients (adjusted rate ratio, 1.91; 95% confidence interval, 1.84-1.99). Conclusions: The decline in SSTI incidence in US EDs between 2009 and 2014 is a remarkable epidemiologic shift from the increase in SSTIs after 2000, and further research is necessary to assess reasons for this decrease.

A Clinical Informatics Approach to Reengagement in HIV Care in the Emergency Department.

Emergency department visits provide an opportunity to reengage people living with HIV (PLWH) who are out of care. We developed an electronic medical record-based algorithm to identify PLWH in the emergency department and inpatient settings and utilized a trained HIV care navigator to reengage PLWH in these settings. The algorithm identified 420 PLWH during the 14-month observation period. Of these, 56 patients were out of care. Out-of-care individuals were significantly younger than those in care (mean age: 38.6 ± 15.5 vs 46.3 ±14.8 years, P < .001) and more likely to be uninsured (7.1% [4/56] vs 1.8% [6/337], P = .02). Among out-of-care patients, 66.1% (37/56) were reengaged in care. Only 21.4% (12/56) of out-of-care patients had previously received outpatient HIV care at our institution. This project demonstrates the feasibility of using an electronic medical record alert and HIV care navigator to reengage PLWH seeking emergency medical care.