The Value of an Emergency Medicine Virtual Observation Unit.

Study Objective: We implemented a virtual observation unit in which emergency department (ED) patients receive observation-level care at home. Our primary aim was to compare this new care model to in-person observation care in terms of brick-and-mortar ED length of stay (inclusive of ED observation unit time) as well as secondarily on inpatient admission and 72-hour return visits (overall and with admission).

Methods: In a retrospective analysis of electronic health record data on ED observation patients from January 1, 2022 to December 29, 2022 from an academic urban ED, we used propensity matching to compare virtual to in-person observation patients on outcomes of interest.

Assessing Patient Acceptance of an Automated Algorithm to Identify Ciswomen for HIV Pre-Exposure Prophylaxis.

The use of HIV pre-exposure prophylaxis (PrEP) in cisgender women (ciswomen) lags far behind their need. Data elements from the electronic medical record (EMR), including diagnosis of a sexually transmitted infection (STI), can be incorporated into automated algorithms for identifying clients who are most vulnerable to HIV and would benefit from PrEP. However, it is unknown how women feel about the use of such technology.

Concurrent Testing for COVID-19 and HIV Infection at 6 High-Volume Emergency Departments in a Priority Jurisdiction for Ending the HIV Epidemic in the United States.

Background: The COVID-19 pandemic caused disruptions in access to routine HIV screening.

Setting: We assess HIV and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing across 6 emergency departments (EDs) in Cook County, Illinois.

Methods: We retrospectively analyzed the number of SARS-CoV-2 tests, HIV screens, and the proportion of concurrent tests (encounters with both SARS-CoV-2 and HIV testing), correlating with diagnoses of new and acute HIV infection.

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.

COVID-19 Outcomes in Hospitalized Patients With Neurodegenerative Disease: A Retrospective Cohort Study.

Background And Objectives: COVID-19 outcomes in patients with neurodegenerative disorders (NDs) are not well understood, and we hypothesize that there may be increased morbidity and mortality in this group.

Methods: This was a retrospective cohort study performed at 3 hospitals in the Chicagoland area. All patients hospitalized with COVID-19 infection with ND during a 3-month period (March 15, 2020-June 15, 2020) were included and compared with age-matched controls (CL) at 1:1 ratio.

External validation of an opioid misuse machine learning classifier in hospitalized adult patients.

Background: Opioid misuse screening in hospitals is resource-intensive and rarely done. Many hospitalized patients are never offered opioid treatment. An automated approach leveraging routinely captured electronic health record (EHR) data may be easier for hospitals to institute.

Evolution of an Electronic Health Record Based-Human Immunodeficiency Virus (HIV) Screening Program in an Urban Emergency Department for Diagnosing Acute and Chronic HIV Infection.

Background: Since 2006, Centers for Disease Control and Prevention guidelines recommend routine opt-out human immunodeficiency virus (HIV) testing among sexually active 13- to 64-year-olds. Earlier diagnosis and treatment of HIV infection reduces morbidity and mortality and can limit transmission to others.

Objective: Our aim was to increase HIV testing, diagnosis, and linkage to care in the emergency department (ED).

Effect of an obesity best practice alert on physician documentation and referral practices.

The Centers for Medicare & Medicaid Services Electronic Health Record Meaningful Use Incentive Program requires physicians to document body mass index (BMI) and a follow-up treatment plan for adult patients with BMI ≥ 25. To examine the effect of a best practice alert on physician documentation of obesity-related care and referrals to weight management treatment, in a cluster-randomized design, 14 primary care clinics at an academic medical center were randomized to best practice alert intervention (n = 7) or comparator (n = 7). The alert was triggered when both height and weight were entered and BMI was ≥30.