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.

Evaluation of multiple data sources for predicting increased need for HIV prevention among cisgender women: understanding missed opportunities for Pre-exposure Prophylaxis (PrEP).

BACKGROUND: Ciswomen constitute a disproportionately low percentage of pre-exposure prophylaxis for HIV prevention (PrEP) users compared to men. Despite PrEP's effectiveness, women are 5.25 times less likely to take PrEP than men. Identifying women who have increased reasons for HIV prevention and educating and offering PrEP to these women is crucial to reducing HIV transmission and overall health equity. However, the best method of identifying women at highest risk of acquiring HIV remains unknown. This study aimed to identify common HIV risk factors and data sources for identifying these common factors (e.g., electronic medical record data, open source neighborhood data), as well as potential intervention points and missed opportunities for PrEP linkage. METHODS: We conducted an evaluation of multiple data sources: semi-structured qualitative interviews, electronic medical record (EMR) chart abstraction, and open source data abstraction. We accessed EMRs for enrolled participants and all participants signed a standard release of medical information (ROI) form for all institutions at which they had received medical care for the five-year period preceding their HIV diagnosis. Data were abstracted using a standardized procedure. Both structured and unstructured fields (i.e., narrative text of free notes) within the EMR were examined and included for analysis. Finally, open data sources (e.g., STI cases, HIV prevalence) were examined by community area of Chicago. Open data sources were used to examine several factors contributing to the overall Economic Hardship Index (EHI) score. We used these calculated scores to assess the economic hardship within participants' neighborhoods. RESULTS: A total of 18 cisgender women with HIV participated in our study. Participants were mostly Black/African American (55.6%) and young (median age of 34). Our analysis identified two main themes influencing HIV risk among participants: contextual factors and relationship factors. Further, potential pre-diagnosis intervention points and missed opportunities were identified during reproductive health/prenatal visits, behavioral/mental health visits, and routine STI testing. Our evaluation of multiple data sources included investigating the presence or absence of information in the EMR (STI history, HIV testing, substance use, etc.) as well as whether pertinent information could be gathered from open access sources. CONCLUSION: Ciswomen recently diagnosed with HIV identified many shared experiences, including syndemic conditions like mental illness and substance abuse, sex with men who have sex with men, and frequent moving in areas with high HIV incidence prior to their diagnosis. It is imperative that providers ask patients about social history, information about partners, and other key variables, in addition to the standardized questions. Findings can be used to better recognize ciswomen most vulnerable to HIV and offer PrEP to them, reducing HIV transmission.

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).

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.

"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.

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.

"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.

Exploring the Feasibility of an Electronic Tool for Predicting Retention in HIV Care: Provider Perspectives.

Retention in care for people living with HIV (PLWH) is important for individual and population health. Preemptive identification of PLWH at high risk of lapsing in care may improve retention efforts. We surveyed providers at nine institutions throughout Chicago about their perspectives on using an electronic health record (EHR) tool to predict the risk of lapsing in care. Sixty-three percent (20/32) of providers reported currently assessing patients' risk for lapsing in care, and 91% (29/32) reported willingness to implement an EHR tool. When compared to those with other job roles, prescribers agreed (vs. neutral) that the tool would be less biased than personal judgment (OR 13.33, 95% CI 1.05, 169.56). Prescribers were also more likely to identify community health workers as persons who should deliver these interventions (OR 10.50, 95% CI 1.02, 108.58). Transportation, housing, substance use, and employment information were factors that providers wanted to be included in an EHR-based tool. Social workers were significantly more likely to indicate the inclusion of employment information as important (OR 10.50, 95% CI 1.11, 98.87) when compared to other participants. Acceptability of an EHR tool was high; future research should investigate barriers and evaluate the effectiveness of such a tool.

"There hasn't been a push to identify patients in the emergency department"-Staff perspectives on automated identification of candidates for pre-exposure prophylaxis (PrEP): A qualitative study.

Automated algorithms for identifying potential pre-exposure prophylaxis (PrEP) candidates are effective among men, yet often fail to detect cisgender women (hereafter referred to as "women") who would most benefit from PrEP. The emergency department (ED) is an opportune setting for implementing automated identification of PrEP candidates, but there are logistical and practical challenges at the individual, provider, and system level. In this study, we aimed to understand existing processes for identifying PrEP candidates and to explore determinants for incorporating automated identification of PrEP candidates within the ED, with specific considerations for ciswomen, through a focus group and individual interviews with ED staff. From May to July 2021, we conducted semi-structured qualitative interviews with 4 physicians and a focus group with 4 patient advocates working in a high-volume ED in Chicago. Transcripts were coded using Dedoose software and analyzed for common themes. In our exploratory study, we found three major themes: 1) Limited PrEP knowledge among ED staff, particularly regarding its use in women; 2) The ED does not have a standardized process for assessing HIV risk; and 3) Perspectives on and barriers/facilitators to utilizing an automated algorithm for identifying ideal PrEP candidates. Overall, ED staff had minimal understanding of the need for PrEP among women. However, participants recognized the utility of an electronic medical record (EMR)-based automated algorithm to identify PrEP candidates in the ED. Facilitators to an automated algorithm included organizational support/staff buy-in, patient trust, and dedicated support staff for follow-up/referral to PrEP care. Barriers reported by participants included time constraints, hesitancy among providers to prescribe PrEP due to follow-up concerns, and potential biases or oversight resulting from missing or inaccurate information within the EMR. Further research is needed to determine the feasibility and acceptability of an EMR-based predictive HIV risk algorithm within the ED setting.

Reflex Human Immunodeficiency Virus (HIV) Type 1 RNA Testing Enables Timely Differentiation of False-Positive Results From Acute HIV Infection.

Accurate, timely human immunodeficiency virus (HIV) diagnosis is critical. Routine HIV screening program data were examined before and after reflex HIV type 1 RNA testing. Reflex testing facilitated confirmation of reactive HIV screening assays (as true or false positives) (odds ratio, 23.7 [95% confidence interval, 6.7-83.4]; P < .0001), improving detection of acute HIV and reducing unconfirmed discordant results.

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. In this study, we assessed women's attitudes and opinions about an automated EMR-based HIV risk algorithm and determined if their perspectives varied by level of HIV risk. Respondents were identified using best practice alerts or referral to a clinic for STI symptoms from January to December 2021 in Chicago, IL. Participants were asked about HIV risk factors, their self-perceived HIV risk, and their thoughts regarding an algorithm to identify ciswomen who could benefit from PrEP. Most of the 112 women who completed the survey (85%) thought they were at low risk for HIV, despite high rates of STI diagnoses. The majority were comfortable with the use of this algorithm, but their comfort level dropped when asked about the algorithm identifying them specifically. Ciswomen had mixed feelings about the use of an automated HIV risk algorithm, citing it as a potentially helpful and empowering tool for women, yet raising concerns about invasion of privacy and potential racial bias. Clinics must balance the benefits of using an EMR-based algorithm for ciswomen with their concerns about privacy and bias to improve PrEP uptake among particularly vulnerable women.

Predictive Modeling of Lapses in Care for People Living with HIV in Chicago: Algorithm Development and Interpretation.

BACKGROUND: Reducing care lapses for people living with HIV is critical to ending the HIV epidemic and beneficial for their health. Predictive modeling can identify clinical factors associated with HIV care lapses. Previous studies have identified these factors within a single clinic or using a national network of clinics, but public health strategies to improve retention in care in the United States often occur within a regional jurisdiction (eg, a city or county). OBJECTIVE: We sought to build predictive models of HIV care lapses using a large, multisite, noncurated database of electronic health records (EHRs) in Chicago, Illinois. METHODS: We used 2011-2019 data from the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN), a database including multiple health systems, covering the majority of 23,580 people with an HIV diagnosis living in Chicago. CAPriCORN uses a hash-based data deduplication method to follow people across multiple Chicago health care systems with different EHRs, providing a unique citywide view of retention in HIV care. From the database, we used diagnosis codes, medications, laboratory tests, demographics, and encounter information to build predictive models. Our primary outcome was lapses in HIV care, defined as having more than 12 months between subsequent HIV care encounters. We built logistic regression, random forest, elastic net logistic regression, and XGBoost models using all variables and compared their performance to a baseline logistic regression model containing only demographics and retention history. RESULTS: We included people living with HIV with at least 2 HIV care encounters in the database, yielding 16,930 people living with HIV with 191,492 encounters. All models outperformed the baseline logistic regression model, with the most improvement from the XGBoost model (area under the receiver operating characteristic curve 0.776, 95% CI 0.768-0.784 vs 0.674, 95% CI 0.664-0.683; P<.001). Top predictors included the history of care lapses, being seen by an infectious disease provider (vs a primary care provider), site of care, Hispanic ethnicity, and previous HIV laboratory testing. The random forest model (area under the receiver operating characteristic curve 0.751, 95% CI 0.742-0.759) revealed age, insurance type, and chronic comorbidities (eg, hypertension), as important variables in predicting a care lapse. CONCLUSIONS: We used a real-world approach to leverage the full scope of data available in modern EHRs to predict HIV care lapses. Our findings reinforce previously known factors, such as the history of prior care lapses, while also showing the importance of laboratory testing, chronic comorbidities, sociodemographic characteristics, and clinic-specific factors for predicting care lapses for people living with HIV in Chicago. We provide a framework for others to use data from multiple different health care systems within a single city to examine lapses in care using EHR data, which will aid in jurisdictional efforts to improve retention in HIV care.

Ending the HIV Epidemic: Identifying Barriers and Facilitators to Implement Molecular HIV Surveillance to Develop Real-Time Cluster Detection and Response Interventions for Local Communities.

The rapid implementation of molecular HIV surveillance (MHS) has resulted in significant challenges for local health departments to develop real-time cluster detection and response (CDR) interventions for priority populations impacted by HIV. This study is among the first to explore professionals' strategies to implement MHS and develop CDR interventions in real-world public health settings. Methods: Semi-structured qualitative interviews were completed by 21 public health stakeholders in the United States' southern and midwestern regions throughout 2020-2022 to identify themes related to the implementation and development of MHS and CDR. Results for the thematic analysis revealed (1) strengths and limitations in utilizing HIV surveillance data for real-time CDR; (2) limitations of MHS data due to medical provider and staff concerns related to CDR; (3) divergent perspectives on the effectiveness of partner services; (4) optimism, but reluctance about the social network strategy; and (5) enhanced partnerships with community stakeholders to address MHS-related concerns. Conclusions: Enhancing MHS and CDR efforts requires a centralized system for staff to access public health data from multiple databases to develop CDR interventions; designating staff dedicated to CDR interventions; and establishing equitable meaningful partnerships with local community stakeholders to address MHS concerns and develop culturally informed CDR interventions.

Multi-Level and Intersectional Stigma Experienced by Black Transgender Women in Chicago: a Qualitative Study to Inform Sociostructural Interventions for Reducing Stigma and Improving Health Outcomes.

BACKGROUND: Stigma contributes to health disparities including increased HIV vulnerability among minority communities. Black transgender women experience multiple forms of stigma (e.g., anticipated, experienced), which can result in poor HIV-related outcomes. We utilized an adapted social ecological model (ASEM) to better understand the levels at which stigma is encountered and its impact on lived experience, particularly related to making healthcare decisions. METHODS: Semi-structured interviews and two focus groups (n = 38) were conducted with Black transgender women and Black transfeminine individuals in Chicago from 2016 to 2017. Participants were asked about discrimination in the community, healthcare experiences, and their thoughts and decision-making process with their healthcare provider regarding HIV pre-exposure prophylaxis. We conducted thematic analysis and organized our findings based on the levels of the ASEM: individual, interpersonal, organizational, community, and structural. RESULTS: Participants experienced and anticipated stigma at each ASEM level. Stigma was not experienced in isolation: stigma experienced at one level caused anticipated stigma at other levels and internalized stigma leading to negative self-image. In each case, stigma adversely impacted health outcomes (e.g., medication nonadherence, disengagement from care). Stigma within healthcare settings, medication-related stigma, and stigma directed at appearance and identity are particularly detrimental to shared decision-making with a healthcare provider. CONCLUSIONS: Recognizing and valuing Black transgender women's experience with stigma are essential for developing social and structural interventions that may work collaboratively across multiple levels of lived experience to reduce stigma and healthcare disparities faced by Black transgender women.

POWER Up-Improving pre-exposure prophylaxis (PrEP) uptake among Black cisgender women in the Southern United States: Protocol for a stepped-wedge cluster randomized trial (SW-CRT).

BACKGROUND: HIV disproportionately affects Black/African American cisgender women (hereafter women) in the United States. Despite its proven effectiveness, pre-exposure prophylaxis (PrEP) for HIV prevention remains vastly under-prescribed to women based on their need. Increasing PrEP uptake and persistence among women is crucial to reducing HIV transmission; however, there have been few studies designed specifically for women. This article describes the study protocol used to assess the feasibility, acceptability, and effectiveness of implementation strategies to improve PrEP uptake and persistence among Black women in the Midwest and South. METHODS: PrEP Optimization among Women to Enhance Retention and Uptake (POWER Up) is an evidence-based, woman-focused set of five implementation science strategies that addresses barriers of PrEP utilization at the provider, patient, and clinic levels. POWER Up includes 1) routine PrEP education for patients, 2) standardized provider training, 3) electronic medical record (EMR) optimization, 4) PrEP navigation, and 5) PrEP clinical champions. These strategies will be adapted to specific clinics for implementation, tested via a stepped-wedge trial, and, if effective, packaged for further dissemination. DISCUSSION: We will utilize a stepped-wedge cluster randomized trial (SW-CRT) to measure change in PrEP utilization across diverse geographic areas. Preparation for adapting and implementing the bundle of strategies is needed to determine how to tailor them to specific clinics. Implementation challenges will include adapting strategies with the available resources at each site, maintaining stakeholder involvement and staff buy-in, adjusting the study protocol and planned procedures as needed, and ensuring minimal crossover. Additionally, strengths and limitations of each strategy must be examined before, during, and after the adaptation and implementation processes. Finally, the implementation outcomes of the strategies must be evaluated to determine the real-world success of the strategies. This study is an important step toward addressing the inequity in PrEP service delivery and increasing PrEP utilization among Black women in the U.S.