HIV Data to Care-Using Public Health Data to Improve HIV Care and Prevention

Challenges and Opportunities in Big Data Science to Address Health Inequities and Focus the HIV Response

PURPOSE OF REVIEW

Big Data Science can be used to pragmatically guide the allocation of resources within the context of national HIV programs and inform priorities for intervention. In this review, we discuss the importance of grounding Big Data Science in the principles of equity and social justice to optimize the efficiency and effectiveness of the global HIV response.

RECENT FINDINGS

Social, ethical, and legal considerations of Big Data Science have been identified in the context of HIV research. However, efforts to mitigate these challenges have been limited. Consequences include disciplinary silos within the field of HIV, a lack of meaningful engagement and ownership with and by communities, and potential misinterpretation or misappropriation of analyses that could further exacerbate health inequities. Big Data Science can support the HIV response by helping to identify gaps in previously undiscovered or understudied pathways to HIV acquisition and onward transmission, including the consequences for health outcomes and associated comorbidities. However, in the absence of a guiding framework for equity, alongside meaningful collaboration with communities through balanced partnerships, a reliance on big data could continue to reinforce inequities within and across marginalized populations.

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.

Enhancements to the National HIV Surveillance System, United States, 2013-2023

HIV infection is monitored through the National HIV Surveillance System (NHSS) to help improve the health of people with HIV and reduce transmission. NHSS data are routinely used at federal, state, and local levels to monitor the distribution and transmission of HIV, plan and evaluate prevention and care programs, allocate resources, inform policy development, and identify and respond to rapid transmission in the United States. We describe the expanded use of HIV surveillance data since the 2013 NHSS status update, during which time the Centers for Disease Control and Prevention (CDC) coordinated to revise the HIV surveillance case definition to support the detection of early infection and reporting of laboratory data, expanded data collection to include information on sexual orientation and gender identity, enhanced data deduplication processes to improve quality, and expanded reporting to include social determinants of health and health equity measures. CDC maximized the effects of federal funding by integrating funding for HIV prevention and surveillance into a single program; the integration of program funding has expanded the use of HIV surveillance data and strengthened surveillance, resulting in enhanced cluster response capacity and intensified data-to-care activities to ensure sustained viral suppression. NHSS data serve as the primary source for monitoring HIV trends and progress toward achieving national initiatives, including the US Department of Health and Human Services' Ending the HIV Epidemic in the United States initiative, the White House's National HIV/AIDS Strategy (2022-2025), and Healthy People 2030. The NHSS will continue to modernize, adapt, and broaden its scope as the need for high-quality HIV surveillance data remains.

Overview of the US National HIV Strategy and Ending the HIV Epidemic Initiative

The US National HIV/AIDS Strategy (NHAS) is a comprehensive plan that outlines specific goals for Ending the HIV Epidemic in the United States (EHE) by 2025. The strategy also provides specific strategies to prevent new HIV infections and improve health outcomes for people with HIV. The EHE is a companion document which focuses on achieving the goals of the NHAS in specific US jurisdictions where the HIV epidemic is concentrated. This article provides an overview of the NHAS and EHE and provides examples of programs and strategies that can be used to end the HIV epidemic in the United States.

Using Data-To-Care Strategies to Optimize the HIV Care Continuum in Connecticut: Results From a Randomized Controlled Trial

BACKGROUND

Re-engaging people with HIV who are newly out-of-care remains challenging. Data-to-care (D2C) is a potential strategy to re-engage such individuals.

METHODS

A prospective randomized controlled trial compared a D2C strategy using a disease intervention specialist (DIS) vs standard of care where 23 HIV clinics in 3 counties in Connecticut could re-engage clients using existing methods. Using a data reconciliation process to confirm being newly out-of-care, 655 participants were randomized to DIS (N = 333) or standard of care (N = 322). HIV care continuum outcomes included re-engagement at 90 days, retention in care, and viral suppression by 12 months. Multivariable regression models were used to assess factors predictive of attaining HIV care continuum outcomes.

RESULTS

Participants randomized to DIS were more likely to be re-engaged at 90 days (adjusted odds ratios [aOR] = 1.42, P = 0.045). Independent predictors of re-engagement at 90 days were age older than 40 years (aOR = 1.84, P = 0.012) and perinatal HIV risk category (aOR = 3.19, P = 0.030). Predictors of retention at 12 months included re-engagement at 90 days (aOR = 10.31, P < 0.001), drug injection HIV risk category (aOR = 1.83, P = 0.032), detectable HIV-1 RNA before randomization (aOR = 0.40, P = 0.003), and county (Hartford aOR = 1.74, P = 0.049; New Haven aOR = 1.80, P = 0.030). Predictors of viral suppression included re-engagement at 90 days (aOR = 2.85, P < 0.001), retention in HIV care (aOR = 7.07, P < 0.001), and detectable HIV-1 RNA prerandomization (aOR = 0.23, P < 0.001).

CONCLUSIONS

A D2C strategy significantly improved re-engagement at 90 days. Early re-engagement improved downstream benefits along the HIV care continuum like retention in care and viral suppression at 12 months. Moreover, other factors predictive of care continuum outcomes can be used to improve D2C strategies.

Misclassification of Loss to Care Among Persons With Human Immunodeficiency Virus: Improved Capture of Silent Transfers Through Surveillance Linkage Using Statewide Mandatorily Reported Laboratory Measures

Human Immunodeficiency Virus (HIV)-positive individuals lost to follow-up from particular clinics may not be lost to care (LTC). After linking Vanderbilt's Comprehensive Care Clinic cohort to Tennessee's statewide HIV surveillance database, LTC decreased from 48.4% to 35.0% at 10 years. Routine surveillance linkage by domestic HIV clinics would improve LTC and retention measure accuracy.

Using the exploration, preparation, implementation, sustainment (EPIS) framework to assess the cooperative re-engagement controlled trial (CoRECT)

Background

"Data to Care" (D2C) is a strategy which relies on a combination of public health surveillance data supplemented by clinic data to support continuity of HIV care. The Cooperative Re-Engagement Controlled Trial (CoRECT) was a CDC-sponsored randomized controlled trial of a D2C model, which provided an opportunity to examine the process of implementing an intervention for people with HIV (PWH) who are out-of-care across three public health department jurisdictions. Using the EPIS (Exploration, Preparation, Implementation, Sustainment) framework, we aimed to retrospectively describe the implementation process for each site to provide insights and guidance to inform future D2C activities implemented by public health agencies and their clinical and community partners.

Methods

After completion of CoRECT, the three (Connecticut, Massachusetts, Philadelphia) trial sites reviewed study protocols and held iterative discussions to describe and compare their processes regarding case identification, interactions with partnering clinics and patients, and sustainability. The EPIS framework provided a structure for comparing key organizational and operational practices and was applied to the entire implementation process.

Results

The trial sites varied in their implementation processes and the specific elements of the intervention. Factors including prior D2C experience, data management and analytic infrastructure, staff capacity, and relationships with clinic partners informed intervention development and implementation. Additionally, this review identified key lessons learned including to: (1) explore new supplemental sources for public health surveillance data; (2) work with stakeholders representing core functions/components in the early stages of the intervention design process; (3) build flexibility into all components of the follow-up activities; and (4) integrate data sharing, project management, and follow-up activities within existing DPH organizational structure.

Conclusion

The CoRECT study provides a general blueprint and lessons learned for implementing a D2C intervention for re-engagement in HIV care. Interventions should be tailored to local operational and structural factors, and responsive to evolving clinical and public health practices.

Integrating a Resilience Framework to Assess Implementation of a Novel HIV Care Re-Engagement Model in NYC

BACKGROUND

The Bottom Up Project, a collaboration of clinical, community, and academic partners, consists of 7 major steps that leverage a health information exchange, a system for sharing patient health information, with real-time alerts to mobilize peer outreach workers to find and re-engage persons with HIV disconnected from care. Bottom Up faced implementation challenges in its start-up phase and produced effective responses leading to Project maturation, which we explore using a novel implementation science framework incorporating resilience.

METHODS

We conducted semistructured interviews with implementation staff (N = 6) and meeting minutes and protocols document reviews (N = 35). The Consolidated Framework for Implementation Research and a novel resilience framework guided thematic and process analyses. The resilience framework consisted of the following 3 resilience types: absorptive to cope with adversity, adaptive to adjust as short-term solutions, and transformative to structurally change.

RESULTS

The Project experienced 20 major challenges, 2-5 challenges per step. Challenges were multilevel and of chronic and crisis intensities. Implementers overcame challenges by leveraging multilevel factors that were absorptive, adaptive (most common), and transformative.

DISCUSSION

Bottom Up matured by practicing consistency and flexibility. The Project maintained core operations while under crisis-level stress by strategically simplifying or "downshifting" activities. Transformational responses suggest that specific initiatives can catalyze organizational change.

CONCLUSIONS

Bottom Up implementation demonstrates using diverse tactics to respond to challenges, thereby shaping Project development and in turn organizations. Applying resilience to Consolidated Framework for Implementation Research helps build awareness of active and dynamic processes promoting or impeding the growth and success of intervention-oriented Projects.

Increasing antiretroviral therapy adherence and retention in care among adults living with HIV in Philadelphia: a study protocol for a stepped-wedge cluster-randomised type 2 hybrid effectiveness-implementation trial of managed problem-solving plus (MAPS+) delivered by community health workers

INTRODUCTION

To end the HIV epidemic in Philadelphia, implementation of evidence-based practices (EBP) to increase viral suppression and retention in HIV care is critical. Managed problem solving (MAPS), an EBP for antiretroviral therapy adherence, follows a problem-solving approach to empower people living with HIV (PWH) to manage their health. To overcome barriers to care experienced by PWH in Philadelphia, the EBP was adapted to include a focus on care retention and delivery by community health workers (CHWs). The adapted intervention is MAPS+. To maximise the clinical impact and reach of the intervention, evaluation of the effectiveness and implementation of MAPS+ is necessary.

METHODS AND ANALYSIS

This manuscript describes the protocol for a stepped-wedge cluster-randomised type 2 hybrid effectiveness-implementation trial in 10 clinics in Philadelphia. This research incorporates innovative approaches to accomplish three objectives: (1) to evaluate the effectiveness of the CHW-led MAPS+ intervention to improve viral suppression and retention in care 1 year after the individual implementation period (N=390 participants), (2) to examine the effect of the menu of implementation strategies on reach and implementation cost and (3) to examine processes, mechanisms, and sustainment of the implementation strategies for MAPS+ (N=56 participants). Due to various factors (eg, COVID-19), protocol modifications have occurred.

ETHICS AND DISSEMINATION

The institutional review board (IRB) at the city of Philadelphia serves as the primary IRB; initial approval was granted on 21 December 2020. The University of Pennsylvania and Northwestern University executed reliance agreements. A safety monitoring committee comprised experts in implementation science, biostatistics and infectious diseases oversee this study. This research will offer insights into achieving the goals to end the HIV epidemic in Philadelphia as well as implementation efforts of MAPS+ and other behavioural interventions aimed at increasing medication adherence and retention in care. Dissemination will include deliverables (eg, peer-reviewed manuscripts and lay publications) to reach multiple constituents.

TRIAL REGISTRATION NUMBER

NCT04560621.

Laboratory services in the context of prevention of mother-to-child transmission of HIV testing requirements in Copperbelt Province, Zambia: a qualitative inquiry

INTRODUCTION

Reliable and timely laboratory results are crucial for monitoring the Prevention of the Mother-to-Child Transmission (PMTCT) cascade, particularly to enable early HIV diagnosis and early intervention. We sought to explore whether and how laboratory services have been prepared to absorb new testing requirements following PMTCT Test-and-Treat policy changes in three districts of Zambia.

METHOD

We employed in-depth interviews and thematic data analysis, informed by the health system dynamic framework. Twenty-Six health workers were purposively selected and a document review of laboratory services in the context of PMTCT was undertaken. All face-to-face interviews were conducted in three local government areas in the Copperbelt Province (one urban and two rural) between February 2019 and July 2020. We extracted notes and markings from the transcripts for coding. Different codes were sorted into potential themes and the data extracted were put within the identified themes. Trustworthiness was confirmed by keeping records of all data field notes, transcripts, and reflexive journals.

RESULTS

The findings revealed that the health system inputs (infrastructure and supplies, human resources, knowledge, and information and finance) and service delivery were unequal between the rural and urban sites, and this affected the ability of health facilities to apply the new testing requirements, especially, in the rural-based health facilities. The major barriers identified include gaps in the capacity of the existing laboratory system to perform crucial PMTCT clinical and surveillance functions in a coordinated manner and insufficient skilled human resources to absorb the increased testing demands. The centralized laboratory system for HIV testing of mothers and exposed neonates meant facilities had to send specimens to other facilities and districts which resulted in high turnaround time and hence delayed HIV diagnosis.

CONCLUSION

New guidelines implemented without sufficient capacitation of health system laboratory capacity severely limited the effectiveness of PMTCT program implementation. This study documented the areas relating to health system inputs and laboratory service delivery where greater support to enable the absorption of the new testing requirements is needed.

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.

Expanding Data to Care Programs to Improve HIV Care Continuum Among Men Who Have Sex With Men and Transgender Persons: Key Processes and Outcomes From Project PrIDE, 2015-2019

OBJECTIVES

During 2015-2019, five local and state health department jurisdictions implemented Data to Care (D2C) programs supported by Project PrIDE (Pre-exposure prophylaxis, Implementation, Data to Care, and Evaluation) to improve linkage or reengagement in HIV medical care among persons with HIV (PWH) who had gaps in care, particularly among men who have sex with men (MSM) and transgender persons. We describe findings from the cross-jurisdiction evaluation of the project.

METHODS

We conducted a qualitative analysis of the final progress reports submitted by PrIDE jurisdictions to the Centers for Disease Control and Prevention to identify key D2C activities implemented and challenges encountered. We also conducted descriptive analysis on aggregate quantitative data to summarize key D2C program outcomes.

RESULTS

PrIDE jurisdictions implemented multiple activities to build their D2C capacity, identify PWH who were not in care or virally suppressed, provide linkage/reengagement services, and monitor outcomes. Overall, 11 463 PWH were selected for follow-up, 45% of whom were MSM or transgender persons. Investigations were completed for 8935 (77.9%) PWH. Only 2323 (26.0%) PWH were confirmed not in care or virally suppressed; 1194 (51.4%) were subsequently linked/reengaged in care; among those, 679 (56.9%) were virally suppressed at last test. PrIDE jurisdictions identified data-related (eg, incomplete or delayed laboratory results), program capacity (eg, insufficient staff), and social and structural (eg, unstable housing) challenges that affected their D2C implementation.

CONCLUSIONS

PrIDE jurisdictions successfully enhanced their D2C capacity, reached priority populations who were not in care or virally suppressed, and improved their engagement in care and health outcomes. Data-related and non-data-related challenges limited the efficiency of D2C programs. Findings can help inform other D2C programs and contribute to national HIV prevention goals.

Costs and cost-effectiveness of a collaborative data-to-care intervention for HIV treatment and care in the United States

INTRODUCTION

Data-to-care programmes utilize surveillance data to identify persons who are out of HIV care, re-engage them in care and improve HIV care outcomes. We assess the costs and cost-effectiveness of re-engagement in an HIV care intervention in the United States.

METHODS

The Cooperative Re-engagement Control Trial (CoRECT) employed a data-to-care collaborative model between health departments and HIV care providers, August 2016-July 2018. The health departments in Connecticut (CT), Massachusetts (MA) and Philadelphia (PHL) collaborated with HIV clinics to identify newly out-of-care patients and randomize them to receive usual linkage and engagement in care services (standard-of-care control arm) or health department-initiated active re-engagement services (intervention arm). We used a microcosting approach to identify the activities and resources involved in the CoRECT intervention, separate from the standard-of-care, and quantified the costs. The cost data were collected at the start-up and recurrent phases of the trial to incorporate potential variation in the intervention costs. The costs were estimated from the healthcare provider perspective.

RESULTS

The CoRECT trial in CT, MA and PHL randomly assigned on average 327, 316 and 305 participants per year either to the intervention arm (n = 166, 159 and 155) or the standard-of-care arm (n = 161, 157 and 150), respectively. Of those randomized, the number of participants re-engaged in care within 90 days in the intervention and standard-of-care arms was 85 and 70 in CT, 84 and 70 in MA, and 98 and 67 in PHL. The additional number of participants re-engaged in care in the intervention arm compared with those in the standard-of-care arm was 15 (CT), 14 (MA) and 31 (PHL). We estimated the annual total cost of the CoRECT intervention at $490,040 in CT, $473,297 in MA and $439,237 in PHL. The average cost per participant enrolled was $2952, $2977 and $2834 and the average cost per participant re-engaged in care was $5765, $5634 and $4482. We estimated an incremental cost per participant re-engaged in care at $32,669 (CT), $33,807 (MA) and $14,169 (PHL).

CONCLUSIONS

The costs of the CoRECT intervention that identified newly out-of-care patients and re-engaged them in HIV care are comparable with other similar interventions, suggesting a potential for its cost-effectiveness in the US context.

Overcoming Challenges to HIV Medical Care-seeking and Treatment Among Data-to-Care Program Clients in Baton Rouge and New Orleans, Louisiana

ABSTRACT

Data to Care (D2C) uses US public health surveillance data to identify persons with diagnosed HIV who are not receiving adequate medical care. These persons are linked to care and ancillary social services through personalized outreach. We conducted semistructured interviews with 36 adults with HIV in Louisiana who were engaged for the first time or reengaged back into HIV care through D2C efforts. Before D2C program staff contact, nearly 40% were not contemplating HIV care. Program clients cited barriers to HIV care, including difficulties with appointment scheduling and transportation, health care service and drug costs, low motivation, and competing non-HIV health needs. Thirty-four of the 36 clients said that D2C staff helped them overcome these barriers. Clients also described psychosocial support from D2C staff. After receiving D2C program assistance, more than 90% of clients reported consistently receiving HIV medical care and taking medications. Our findings suggest that D2C staff successfully identified client needs and provided tailored assistance.

Trends in preexposure prophylaxis use among sex partners as reported by persons with HIV - United States, May 2015-June 2020

OBJECTIVE

To estimate trends in the proportion of sexually active U.S. adults with HIV (PWH) reporting an HIV-discordant sexual partner taking preexposure prophylaxis (PrEP) and proportion of partners taking PrEP.

DESIGN

The Medical Monitoring Project is a complex sample survey of U.S. adults with diagnosed HIV.

METHODS

We used annual cross-sectional data collected during June 2015-May 2020 to estimate the annual percentage change (EAPC), overall and by selected characteristics, in reported partner PrEP use among PWH with HIV-discordant partners (N = 8707) and reported PrEP use among these partners (N = 15 844).

RESULTS

The proportion of PWH reporting PrEP use by one or more HIV-discordant sex partner rose 19.5% annually (11.3 to 24.4%). The prevalence rose from 6.0 to 17.4% (EAPC, 25.8%) among Black PWH, 10.1 to 26.0% (EAPC, 19.5%) among Hispanic/Latino PWH, and 20.8 to 34.6% (EAPC, 16.3%) among White PWH. Among MSM with HIV, the prevalence increased from 9.6 to 32.6% (EAPC, 28.2%) among Black MSM, 16.6 to 36.0% (EAPC, 15.6%) among Hispanic/Latino MSM, and 24.9 to 44.1% (EAPC, 17.9%) among White MSM. Among HIV-discordant sex partners, the proportion reported to be taking PrEP increased 21.1% annually (7.8 to 18.8%). Reported PrEP use rose from 4.9 to 14.2% (EAPC, 29.9%) among Black partners, 6.5 to 16.8% (EAPC, 20.3%) among Hispanic/Latino partners, and 12.7 to 26.1% (EAPC, 17.0%) among White partners.

CONCLUSIONS

One in five HIV-discordant sexual partners of PWH was reported to be taking PrEP. PrEP use rose among all examined populations, although the increases did not eliminate disparities in PrEP use.

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.

Data Velocity in HIV-Related Implementation Research: Estimating Time From Funding to Publication

BACKGROUND

Given available effective biomedical and behavioral prevention and treatment interventions, HIV-related implementation research (IR) is expanding. The rapid generation and dissemination of IR to inform guidelines and practice has the potential to optimize the impact of the Ending the Epidemic Initiative and the HIV pandemic response more broadly.

METHODS

We leveraged a prior mapping review of NIH-funded awards in HIV and IR from January 2013 to March 2018 and identified all publications linked to those grants in NIH RePORTER through January 1, 2021 (n = 1509). Deduplication and screening of nonoriginal research reduced the count to 1032 articles, of which 952 were eligible and included in this review. Publication volume and timing were summarized; Kaplan-Meier plots estimated time to publication.

RESULTS

Among the 215 NIH-funded IR-related awards, 127 of 215 (59%) published original research directly related to the grant, averaging 2.0 articles (SD: 3.3) per award, largely in the early IR phases. Many articles (521 of 952, 55%) attributed to grants did not report grant-related data. Time from article submission to publication averaged 205 days (SD: 107). The median time-to-first publication from funding start was 4 years. Data dissemination velocity varied by award type, trending toward faster publication in recent years. Delays in data velocity included (1) time from funding to enrollment, (2) enrollment length, and (3) time from data collection completion to publication.

CONCLUSION

Research publication was high overall, and time-to-publication is accelerating; however, over 40% of grants have yet to publish findings from grant-related data. Addressing bottlenecks in the production and dissemination of HIV-related IR would reinforce its programmatic and policy relevance in the HIV response.

Comparison of algorithms for identifying people with HIV from electronic medical records in a large, multi-site database

Objective

As electronic medical record (EMR) data are increasingly used in HIV clinical and epidemiologic research, accurately identifying people with HIV (PWH) from EMR data is paramount. We sought to evaluate EMR data types and compare EMR algorithms for identifying PWH in a multicenter EMR database.

Materials and Methods

We collected EMR data from 7 healthcare systems in the Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) including diagnosis codes, anti-retroviral therapy (ART), and laboratory test results.

Results

In total, 13 935 patients had a positive laboratory test for HIV; 33 412 patients had a diagnosis code for HIV; and 17 725 patients were on ART. Only 8576 patients had evidence of HIV-positive status for all 3 data types (laboratory results, diagnosis code, and ART). A previously validated combination algorithm identified 22 411 patients as PWH.

Conclusion

EMR algorithms that combine laboratory results, administrative data, and ART can be applied to multicenter EMR data to identify PWH.

"Take care of their hierarchy of needs first": strategies used by data-to-care staff to address barriers to HIV care engagement

Data-to-Care (D2C) is a public health strategy designed to engage out-of-care (OOC) persons with HIV (PWH) in HIV care. OOC PWH are identified through review of state and local HIV data and engaged in care through individualized efforts that address barriers to HIV care. Perspectives of D2C program staff can contribute to D2C program development and sustainability. We conducted semi-structured interviews in 2017 with 20 D2C program staff from Louisiana (n = 10) and Virginia (n = 10), states with distinct D2C programs. We used content and thematic analysis to analyze interview transcripts. In both states, common barriers to care for OOC PWH include limited transportation, stigma, substance use, poverty, homelessness, and mental illness. To address these barriers and engage OOC clients in HIV care, staff and programs provided transportation vouchers and housing assistance, integrated substance use and mental health services into care engagement processes, provided empathy and compassion, and assessed and addressed basic unmet needs. Identifying and addressing social and structural barriers to HIV care is a critical and often a necessary first step in engaging OOC clients in HIV care. These findings can be used for D2C program design and implementation, facilitating engagement in HIV care for OOC PWH.

Strategies to improve HIV care outcomes for people with HIV who are out of care

OBJECTIVE

The aim of this study was to evaluate the effectiveness of five intervention strategies: patient navigation, appointment help/alerts, psychosocial support, transportation/appointment accompaniment, and data-to-care on HIV care outcomes among persons with HIV (PWH) who are out of care (OOC).

DESIGN

A systematic review with meta-analysis.

METHODS

We searched CDC's Prevention Research Synthesis (PRS) Project's cumulative HIV database to identify intervention studies conducted in the U.S., published between 2000 and 2020 that included comparisons between groups or prepost, and reported at least one relevant outcome (i.e. re-engagement or retention in HIV care, and viral suppression). Effect sizes were meta-analyzed using random-effect models to assess intervention effectiveness.

RESULTS

Thirty-nine studies reporting on 42 unique interventions met the inclusion criteria. Overall, intervention strategies are effective in improving re-engagement in care [odds ratio (OR) = 1.79;95% confidence interval (95% CI): 1.36-2.36, k = 14], retention in care (OR = 2.01; 95% CI: 1.64-2.64, k = 22), and viral suppression (OR = 2.50;95% CI: 1.87-3.34, k = 27). Patient navigation, appointment help/alerts, psychosocial support, and transportation/appointment accompaniment improved all three HIV care outcomes. Data-to-care improved re-engagement and retention but had insufficient evidence for viral suppression.

CONCLUSION

Several strategies are effective for improving HIV care outcomes among PWH who are OOC. More work is still needed for consistent definitions of OOC and HIV care outcomes, better reporting of intervention and cost data, and identifying how best to implement and scale-up effective strategies to engage and retain OOC PWH in care and reach the ending the HIV epidemic goals.

Increased reengagement of out-of-care HIV patients using Lost & Found, a clinic-based intervention

BACKGROUND

Negative health outcomes associated with being out of HIV care (OOC) warrant reengagement strategies. We aimed to assess effectiveness of Lost & Found, a clinic-based intervention to identify and reengage OOC patients.

METHODS

Developed and delivered using implementation science, Lost & Found consists of two core elements: identification, operationalized through nurse validation of a real-time list of possible OOC patients; and contact, via nurse-led phone calls. It was implemented over a 12-month period (2018-2019) at the Chronic Viral Illness Service, McGill University Health Centre (CVIS-MUHC) during a type-II implementation-effectiveness hybrid pilot study. Descriptive outcomes of interest were identification as possibly OOC, OOC confirmation, contact, and successful reengagement. We present results from a pre-post analysis comparing overall reengagement to the year prior, using robust Poisson regression controlled for sex, age, and Canadian birth. Time to reengagement is reported using a Cox proportional hazards model.

RESULTS

Over half (56%; 1312 of 2354) of CVIS-MUHC patients were identified as possibly OOC. Among these, 44% (n = 578) were followed elsewhere, 19% (n = 249) engaged in care, 3% (n = 33) deceased, 2% (n = 29) otherwise not followed, and 32% (n = 423) OOC. Of OOC patients contacted (85%; 359/423), 250 (70%) reengaged and 40 (11%) had upcoming appointments; the remainder were unreachable, declined care, or missed given appointments. Pre-post results indicate people who received Lost & Found were 1.18 [95% confidence interval (CI) 1.02-1.36] times more likely to reengage, and reengaged a median 55 days (95% CI 14-98) sooner.

CONCLUSION

Lost & Found may be a viable clinic-based reengagement intervention for OOC patients. More robust evaluations are needed.

Toward An Enhanced Understanding of HIV Patient Navigation as a Health Care Intervention: An Analysis of Navigation in Practice

Patient navigation is a promising strategy for improving health among persons with multiple barriers to HIV care, yet little is known about navigation's core components. From 24 systematically identified navigation studies, we abstracted navigators' activities, grouped activities into 20 thematic activity categories, and ordered them by frequency. Subsequently, Principal Components Analysis of activity categories was used identify independent clusters. Accompaniment characterized 71% of navigation programs; ≥ half included health education (58%), collaboration/coordination (58%), linkage-to-care (54%), transportation support (54%), service referrals (50%) and instrumental support (50%). Five unique components (comprising 13 activity categories) were identified: (1) services beyond office, (2) health education and relationship building, (3) accompaniment and instrumental support, (4) locating patients and tracking information, and (5) beyond HIV care. Navigators who located patients or tracked information were less likely to provide accompaniment or instrumental support (r = - 0.60, p = 0.002). Findings can enhance precision in developing, describing, evaluating and improving navigation programs.

The HIV Treat Pillar: An Update and Summary of Promising Approaches

The Treat pillar of the Ending the HIV Epidemic in the U.S. plan calls for comprehensive strategies to enhance linkage to, and engagement in, HIV medical care to improve viral suppression among people with HIV and achieve the goal of 95% viral suppression by 2025. The U.S. has seen large increases in the proportion of people with HIV who have a suppressed viral load. Viral suppression has increased 41%, from 46% in 2010 to 65% in 2018. An additional increase of 46% is needed to meet the Ending the HIV Epidemic in the U.S. goal. The rate of viral suppression among those in care increased to 85% in 2018, highlighting the need to ensure sustained care for people with HIV. Greater increases in all steps along the HIV care continuum are needed for those disproportionately impacted by HIV, especially the young, sexual and racial/ethnic minorities, people experiencing homelessness, and people who inject drugs. Informed by systematic reviews and current research findings, this paper describes more recent promising practices that suggest an impact on HIV care outcomes. It highlights rapid linkage and treatment interventions; interventions that identify and re-engage people in HIV care through new collaborations among health departments, providers, and hospital systems; coordinated care and low-barrier clinic models; and telemedicine-delivered HIV care approaches. The interventions presented in this paper provide additional approaches that state and local jurisdictions can use to reach their local HIV elimination plans' goals and the ambitious Ending the HIV Epidemic in the U.S. Treat pillar targets by 2030.

Response to a Large HIV Outbreak, Cabell County, West Virginia, 2018-2019

INTRODUCTION

In January 2019, the West Virginia Bureau for Public Health detected increased HIV diagnoses among people who inject drugs in Cabell County. Responding to HIV clusters and outbreaks is 1 of the 4 pillars of the Ending the HIV Epidemic in the U.S. initiative and requires activities from the Diagnose, Treat, and Prevent pillars. This article describes the design and implementation of a comprehensive response, featuring interventions from all pillars.

METHODS

This study used West Virginia Bureau for Public Health data to identify HIV diagnoses during January 1, 2018-October 9, 2019 among (1) people who inject drugs linked to Cabell County, (2) their sex or injecting partners, or (3) others with an HIV sequence linked to Cabell County people who inject drugs. Surveillance data, including HIV-1 polymerase sequences, were analyzed to estimate the transmission rate and timing of infections using molecular clock phylogenetic analysis. Federal, state, and local partners designed and implemented a comprehensive response during January 2019-October 2019.

RESULTS

Of 82 people identified in the outbreak, most were male (60%), were White (91%), and reported unstable housing (80%). In a large molecular cluster containing 56 of 60 (93%) available sequences, 93% of inferred transmissions occurred after January 1, 2018. HIV testing, HIV pre-exposure prophylaxis, and syringe services were rapidly expanded, leading to improved linkage to HIV care and viral suppression.

CONCLUSIONS

Evidence of rapid transmission in this outbreak galvanized robust collaboration among federal, state, and local partners, leading to critical improvements in HIV prevention and care services. HIV outbreak response requires increased coordination and creativity to improve service delivery to people affected by rapid HIV transmission.

Emergence and evolution of big data science in HIV research: Bibliometric analysis of federally sponsored studies 2000-2019

BACKGROUND

The rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance of Big Data Science. Recently, there have been increasing uptakes of Big Data techniques in basic, clinical, and public health fields of HIV/AIDS research. However, no studies have systematically elaborated on the evolving applications of Big Data in HIV/AIDS research. We sought to explore the emergence and evolution of Big Data Science in HIV/AIDS-related publications that were funded by the US federal agencies.

METHODS

We identified HIV/AIDS and Big Data related publications that were funded by seven federal agencies from 2000 to 2019 by integrating data from National Institutes of Health (NIH) ExPORTER, MEDLINE, and MeSH. Building on bibliometrics and Natural Language Processing (NLP) methods, we constructed co-occurrence networks using bibliographic metadata (e.g., countries, institutes, MeSH terms, and keywords) of the retrieved publications. We then detected clusters among the networks as well as the temporal dynamics of clusters, followed by expert evaluation and clinical implications.

RESULTS

We harnessed nearly 600 thousand publications related to HIV/AIDS, of which 19,528 publications relating to Big Data were included in bibliometric analysis. Results showed that (1) the number of Big Data publications has been increasing since 2000, (2) US institutes have been in close collaborations with China, Canada, and Germany, (3) some institutes (e.g., University of California system, MD Anderson Cancer Center, and Harvard Medical School) are among the most productive institutes and started using Big Data in HIV/AIDS research early, (4) Big Data research was not active in public health disciplines until 2015, (5) research topics such as genomics, HIV comorbidities, population-based studies, Electronic Health Records (EHR), social media, precision medicine, and methodologies such as machine learning, Deep Learning, radiomics, and data mining emerge quickly in recent years.

CONCLUSIONS

We identified a rapid growth in the cross-disciplinary research of HIV/AIDS and Big Data over the past two decades. Our findings demonstrated patterns and trends of prevailing research topics and Big Data applications in HIV/AIDS research and suggested a number of fast-evolving areas of Big Data Science in HIV/AIDS research including secondary analysis of EHR, machine learning, Deep Learning, predictive analysis, and NLP.

Jail-Based Data-to-Care to Improve Continuity of HIV Care: Perspectives and Experiences from Previously Incarcerated Individuals

Incarceration can disrupt retention in HIV care and viral suppression, yet it can also present an opportunity to reengage people living with HIV (PLWH) in care. Data-to-care (D2C) is a promising new public health strategy that uses HIV surveillance data to improve continuity of care for PLWH. The goal of this study was to examine perspectives on and experiences with D2C among PLWH who had recently been incarcerated in jail. Semistructured, qualitative interviews were conducted with 24 PLWH in community and prison settings about (1) knowledge of and experiences with D2C and (2) attitudes about implementing D2C in the jail setting. Participants who had been contacted for D2C described their interactions with state public health workers favorably, although almost half were not aware that the state performs HIV surveillance and D2C. While most participants indicated they would welcome assistance from the state for reengaging in care, they also framed retention in care as an individual responsibility. Most participants supported the idea of jail-based D2C. A vocal minority expressed adamant opposition, citing concerns about the violation of privacy and the threat of violence in the jail setting. Findings from this study suggest that D2C interventions in jails could be beneficial to reengaging PLWH in care, and acceptable to PLWH if done in a way that is sensitive to the needs and concerns of incarcerated individuals. If implemented, jail-based D2C programs must be designed with care to preserve privacy, confidentiality, and the autonomy of incarcerated individuals.

Responding to Outbreaks of Human Immunodeficiency Virus Among Persons Who Inject Drugs-United States, 2016-2019: Perspectives on Recent Experience and Lessons Learned

In 2015, a large human immunodeficiency virus (HIV) outbreak occurred among persons who inject drugs (PWID) in Indiana. During 2016-2019, additional outbreaks among PWID occurred across the United States. Based on information disseminated by responding health departments and Centers for Disease Control and Prevention (CDC) involvement, we offer perspectives about characteristics of and public health responses to 6 such outbreaks. Across outbreaks, injection of opioids (including fentanyl) or methamphetamine predominated; many PWID concurrently used opioids and methamphetamine or cocaine. Commonalities included homelessness or unstable housing, previous incarceration, and hepatitis C virus exposure. All outbreaks occurred in metropolitan areas, including some with substantial harm reduction and medical programs targeted to PWID. Health departments experienced challenges locating case patients and contacts, linking and retaining persons in care, building support to strengthen harm-reduction programs, and leveraging resources. Expanding the concept of vulnerability to HIV outbreaks and other lessons learned can be considered for preventing, detecting, and responding to future outbreaks among PWID.

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.

Comparison of effectiveness and cost for different HIV screening strategies implemented at large urban medical centre in the United States

INTRODUCTION

Incident HIV infections persist in the United States (U.S.) among marginalized populations. Targeted and cost-efficient testing strategies can help in reaching HIV elimination. This analysis compares the effectiveness and cost of three HIV testing strategies in a high HIV burden area in the U.S. in identifying new HIV infections.

METHODS

We performed a cost analysis comparing three HIV testing strategies in Chicago: (1) routine screening (RS) in an inpatient and outpatient setting, (2) modified partner services (MPS) among networks of the recently HIV infected and diagnosed, and (3) a respondent drive sampling (RDS)-based social network (SN) approach targeting young African-American men who have sex with men. All occurred at the same academic medical centre during the following times: routine testing, 2011 to 2016; MPS, 2013 to 2016; SN: 2013 to 2014. Costs were in 2016 dollars and included personnel, HIV testing, training, materials, overhead. Outcomes included cost per test, HIV-positive test and new diagnosis. Sensitivity analyses were performed to assess the impact of population demographics.

RESULTS

The RS programme completed 57,308 HIV tests resulting in 360 (0.6%) HIV-positive tests and 165 new HIV diagnoses (0.28%). The MPS completed 146 HIV tests, resulting in 79 (54%) HIV-positive tests and eight new HIV diagnoses (5%). The SN strategy completed 508 HIV tests, resulting in 210 (41%) HIV-positive tests and 37 new HIV diagnoses (7.2%). Labour accounted for the majority of costs in all strategies. The estimated cost per new HIV diagnosis was $16,773 for the RS programme, $61,418 for the MPS programme and $15,683 for the SN testing programme. These costs were reduced for the RS and MPS strategies in sensitivity analyses limiting testing efficacy to the highest prevalence patient populations ($2,841 and $33,233 respectively).

CONCLUSIONS

The SN strategy yielded the highest proportion of new diagnoses, followed closely by the MPS programme. Both the SN strategy and RS programme were comparable in the cost per new diagnosis. A simultaneous approach that consists of RS in combination with SN testing may be most effective for identifying new HIV infections in settings with heterogeneous epidemics with both high rates of HIV prevalence and HIV testing.

Reassessing the Ethics of Molecular HIV Surveillance in the Era of Cluster Detection and Response: Toward HIV Data Justice

In the United States, clinical HIV data reported to surveillance systems operated by jurisdictional departments of public health are re-used for epidemiology and prevention. In 2018, all jurisdictions began using HIV genetic sequence data from clinical drug resistance tests to identify people living with HIV in "clusters" of others with genetically similar strains. This is called "molecular HIV surveillance" (MHS). In 2019, "cluster detection and response" (CDR) programs that re-use MHS data became the "fourth pillar" of the national HIV strategy. Public health re-uses of HIV data are done without consent and are a source of concern among stakeholders. This article presents three cases that illuminate bioethical challenges associated with re-uses of clinical HIV data for public health. We focus on evidence-base, risk-benefit ratio, determining directionality of HIV transmission, consent, and ethical re-use. The conclusion offers strategies for "HIV data justice." The essay contributes to a "bioethics of the oppressed."

"Is a Bird in the Hand Worth 5 in the Bush?": A Comparison of 3 Data-to-Care Referral Strategies on HIV Care Continuum Outcomes in San Francisco

Background

Health departments utilize HIV surveillance data to identify people with HIV (PWH) who need re-linkage to HIV care as part of an approach known as Data to Care (D2C.) The most accurate, effective, and efficient method of identifying PWH for re-linkage is unknown.

Methods

We evaluated referral and care continuum outcomes among PWH identified using 3 D2C referral strategies: health care providers, surveillance, and a combination list derived by matching an electronic medical record registry to HIV surveillance. PWH who were enrolled in the re-linkage intervention received short-term case management for up to 90 days. Relative risks and 95% confidence intervals were calculated to compare proportions of PWH retained and virally suppressed before and after re-linkage. Durable viral suppression was defined as having suppressed viral loads at all viral load measurements in the 12 months after re-linkage.

Results

After initial investigation, 233 (24%) of 954 referrals were located and enrolled in navigation. Although the numbers of surveillance and provider referrals were similar, 72% of enrolled PWH were identified by providers, 16% by surveillance, and 12% by combination list. Overall, retention and viral suppression improved, although relative increases in retention and viral suppression were only significant among individuals identified by surveillance or providers. Seventy percent of PWH who achieved viral suppression after the intervention remained durably virally suppressed.

Conclusions

PWH referred by providers were more likely to be located and enrolled in navigation than PWH identified by surveillance or combination lists. Overall, D2C re-linkage efforts improved retention, viral suppression, and durable viral suppression.

Practical and Ethical Concerns in Implementing Enhanced Surveillance Methods to Improve Continuity of HIV Care: Qualitative Expert Stakeholder Study

BACKGROUND

Retention in HIV care is critical to maintaining viral suppression and preventing further transmission, yet less than 50% of people living with HIV in the United States are engaged in care. All US states have a funding mandate to implement Data-to-Care (D2C) programs, which use surveillance data (eg, laboratory, Medicaid billing) to identify out-of-care HIV-positive persons and relink them to treatment.

OBJECTIVE

The purpose of this qualitative study was to identify and describe practical and ethical considerations that arise in planning for and implementing D2C.

METHODS

Via purposive sampling, we recruited 43 expert stakeholders-including ethicists, privacy experts, researchers, public health personnel, HIV medical providers, legal experts, and community advocates-to participate in audio-recorded semistructured interviews to share their perspectives on D2C. Interview transcripts were analyzed across a priori and inductively derived thematic categories.

RESULTS

Stakeholders reported practical and ethical concerns in seven key domains: permission and consent, government assistance versus overreach, privacy and confidentiality, stigma, HIV exceptionalism, criminalization, and data integrity and sharing.

CONCLUSIONS

Participants expressed a great deal of support for D2C, yet also stressed the role of public trust and transparency in addressing the practical and ethical concerns they identified.

Reported preexposure prophylaxis use among male sex partners of HIV-positive men: 2016-2018

OBJECTIVE

To estimate the proportion of US HIV-positive men who report a male HIV-negative/unknown status (HIV-discordant) sexual partner taking preexposure prophylaxis (PrEP), and the use of multiple HIV prevention strategies within partnerships.

DESIGN

The Medical Monitoring Project is a complex sample survey of US adults with diagnosed HIV.

METHODS

We used data collected during June 2016 to May 2018 among sexually active HIV-positive men who had at least one HIV-discordant male partner (N = 1871) to estimate the weighted prevalence of reporting at least one partner taking PrEP. Among HIV-discordant partnerships (N = 4029), we estimated PrEP use, viral suppression among HIV-positive partners, and condomless anal sex. We evaluated significant (P < 0.05) differences between groups using prevalence ratios with predicted marginal means.

RESULTS

Twenty-eight percent of sexually active HIV-positive MSM reported at least one HIV-discordant male partner taking PrEP. Twenty percent of HIV-discordant partners were reported to be taking PrEP; 73% were taking PrEP or the HIV-positive partner was virally suppressed. PrEP use was lower among black and Hispanic partners compared with white partners (12% and 19% vs. 27%). Fewer black than white MSM were in partnerships in which PrEP was used or the HIV-positive partner had sustained viral suppression (69% vs. 77%). Condomless anal intercourse was more prevalent in partnerships involving PrEP use and in partnerships involving either PrEP use or sustained viral suppression among the HIV-positive partner.

CONCLUSION

PrEP use was reported among one in five partners, with disparities between black and white partners. Increasing PrEP use and decreasing racial/ethnic disparities could reduce disparities in HIV incidence and help end the US HIV epidemic.