Implementation support for the data-driven components of care in a multisite network of coordinated specialty care programs.

Beyond training providers prior to the roll-out of coordinated specialty care (CSC) for first-episode psychosis in clinical settings, implementation support for data-informed care remains an area that has received very little attention. The current paper describes the development and refinement of implementation support for the data-driven components of care in the New Journeys network, Washington State's CSC model for psychosis, comprised of 14 CSC programs. Using the Evidence-Based System for Innovation Support Logic Model, this paper outlines the individual components for implementation support, tools, training, technical assistance, and quality improvement/evaluation that have been developed for the New Journeys network. We present examples of modifications that have occurred over nine years to address the needs of clients, providers, and state-level network administrators to facilitate the data-driven components of care. We conclude with recommendations based on lessons learned in Washington State aimed at improving implementation of data-driven care in CSC models throughout the USA.

The purpose of this work was to outline the development and strategies used to provide implementation support for the data-driven components of coordinated specialty care programs for early psychosis. We describe the individual use of tools, training, technical assistance, and quality improvement, and how these strategies are used collectively. Based on detailed notes from meetings and correspondence from providers and state-level administrators we present modifications that have occurred to address barriers and needs, essentially using quantitative and qualitative data to inform quality improvement. We then present lessons learned that could be helpful for existing and new coordinated specialty care networks.

Demographics, Trends, and Clinical Characteristics of HIV Pre-Exposure Prophylaxis Recipients and People Newly Diagnosed with HIV from Large Electronic Health Records in Florida.

Florida is one of the HIV epicenters with high incidence and marked sociodemographic disparities. We analyzed a decade of statewide electronic health record/claims data-OneFlorida+-to identify and characterize pre-exposure prophylaxis (PrEP) recipients and newly diagnosed HIV cases in Florida. Refined computable phenotype algorithms were applied and a total of 2186 PrEP recipients and 7305 new HIV diagnoses were identified between January 2013 and April 2021. We examined patients' sociodemographic characteristics, stratified by self-reported sex, along with both frequency-driven and expert-selected descriptions of clinical conditions documented within 12 months before the first PrEP use or HIV diagnosis. PrEP utilization rate increased in both sexes; higher rates were observed among males with sex differences widening in recent years. HIV incidence peaked in 2016 and then decreased with minimal sex differences observed. Clinical characteristics were similar between the PrEP and new HIV diagnosis cohorts, characterized by a low prevalence of sexually transmitted infections (STIs) and a high prevalence of mental health and substance use conditions. Study limitations include the overrepresentation of Medicaid recipients, with over 96% of female PrEP users on Medicaid, and the inclusion of those engaged in regular health care. Although PrEP uptake increased in Florida, and HIV incidence decreased, sex disparity among PrEP recipients remained. Screening efforts beyond individuals with documented prior STI and high-risk behavior, especially for females, including integration of mental health care with HIV counseling and testing, are crucial to further equalize PrEP access and improve HIV prevention programs.

Associations Between Clinic-Based HIV Testing Guidelines and Population-Level HIV Testing Rates in the United States.

ABSTRACT: Between 2005 and 2006, the United States Preventive Services Task Force and the Centers for Disease Control and Prevention revised their risk-based HIV testing guidelines to include universal HIV testing in routine health care. We examined trends in HIV testing and associations with changing policy recommendations using the 2000-2017 National Health Interview Surveys. Multivariable logistic regression and difference-in-difference approach were used to assess rates and correlates of HIV testing before and after the policy changes. Changes in recommendations had minimal effects on overall HIV testing rates but had significant effects on selected subpopulations. The odds of HIV testing increased disproportionately among African Americans, Hispanics, individuals with some college education, low perceived HIV risks, and those who were never married but decreased among those with no regular source of care. A strategy combining risk-based and routine opt-out testing holds promise to rapidly link recently infected individuals to care while reaching individuals who have never been tested.

Characteristics of California Emergency Departments in Centers for Disease Control and Prevention-Designated HIV Priority Counties.

BACKGROUND: Refocused national HIV testing initiatives include a geographic focus. OBJECTIVE: Using a geographic focus, we sought to identify which emergency departments (EDs) might be the most efficient targets for future HIV testing efforts, using California as an example. METHODS: Retrospective analysis of California EDs, emergency physicians, and patients served, along with county-level estimates of HIV prevalence and proportion of the population living in poverty. Emphasis was placed on characterizing EDs affiliated with teaching hospitals and those located in Centers for Disease Control (CDC) and Prevention HIV priority counties. RESULTS: Of the 320 EDs studied, 178 were in priority counties, 29 were affiliated with teaching hospitals, and 24 had both characteristics. Of the 12,869,889 ED visits included, 61.8% occurred in priority counties, 14.7% in EDs affiliated with teaching hospitals, and 12.0% in EDs with both characteristics. The subset of EDs in priority counties with teaching hospital affiliations (compared with priority and nonpriority county ED groups without a teaching hospital affiliation) had higher overall median visit volumes and higher proportions of visits by at-risk and CDC-targeted populations (e.g., individuals who were homeless, those who identified as Black or African American race, and those who identified as Hispanic or Latino ethnicity, all p < 0.01). CONCLUSIONS: EDs in priority counties affiliated with teaching hospitals are major sources of health care in California. These EDs more often serve populations disproportionately impacted by HIV. These departments are efficient targets to direct testing efforts. Increasing testing in these EDs could reduce the burden of undiagnosed HIV in California.

Ageing with HIV in the United States: Changing trends in inpatient hospital stays and comorbidities, 2003-2015.

INTRODUCTION: As people with HIV (PWH) age, they experience prolonged exposure to HIV and antiretroviral therapy, increased risks of developing age-related HIV-associated non-AIDS (HANA) comorbidities and higher rates of hospitalization. Few studies have explored the ageing of PWH and its impact on hospital stays in the US. This study examined trends, characteristics and comorbidities associated with hospital stays with HIV (HSWH) as compared with hospital stays without HIV (HSWOH). METHODS: Thirteen years of pooled National Inpatient Sample (NIS) data from 2003 through 2015 were analysed to describe yearly trends. Trends were evaluated for eight major HANA conditions (cardiovascular disease, cancer, diabetes, liver disease, bone loss, kidney disease, pulmonary disease and neurological disease) across four age groups (18-34, 35-49, 50-64, 65+ years). RESULTS: Although overall rates of hospitalization reduced across all age groups, the proportion of HIV-related hospitalization increased among older Americans. The average number of chronic conditions was higher for HSWH among all age groups and disproportionately increased for older PWH. Although age-adjusted rates of cardiovascular disease, cancer, bone loss and pulmonary disease were lower for HSWH relative to HSWOH, rates increased disproportionately over the study period. The prevalence of all major HANA conditions except cancer and diabetes increased among the elderly (65+), and the prevalence of cardiovascular disease, cancer, bone loss, kidney disease and pulmonary disease also increased among patients aged 50-64 years. CONCLUSIONS: Higher rates of hospitalizations and HANA comorbidities were observed among older HIV patients. The ageing of PWH suggests increased future hospital resource utilization for HSWH. Appropriate training of healthcare providers is essential to managing increased comorbidity burdens of older PWH during hospital stays in the US.

Longitudinal trajectories of HIV care engagement since diagnosis among persons with HIV in the Florida Ryan White program.

HIV care engagement is a dynamic process. We employed group-based trajectory modeling to examine longitudinal patterns in care engagement among people who were newly diagnosed with HIV and enrolled in the Ryan White program in Florida (n = 9,755) between 2010 and 2015. Five trajectories were identified (47.9% "in care" with 1-2 care visit(s) per 6 months, 18.0% "frequent care" with 3 or more care visits per 6 months, 11.0% "re-engage", 11.0% "gradual drop out", 12.6% "early dropout") based on the number of care attendances (including outpatient/case management visits, viral load or CD4 test) for each six-month during the first five years since diagnosis. Relative to "in care", people in the "frequent care" trajectory were more likely to be Hispanic/Latino and older at HIV diagnosis, whereas people in the three suboptimal care retention trajectories were more likely to be younger. Area deprivation index, rurality, and county health rankings were also strongly associated with care trajectories. Individual- and community-level factors associated to the three suboptimal care retention trajectories, if confirmed to be causative and actionable, could be prioritized to improve HIV care engagement.

Estimating resource utilization for emergency department visits by patients' HIV seropositivity in the United States, 2009 to 2018.

INTRODUCTION: The Emergency Department (ED) plays a key role in linkage to and engagement in care for people with HIV (PWH) in the United States, particularly for individuals without a routine source or schedule for care. Assessing patterns of ED resource utilization by PWH can help elucidate the role of EDs across the HIV care continuum. The aim of this study was to use visit-level data to characterize resource utilization patterns for HIV-related ED visit diagnoses compared to those of other ED visit types. METHODS: HIV-related ED visits were identified as either having answered 'have HIV' in a survey question, been diagnosed with HIV, or had HIV noted as a reason for a visit. Weighted, pooled cross-sectional analyses were performed using the National Hospital Ambulatory Medical Care Survey (NHAMCS) for 2009-2018. ED visits were restricted to those aged 13 years and older. Both descriptive and multivariable regression analyses were performed using Stata 15.1 to measure differences in ED resource utilization. RESULTS: A weighted total of 6.10 million ED visits occurred among PWH, representing 5.5 visits per 1000 ED visits. The rates of HIV-related ED visits (per 1000 ED visits) were higher among patients aged 50-64 years (9.1), males (7.9), African Americans (11.1), Medicaid recipients (7.8), patients in the Northeast (6.8), and patients in metropolitan areas (MSA) (6.1). HIV-related ED visits reflected higher resource utilization: including higher utilization of the ambulance, diagnostic tests, blood tests, urinalysis, HIV tests, intravenous fluids, medications, consultants, critical care units, longer visits, and hospital admissions. Multivariable regression models revealed higher ED resource utilization and showed that patients making HIV-related visits were 57% more likely to result in hospital admission, spending 17% more time compared to patients making non-HIV-related visits. CONCLUSION: Hospitals should be prepared to meet the unique needs of PWH presenting for ED services. Continued surveillance of resource utilization patterns among PWH in EDs is important to plan successful HIV care engagement interventions in these settings.

Optimizing Identification of People Living with HIV from Electronic Medical Records: Computable Phenotype Development and Validation.

BACKGROUND: Electronic health record (EHR)-based computable phenotype algorithms allow researchers to efficiently identify a large virtual cohort of Human Immunodeficiency Virus (HIV) patients. Built upon existing algorithms, we refined, improved, and validated an HIV phenotype algorithm using data from the OneFlorida Data Trust, a repository of linked claims data and EHRs from its clinical partners, which provide care to over 15 million patients across all 67 counties in Florida. METHODS: Our computable phenotype examined information from multiple EHR domains, including clinical encounters with diagnoses, prescription medications, and laboratory tests. To identify an HIV case, the algorithm requires the patient to have at least one diagnostic code for HIV and meet one of the following criteria: have 1+ positive HIV laboratory, have been prescribed with HIV medications, or have 3+ visits with HIV diagnostic codes. The computable phenotype was validated against a subset of clinical notes. RESULTS: Among the 15+ million patients from OneFlorida, we identified 61,313 patients with confirmed HIV diagnosis. Among them, 8.05% met all four inclusion criteria, 69.7% met the 3+ HIV encounters criteria in addition to having HIV diagnostic code, and 8.1% met all criteria except for having positive laboratories. Our algorithm achieved higher sensitivity (98.9%) and comparable specificity (97.6%) relative to existing algorithms (77-83% sensitivity, 86-100% specificity). The mean age of the sample was 42.7 years, 58% male, and about half were Black African American. Patients' average follow-up period (the time between the first and last encounter in the EHRs) was approximately 4.6 years. The median number of all encounters and HIV-related encounters were 79 and 21, respectively. CONCLUSION: By leveraging EHR data from multiple clinical partners and domains, with a considerably diverse population, our algorithm allows more flexible criteria for identifying patients with incomplete laboratory test results and medication prescribing history compared with prior studies.