While Medicaid eligibility expansion created health care access for millions in California, its impact on people living with HIV has been more nuanced. Newly covered people living with HIV who have behavioral health care needs now must navigate separate mental health and substance use care systems, instead of receiving them in integrated care settings as they had under the Ryan White HIV/AIDS Program. We conducted forty-seven interviews in the period April 2015-June 2016 to examine the impact of Medicaid expansion on people living with HIV in California who had behavioral health care needs. California's historical division in its Medicaid funding streams created challenges in determining which payer should cover clients' behavioral health care. Compounding these challenges were a perceived lack of cultural competence for serving this population, insufficient infrastructure to facilitate continuity of care, and unmet need for nonmedical supportive services. The multipayer model under health reform has compromised the administrative simplicity and integrated delivery of HIV and behavioral health services previously available to uninsured patients through the Ryan White HIV/AIDS Program.

Background The United States HIV care workforce is shrinking, which could complicate service delivery to people living with HIV (PLWH). In this study, we examined the impact of practice transformations, defined as efficiencies in structures and delivery of care, on demonstration project sites within the Workforce Capacity Building Initiative, a Health Resources and Services Administration (HRSA) Ryan White HIV/AIDS Program Special Projects of National Significance (SPNS). Methods and findings Data were collected at 14 demonstration project sites in 7 states and the District of Columbia. Organizational assessments were completed at sites once before and 4 times after implementation. They captured 3 transformation approaches: maximizing the HIV care workforce (efforts to increase the number of existing healthcare workforce members involved in the care of PLWH), share-the-care (team-based care giving more responsibility to midlevel providers and staff), and enhancing client engagement in primary HIV care to reduce emergency and inpatient care (e.g., care coordination). We also obtained Ryan White HIV/AIDS Program Services Reports (RSRs) from sites for calendar years (CYs) 2014-2016, corresponding to before, during, and after transformation. The RSR include data on client retention in HIV care, prescription of antiretroviral therapy (ART), and viral suppression. We used generalized estimating equation (GEE) models to analyze changes among sites implementing each practice transformation approach. The demonstration projects had a mean of 18.5 prescribing providers (SD = 23.5). They reported data on more than

Background In the United States, patients with HIV face significant barriers to linkage to and retention in care which impede the necessary steps toward achieving the desired clinical outcome of viral suppression. Individual-level interventions, such as patient navigation, are evidence based, effective strategies for improving care engagement. In addition, use of surveillance and clinical data to identify patients who are not fully engaged in care may improve the effectiveness and cost-effectiveness of these programs. Methods and findings We employed a pre-post design to estimate the outcomes and costs, from the program perspective, of 5 state-level demonstration programs funded under the Health Resources and Services Administration’s Special Projects of National Significance Program (HRSA/SPNS) Systems Linkages Initiative that employed existing surveillance and/or clinical data to identify individuals who had never entered HIV care, had fallen out of care, or were at risk of falling out of care and navigation strategies to engage patients in HIV care. Outcomes and costs were measured relative to standard of care during the first year of implementation of the interventions (2013 to 2014). We followed patients to estimate the number and proportion of additional patients linked, reengaged, retained, and virally suppressed by 12 months after enrollment in the interventions. We employed inverse probability weighting to adjust for differences in patient characteristics across programs, missing data, and loss to follow-up. We estimated the additional costs expended during the first year of each intervention and the cost per outcome of each intervention as the additional cost per HIV additional care continuum target achieved (cost per patient linked, reengaged, retained, and virally suppressed) 12 months after enrollment in each intervention. In this study, 3,443 patients were enrolled in Louisiana (LA), Massachusetts (MA), North Carolina (NC), Virginia (VA), and Wisconsin (WI) (147, 151, 2,491, 321, and 333, respectively). Patients were a mean of 40 years old, 75% male, and African American (69%) or Caucasian (22%). At baseline, 24% were newly diagnosed, 2% had never been in HIV care, 45% had fallen out of care, and 29% were at risk of falling out of care. All 5 interventions were associated with increases in the number and proportion of patients with viral suppression [percent increase: LA = 90.9%, 95% confidence interval (CI) = 88.4 to 93.4; MA = 78.1%, 95% CI = 72.4 to 83.8; NC = 47.5%, 95% CI = 45.2 to 49.8; VA = 54.6, 95% CI = 49.4 to 59.9; WI = 58.4, 95% CI = 53.4 to 63.4]. Overall, interventions cost an additional $4,415 (range = $3,746 to $5,619), $2,009 (range = $1,516 to $2,274), $920 (range = $627 to $941), $2,212 (range = $1,789 to $2,683), and $3,700 ($2,734 to $4,101), respectively per additional patient virally suppressed. The results of this study are limited in that we did not have contemporaneous controls for each intervention; thus, we are only able to assess patients against themselves at baseline and not against standard of care during the same time period. Conclusions Patient navigation programs were associated with improvements in engagement of patients in HIV care and viral suppression. Cost per outcome was minimized in states that utilized surveillance data to identify individuals who were out of care and/or those that were able to identify a larger number of patients in need of improvement at baseline. These results have the potential to inform the targeting and design of future navigation-type interventions.