ABSTRACT
To end the HIV/AIDS epidemic, innovative strategies are needed to improve outcomes along the HIV care continuum. Data-to-Care is a public health strategy whereby HIV surveillance data are used to identify people living with HIV/AIDS for linkage to, or re-engagement in HIV medical care. Three main approaches to Data-to-Care are defined by where persons out of care are identified and where outreach activities are initiated: the Health Department level, the Healthcare Provider level, or a combination of the two (Combination Model). The purpose of this evaluation was to compare successes and challenges for two Data-to-Care models implemented in New York State between 1 January 2015 and 1 September 2016: a Health Department Model, and a Combination Model. The Health Department Model identifies persons presumed to be out of care based on an absence of HIV laboratory tests within the states surveillance system alone, and the Combination Model identifies individuals based on both an absence of a medical provider visit at a partnering health center, and an absence of HIV laboratory tests in the surveillance system. Only counties served by partnering health centers were included in this evaluation. In the Health Department Model, 348 out of 1352 (26%) surveillance identified individuals were truly out of care; of those, re-linkage success was 78%. In the Combination Model, 19 out of 51 (37%) individuals were truly out of care; of those, re-linkage success was 63%. The proportion of cases truly out of care was significantly higher for the Combination Model than the Health Department Model (p-value: 0.08). Both models were successful in re-linking a high proportion of individuals back to care, though the efficiency of identifying individuals who are truly out of care remains an area in need of further refinement for both models.
Acknowledgments
A special thank you goes out to our phenomenal HICAPP Linkage Specialists Nessie Tabe, Megan McPhail and Katherine (Herpin) DiBenedetto of the New York State Department of Health, and Edwin Lopez of the New York City Department of Health for their exemplary work in the field. In addition, we would like to thank our partnering health centers: Betances Health Center, Damian Family Care Center, Bedford Stuyvesant Family Health Center, Cornerstone Family Health Center, Community Health Center of Buffalo, and Jordan Health. Furthermore, we would like to thank Megan Johnson, Britney Johnson, Mara Sanantonio-Gaddy, Maryline Alexis-Philippe, the Bureau of HIV/STD Field Services, the Bureau of STD Prevention and Epidemiology of the New York State Department of Health, and the Expanded Partner Services Advocates for their tireless efforts, and for the great impact they have made with respect to Data to Care. Additionally, we would like to thank the New York State Department of Health AIDS Institute Bureau of HIV/AIDS Epidemiology for their expertize in HIV surveillance, and the New York City Department of Health and Mental Hygiene Field Services Unit, especially Chi-Chi Udeagu, for their contribution to the programmatic integrity of this work, and to the current Data to Care programs. Lastly, we would like to thank Tarak Shrestha for his analytic contribution to all Data to Care work in New York State. This analysis was made possible through the support of the Centers for Disease Control and Prevention PS14-1410 Secretary’s Minority AIDS Initiative Funding to Increase HIV Prevention and Care Service Delivery among Health Centers Serving High HIV Prevalence Jurisdictions.
Disclosure statement
No potential conflict of interest was reported by the authors.
ORCID
Rachel Hart-Malloy http://orcid.org/0000-0001-8114-7626