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AIDS and Behavior

, Volume 23, Supplement 1, pp 70–77 | Cite as

“Closing the Loop” Developing State-Level Data Sharing Interventions to Promote Optimum Outcomes Along the HIV Continuum of Care

  • Sophia Zamudio-HaasEmail author
  • Kimberly A. Koester
  • Andres Maiorana
  • Shannon M. Fuller
  • Wayne T. Steward
  • DeAnn Gruber
  • J. Christian Hauge
  • Heather E. Parnell
  • Evelyn Byrd Quinlivan
  • Janet J. Myers
Original Paper

Abstract

This manuscript describes the experiences of three state departments of health (SDoH) that successfully launched data sharing interventions involving surveillance and/or patient data collected in clinics to improve care outcomes among people living with HIV. We examined 58 key informant interviews, gathered at two time points, to describe the development and implementation of data sharing interventions. We identified three common themes across states’ experiences: creating standard practices, fostering interoperability, and negotiating the policy environment. Projects were successful when state teams adapted to changing circumstances and were committed to a consistent communication process. Once implemented, the interventions streamlined processes to promote linkage and retention in care among low-income populations living with HIV. Despite using routinely collected data, key informants emphasized the labor-intensive process to develop and sustain the interventions. Lessons learned from these three state experiences can help inform best practices for other SDoH that are considering launching similar interventions.

Keywords

HIV care continuum Data sharing interventions Surveillance data Implementation science State surveillance 

Resumen

Este manuscrito describe las experiencias de tres departamentos estatales de salud (SDoH, por su sigla en inglés) que implementaron con éxito intervenciones de intercambio de datos que incluían datos de vigilancia y/o de pacientes recogidos en clínicas para mejorar los resultados médicos para personas que viven con el VIH. Analizamos 58 entrevistas con informantes claves, conducidas en dos etapas, para describir el desarrollo y la implementación de intervenciones de intercambio de datos. Identificamos tres temas comunes en las experiencias de los estados: la creación de prácticas estándar, el fomento de la interoperabilidad y la negociación del entorno de políticas. Los proyectos tuvieron éxito cuando los equipos estatales se adaptaron a circunstancias cambiantes y se comprometieron en un proceso de comunicación constante. Una vez implementadas, las intervenciones racionalizaron los procesos para promover el vínculo y la retención en la atención médica en poblaciones de bajos ingresos que viven con el VIH. A pesar de utilizar datos recopilados rutinariamente, los informantes clave enfatizaron el proceso de trabajo intensivo para desarrollar y sostener las intervenciones. Las lecciones aprendidas de estas tres experiencias estatales pueden ayudar a informar mejores prácticas para otros SDoH que estén considerando iniciar intervenciones similares.

Notes

Acknowledgements

This project was supported by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under Grant Number U90HA22702 for the Systems Linkages and Access to Care for Populations at High Risk for HIV Infection Initiative Evaluation and Technical Assistance Center. This information or content and conclusions are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by HRSA, HHS or the U.S. Government.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures involving human participants were in accordance with the ethical standards for the institutional review board and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study. No personal identifying information is included in the manuscript.

References

  1. 1.
    Cohen MS, Chen YQ, McCauley M, et al. Antiretroviral therapy for the prevention of HIV-1 transmission. N Engl J Med. 2016;375:830–9.CrossRefGoogle Scholar
  2. 2.
    Skarbinski J, Rosenberg E, Paz-Bailey G, et al. Human immunodeficiency virus transmission at each step of the care continuum in the United States. JAMA Intern Med. 2015;175(4):588–96.CrossRefGoogle Scholar
  3. 3.
  4. 4.
    Gardner LI, Metsch LR, Anderson-Mahoney P, Loughlin AM, del Rio C, Strathdee S, Holmberg SD. Efficacy of a brief case management intervention to link recently diagnosed HIV-infected persons to care. AIDS. 2005;19:423–31.CrossRefGoogle Scholar
  5. 5.
    Arnold EA, Totten AM, Kassakian SZ, et al. Identifying social and economic barriers to regular care and treatment for Black men who have sex with men and women (BMSMW) and who are living with HIV: a qualitative study from the Bruthas cohort. BMC Health Serv Res. 2017;17:90.CrossRefGoogle Scholar
  6. 6.
    Friendman MR, Coulter RW, Silvestre AJ, et al. Someone to count on: social support as an effect modifier in viral load suppression in a prospective cohort study. AIDs Care. 2017;29(4):469–80.CrossRefGoogle Scholar
  7. 7.
    Ayala G, Santos GM. Will the global HIV response fail bisexual men and other men who have sex with men? J Intn AIDS Soc. 2016;19(1):21098.CrossRefGoogle Scholar
  8. 8.
    Colasanti J, Stahl N, Farber EW, Del Rio C, Armstrong WS. An exploratory study to assess individual and structural level barriers associated with poor retention and re-engagement in care among persons living with HIV/AIDS. J Acquir Immune Defic Syndr. 2017;1(74 Suppl 2):S113–20.CrossRefGoogle Scholar
  9. 9.
    Keller J, Heine A, LeViere AF, et al. HIV patient retention: the implementation of a North Carolina clinic-based protocol. AIDS Care. 2017;29:627–31.CrossRefGoogle Scholar
  10. 10.
    Bove J, Golden MR, Dhanireddy S, et al. Outcomes of a clinic-based, surveillance-informed intervention to relink patients to HIV care. J Acquir Immune Defic Syndr. 2015;70(3):262–8.CrossRefGoogle Scholar
  11. 11.
    Buchacz K, Chen MJ, Parisi MK, et al. Using HIV surveillance registry data to re-link persons to care: the RSVP project in San Francisco. PLoS ONE. 2015;10:e0118923.CrossRefGoogle Scholar
  12. 12.
    Hague JC, John B, Goldman L, et al. Using HIV surveillance laboratory data to identify out-of-care patients. AIDS Behav. 2017.  https://doi.org/10.1007/s10461-017-1742-5.Google Scholar
  13. 13.
    Herwehe J, Wilbright W, Abrams A, et al. Implementation of an innovative, integrated electronic medical record (EMR) and public health information exchange for HIV/AIDS. J Am Med Inform Assoc. 2012;19:448–52.CrossRefGoogle Scholar
  14. 14.
    Health Resources and Services Administration. SPNS Initiative: Systems Linkages and Access to Care, 2011–2016. https://hab.hrsa.gov/about-ryan-white-hivaids-program/spns-systems-linkages-and-access.
  15. 15.
    Dombrowski JC, Bove J, Roscoe JC, et al. “Out of Care” HIV case investigations: a collaborative analysis across 6 states in the northwest US. J Acquir Immune Defic Syndr. 2017;74:S81–7.CrossRefGoogle Scholar
  16. 16.
    Lubelcheck RJ, Finnegran KJ, Hotton AL, et al. Assessing the use of surveillance data to help gauge patient retention in care. J Acquir Immune Defic Syndr. 2015;69(S1):S25–30.CrossRefGoogle Scholar
  17. 17.
    Enns EA, Reilly CS, Virnig BA, et al. Potential impact of integrating HIV surveillance and clinic data on retention-in-care estimates and re-engagement efforts. AIDS Patient Care STDS. 2016;30:409–15.CrossRefGoogle Scholar
  18. 18.
    Christopoulos KA, Scheer S, Steward WT, et al. Examining clinic-based and public health approaches to ascertainment of HIV care status. J Acquir Immune Defic Syndr. 2015;69:S56–62.CrossRefGoogle Scholar
  19. 19.
    Koester KA, Fuller SM, Maiorana A, et al. Implementing multi-level interventions to improve HIV testing, linkage to and retention in care interventions. J Health Care Poor Underserv. 2016;27(3):1234–51.CrossRefGoogle Scholar
  20. 20.
    Ritchie J, Spencer L. Qualitative data analysis for applied policy research. In: Bryman A, Burgess RG, editors. Analyzing Qualitative Data. London: Routledge; 1993.Google Scholar
  21. 21.
  22. 22.
    Seña AC, Donovan J, Swygard H, et al. The North Carolina HIV Bridge Counselor Program: outcomes from a statewide level intervention to link and reengage HIV-infected persons in care in the South. J Acquir Immune Defic Syndr. 2017;76(1):e7–14.  https://doi.org/10.1097/QAI.0000000000001389.CrossRefGoogle Scholar
  23. 23.
    Maiorana A, Steward WT, Koester KA, et al. Trust, confidentiality, and the acceptability of sharing HIV-related patient data: lessons learned from a mixed methods study about Health Information Exchanges. Implement Sci. 2012;7:34.CrossRefGoogle Scholar
  24. 24.
    Evans D, Gorder DV, Morin SF, et al. Acceptance of the use of HIV surveillance data for care engagement: national and local community perspectives. J Acquir Immune Defic Syndr. 2015;69(S1):S31–6.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Sophia Zamudio-Haas
    • 1
    Email author
  • Kimberly A. Koester
    • 1
  • Andres Maiorana
    • 1
  • Shannon M. Fuller
    • 1
  • Wayne T. Steward
    • 1
  • DeAnn Gruber
    • 2
  • J. Christian Hauge
    • 3
  • Heather E. Parnell
    • 4
  • Evelyn Byrd Quinlivan
    • 5
  • Janet J. Myers
    • 1
  1. 1.Division of Prevention Science, Center for AIDS Prevention StudiesUniversity of California, San FranciscoSan FranciscoUSA
  2. 2.Department of Public HealthNew OrleansUSA
  3. 3.Department of Public HealthBostonUSA
  4. 4.Center for Health Policy and Inequalities ResearchDuke UniversityDurhamUSA
  5. 5.Institute for Global Health and Infectious DiseasesUniversity of North Carolina – Chapel HillChapel HillUSA

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