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Using Routine Data to Improve ART Retention: Examples and Lessons Learned from the Literature and Experts in the Field


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Webinar discussion led by Nena do Nascimento, Cathy Barker, and Michelle Li

Published in: Health & Medicine
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Using Routine Data to Improve ART Retention: Examples and Lessons Learned from the Literature and Experts in the Field

  1. 1. Using Routine Data to Improve ART Retention: Examples and Lessons Learned from the Literature and Experts in the Field Photo credits: Left: CDC,; Center: Riccardo Lennart Niels Mayer, iStock Photo, 2015; Right: Paul Jeffrey March 30, 2017 MEASURE Evaluation Webinar Nena do Nascimento, MPP Michelle Li, MS Catherine Barker, MPH
  2. 2. Investigate how countries are currently using routine health facility records to improve adult antiretroviral treatment(ART)* retention in low- and middle- income countries and recommend how to strengthen data use for higher ART retention. * male and female, excluding PMTCT & pre-ART Activity Purpose
  3. 3.  As countries work towards an AIDS-free generation, they must be able to use their routine health data to retain patients in the continuum of HIV care by effectively tracking clients and ensuring that they follow their treatment regimen. Retention:  Proxy for adherence or programming effectiveness (Geng et al., 2010)  Access to support services to ensure continuous treatment and reduce risk to others (Messeri et al., 2002) Retention and 90-90-90 UNAIDS’ ambitious treatment target to help end the AIDS epidemic
  4. 4. Facility (pharmacy & clinic) Use data to inform care needs for patients & ensure optimal treatment Community Trace patients, provide support services, refer patients to health facility National and sub- national level Identify retention performance and trends & policies to improve retention Aggregate data and send to subnational and national level on retention Send results of patient tracing; refer patients for relevant services Share reports on retention at subnational and national level Provide data on defaulted patients in need of follow- up or patients in need of additional support services Routine Health Data & Retention
  5. 5. Systematic review  Close to 5,000 publications reviewed, including national guidance  Peer reviewed, grey literature, relevant websites  Question: “How have low- and middle-income countries routinely collected patient-level data to retain adults on Online survey  Purpose: to fill gaps in the literature  62 practitioners completed a 16-question survey In-depth interviews  Purpose: deepen understanding of practitioners’  Seven interviews with monitoring and evaluation experts one MOH official from a PEPFAR country Methods
  6. 6. Survey Respondents
  7. 7. Interventions that Support Use of Data for ART Retention
  8. 8. Improved Data Capture Systems
  9. 9. Data Review Meetings
  10. 10. Patient Tracing
  11. 11. Interventions that Support Use of Data for ART Retention  Interventions determined by:  Patient load  Type of the epidemic  Health information system design  Available technology and connectivity  Human resource capacity
  12. 12. Smart Care – Zambia Tickler File – Ethiopia Photo credits: Left Right: Tariq Azam Interventions that Support Use of Data for ART Retention
  13. 13. Opinions on Interventions “The use of the data have increased retention of patients on ART as they guide the program to make informed decisions. [Interventions include] early tracking of missed appointments, and set time blocks for patients to reduce the long waiting hours at counseling and testing clinics.” - Survey respondent with experience in Tanzania “The cohort reports specifically has enabled facilities to analyze attrition rates and the reasons contributing to that. This has enabled the facilities to focus their efforts on the gaps as part of their continuous quality improvement.” - Survey respondent with experience in Haiti, Kenya, Nigeria, Rwanda, Uganda, and Zambia Only1survey respondent of 57 indicated that use of routine health facility records did not lead to increased retention
  14. 14.  Data quality  Data use culture  Human resources  Parallel systems  Linking community and facility data  Sustainability Challenges
  15. 15. 1. Patient tracing to improve ART retention most commonly cited — less emphasis on data review meetings and improving data capture systems 2. Approaches should be fit-for-purpose 3. Human resources are a key to improved ART retention 4. Community programming is integral Conclusions
  16. 16. 1. More emphasis should be placed on data use as part of retention interventions at the community and facility level. 2. Supportive supervision, mentoring, and training of health facility workers on data collection and data use would strengthen data quality and use of data to improve retention. 3. Strengthen and invest in community programming and community information systems — and strengthen their linkages to facility systems. The use of unique patient identifiers and mobile technology could improve linkages and enable more accurate measurement. 4. Reduce multiple vertical reporting mechanisms to reduce workload of health facility workers and better use data Recommendations
  17. 17.  Retention within the context of multi- month scripts, differentiated care  Role of the community in tracking retention and adherence through community adherence groups and other structures What’s Next?
  18. 18. Poll & Questions
  19. 19. For more information… Email:
  20. 20. 20 References 1. Fox MP, Rosen S. Patient retention in antiretroviral therapy programs up to three years on treatment in sub‐Saharan Africa, 2007–2009: systematic review. Tropical Medicine & International Health. 2010;15(s1):1-15. 2. WHO. Retention in HIV Programmes: Defining the challenges and identifying solutions. Meeting report, 13-15 September 2011, Geneva. 3. PEPFAR. FY 2015 Results - Tanzania. Available at: 4. Hotchkiss DR, Diana ML, Foreit KG. How can routine health information systems improve health systems functioning in low-and middle-income countries? Assessing the evidence base. Adv Health Care Manag. 2012;12:25-58. 5. Mugavero MJ, Westfall AO, Zinski A, Davila K, Drainoni, ML, Gardner, L et al. Measuring retention in HIV care: the elusive gold standard. Journal of acquired immune deficiency syndromes (1999). 2012;61(5):574. 6. Massaquoi M, Zachariah R, Manzi M, et al. Patient retention and attrition on antiretroviral treatment at district level in rural Malawi. Trans R Soc Trop Med Hyg. 2009;103:594–600. 7. 8. Tierney, William M., et al. "Assessing the impact of a primary care electronic medical record system in three Kenyan rural health centers." Journal of the American Medical Informatics Association (2015): ocv074. 9. DHIS 2.20 Overview. Available at: 10. REDCap Project lead by Project Hope in Namibia. 11. do Nascimento N, de Jesus Joao F. Formative Assessment of a Future mHealth Site in Nhamatanda, Mozambique. MEASURE Evaluation: Working Paper Series. 2013. 12. Wandina D, Odhiambo F, Ojoo S, Mongare J, Ogillo G, Muriuki J, et al. Strategies for reducing lost to follow-up rates in adult patients receiving antiretroviral treatment in rural services in Kenya [Poster Presentation]. The 6th International AIDS Society Conference on HIV Pathogenesis, Treatment and Prevention, Rome, Italy, July 2011. 13. South African National Department of Health (SANDOH). Models for the scale up of HIV prevention, treatment and care from South Africa and beyond. 2010. 14. Rosen, S and Ketlhapile, M. Cost of using a patient tracer to reduce loss to follow-up and ascertain patient status in a large antiretroviral therapy program in Johannesburg, South Africa. Tropical Medicine and International Health. 2010; 15 (I); 98-104. 15. Geng EH, Nash D, Kambugu A, et al. Retention in Care Among HIV-Infected Patients in Resource-Limited Settings: Emerging Insights and New Directions. Curr HIV/AIDS Rep. 2010; Nov; 7(4): 234–244. 16. McMahon JH, Moore R, Eu B, et al. Clinic Network Collaboration and Patient Tracing to Maximize Retention in HIV Care. PloS one. 2015;10(5):e0127726. 17. Dalal, R.P., MacPhail, C., Mqhayi, M., Wing, J., Feldman, C., Chersich, M.F., Venter, W.D..(2008). Characteristics and outcomes of adult patients lost to follow-up at an antiretroviral treatment clinic in Johannesburg, South Africa. JAIDS Journal of Acquired Immune Deficiency Syndromes, 47(1), 101-107. 18. Forster, M., Bailey, C., BrinkhofI, M.W.G., Graber, C., Boulle, A., Spohr, M., Balestre, E… Egger, M. (2008). Electronic medical record systems, data quality and loss to follow-up: survey of antiretroviral therapy programmes in resource-limited settings. Bulletin of the World Health Organization, 86 (12). 19. Scheibe, F.J., Waiswa, P., Kadobera, D., Miller, O., Ekström, A.M., Sarker, M., Neuhann, H.W.F.. (2013). Effective Coverage for Antiretroviral Therapy in a Ugandan District with a Decentralized Model of Care. PloS one, 8(7), e69433. 20. Ministry of Health and Ministry of Community Development, Mother and Child Health. Zambia Consolidated Guidelines for Treatment and Prevention of HIV Infection. (2014, Feb). 21. National AIDS & STI Control Program. Guidelines on Use of Antiretroviral Drugs for Treating and Preventing HIV Infection in Kenya (2016 ed.). 22. Republica de Mocambique, Ministerio da Saude, Direccao National de Assistencia Medica. (2014). Guia de Tratamento antiretroviral e infeccoes oportunistas no adulto, adolescente, gravida e crianca 2014. 23. South African National AIDS Council (SANAC). National Strategic Plan for HIV, STIs, and TB. (2012-2016). 2011. 24. The United Republic of Tanzania, Ministry of Health and Social Welfare, National AIDS Control Programme. National Guidelines for the Management of HIV and AIDS (5th ed.). (2015, May).
  21. 21. This presentation was produced with the support of the United States Agency for International Development (USAID) under the terms of MEASURE Evaluation cooperative agreement AID-OAA-L- 14-00004. MEASURE Evaluation is implemented by the Carolina Population Center, University of North Carolina at Chapel Hill in partnership with ICF International; John Snow, Inc.; Management Sciences for Health; Palladium; and Tulane University. Views expressed are not necessarily those of USAID or the United States government.