Skip to main content
SpringerLink
Log in

Actionable Adherence Monitoring: Technological Methods to Monitor and Support Adherence to Antiretroviral Therapy

  • HIV and Technology (J Simoni and K Ronen, Section Editor)
  • Published:
Current HIV/AIDS Reports Aims and scope Submit manuscript

Abstract

Purpose of Review

Current digital technologies are being used for “actionable adherence monitoring”; that is, technologies that can be used to identify episodes of non-adherence to ART in a timely manner such that tailored interventions based on adherence data can be provided when and where they are needed most.

Recent Findings

Current digital communication technologies used to monitor ART adherence include electronic adherence monitors (EAMs), digital ingestion monitors, cellular phones, and electronic pharmacy refill tracking systems.

Summary

Currently available real-time adherence monitoring approaches based on cellular technology allow for the delivery of interventions precisely when and where they are needed. Such technology can potentially enable significant efficiency of care delivery and impact on adherence and associated clinical outcomes. Standard digital advances, such as automated reminders in EAM and electronic pharmacy records, may also achieve improvements with relatively lower cost and easier implementation. Future research is needed to improve the functionality of these approaches, with attention paid to system-level issues through implementation science, as well as acceptability and ethical considerations at the individual level.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

  1. UNAIDS. Fact sheet - Latest statistics on the status of the AIDS epidemic. 2017 [cited 2018 Feb ]; Available from: http://www.unaids.org/sites/default/files/media_asset/UNAIDS_FactSheet_en.pdf

  2. UNAIDS. 90–90-90: An ambitious treatment target to help end the AIDS epidemic. Geneva, Switzerland: The Joint United Nations Programme on HIV/AIDS; 2014.

    Google Scholar 

  3. Volberding PA, Deeks SG. Antiretroviral therapy and management of HIV infection. Lancet. 2010;376(9734):49–62.

    Article  Google Scholar 

  4. Cohen MS, Chen YQ, McCauley M, Gamble T, Hosseinipour MC, Kumarasamy N, et al. Prevention of HIV-1 infection with early antiretroviral therapy. N Engl J Med. 2011;365(6):493–505.

    Article  CAS  Google Scholar 

  5. • Haberer JE, Musinguzi N, Boum Y II, Siedner MJ, Mocello AR, Hunt PW, et al. Duration of antiretroviral therapy adherence interruption is associated with risk of virologic rebound as determined by real-time adherence monitoring in rural Uganda. J Acquir Immune Defic Syndr. 2015;70(4):386–92. This article is the first demonstration of HIV RNA rebound during adherence interruptions objectively measured in real time.

    Article  CAS  Google Scholar 

  6. Arnsten JH, Demas PA, Farzadegan H, Grant RW, Gourevitch MN, Chang CJ, et al. Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring. Clin Infect Dis. 2001;33(8):1417–23.

    Article  CAS  Google Scholar 

  7. Info, A, Guidelines for the use of antiretroviral agents in adults and adolescents living with HIV. 2017.

  8. Bangsberg DR, Haberer JE. Lifetime HIV antiretroviral therapy adherence intervention: timing is everything: comment on “managed problem solving for antiretroviral therapy adherence”. JAMA Intern Med. 2013;173(4):306–7.

    Article  Google Scholar 

  9. Simoni JM, Kurth AE, Pearson CR, Pantalone DW, Merrill JO, Frick PA. Self-report measures of antiretroviral therapy adherence: a review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–45.

    Article  Google Scholar 

  10. Chaiyachati KH, Ogbuoji O, Price M, Suthar AB, Negussie EK, Bärnighausen T. Interventions to improve adherence to antiretroviral therapy: a rapid systematic review. AIDS. 2014;28(Suppl 2):S187–204.

    Article  Google Scholar 

  11. Haberer JE. Actionable adherence monitoring to optimise intervention. Lancet HIV. 2017;4(1):e5–6.

    Article  Google Scholar 

  12. Vrijens B, de Geest S, Hughes DA, Przemyslaw K, Demonceau J, Ruppar T, et al. A new taxonomy for describing and defining adherence to medications. Br J Clin Pharmacol. 2012;73(5):691–705.

    Article  Google Scholar 

  13. • Gallagher B, Munter P, Moise N, Lin JJ, Kronish IM. Are two commonly used self-report questionnaires useful for identifying antihypertensive medication nonadherence? J Hypertens. 2015;33:1108–13. Other tools, including electronic measurement, may be needed to guide titration of antihypertensive medications among patients with uncontrolled hypertension.

    Article  CAS  Google Scholar 

  14. Genberg BL, Wilson IB, Bangsberg DR, Arnsten J, Goggin K, Remien RH, et al. Patterns of antiretroviral therapy adherence and impact on HIV RNA among patients in North America. AIDS. 2012;26(11):1415–23.

    Article  CAS  Google Scholar 

  15. Demonceau J, et al. Identification and assessment of adherence-enhancing interventions in studies assessing medication adherence through electronically compiled drug dosing histories: a systematic literature review and meta-analysis. Drugs. 2013;73(6):545–62.

    Article  CAS  Google Scholar 

  16. Vrijens B, Urquhart J, White D. Electronically monitored dosing histories can be used to develop a medication-taking habit and manage patient adherence. Expert Rev Clin Pharmacol. 2014;7(5):633–44.

    Article  CAS  Google Scholar 

  17. TB Adherence: Development & Deployment of Intervention Technologies. [cited 2018 Feb 14]; Available from: http://thearcadygroup.com/illustrative-engagements/tb-adherence-development-deployment-of-intervention-technologies/.

  18. The World Bank. Mobile cellular subscriptions (per 100 people). [cited 2017; Available from: https://data.worldbank.org/indicator/IT.CEL.SETS.P2.

  19. • Jongbloed K, Parmar S, van der Kop M, Spittal PM, Lester RT. Recent evidence for emerging digital technologies to support global HIV engagement in care. Curr HIV/AIDS Rep. 2015;12(4):451–61. Technologies for health provide emerging and proven solutions to support achievement of the United Nations targets for the generalized HIV-affected population.

    Article  Google Scholar 

  20. • Van der Elst EM, et al. High acceptability of HIV pre-exposure prophylaxis but challenges in adherence and use: qualitative insights from a phase I trial of intermittent and daily PrEP in at-risk populations in Kenya. AIDS Behav. 2013;17(6):2162–72. Analyses identified three themes: (i) acceptability of PrEP was high, i.e. side effects were experienced early in the study but diminished over time, however characteristics of pills could improve comfort and use; (ii) social impacts such as stigma, rumors, and relationship difficulties due to being perceived as HIV positive were prevalent; (iii) adherence was challenged by complexities of daily life, in particular post-coital dosing adherence suffered from alcohol use around time of sex, mobile populations, and transactional sex work.

    Article  Google Scholar 

  21. de Sumari-de Boer IM, van den Boogaard J, Ngowi KM, Semvua HH, Kiwango KW, Aarnoutse RE, et al. Feasibility of real time medication monitoring among HIV infected and TB patients in a resource-limited setting. AIDS Behav. 2016;20(5):1097–107.

    Article  Google Scholar 

  22. • Sabin L, et al. Improving adherence to antiretroviral therapy with triggered real-time text message reminders: the China Adherence Through Technology Study. J Acquir Immune Defic Syndr. 2015;69(5):551–9. Real-time reminders significantly improved ART adherence in some populations.

    Article  Google Scholar 

  23. • Evans D, Berhanu R, Moyo F, Nguweneza A, Long L, Fox MP. Can short-term use of electronic patient adherence monitoring devices improve adherence in patients failing second-line antiretroviral therapy? Evidence from a pilot study in Johannesburg. South Africa AIDS Behav. 2016;20(11):2717–28. In patients with an elevated viral load on second-line ART electronic adherence monitoring was associated with a modest, but not significant, improvement in viral suppression.

    Article  Google Scholar 

  24. • Atukunda EC, Musiimenta A, Musinguzi N, Wyatt MA, Ashaba J, Ware NC, et al. Understanding patterns of social support and their relationship to an ART adherence intervention among adults in rural southwestern Uganda. AIDS Behav. 2017;21(2):428–40. Effective social support appeared subject to social supporters' food security, economic stability and a well-functioning social network dependent on trust and supportive disclosure.

    Article  Google Scholar 

  25. Haberer JE, Kiwanuka J, Nansera D, Ragland K, Mellins C, Bangsberg DR. Multiple measures reveal antiretroviral adherence successes and challenges in HIV-infected Ugandan children. PLoS One. 2012;7(5):e36737.

    Article  CAS  Google Scholar 

  26. Haberer, J., Does the monitoring of medication packaging tell us what we need to know about TB treatment adherence. 2017, UNION.

  27. • Mbuagbaw L, van der Kop ML, Lester RT, Thirumurthy H, Pop-Eleches C, Ye C, et al. Mobile phone text messages for improving adherence to antiretroviral therapy (ART): an individual patient data meta-analysis of randomised trials. BMJ Open. 2013;3(12):e003950. Text messaging has a significant effect on adherence to ART, and this effect is influenced by level of education, gender, timing (weekly vs daily) and interactivity. We recommend the use of interactive weekly text messaging to improve adherence to ART, which is most effective in those with at least a primary level of education.

    Article  Google Scholar 

  28. • Orrell C, Cohen K, Mauff K, Bangsberg DR, Maartens G, Wood R. A randomized controlled trial of real-time electronic adherence monitoring with text message dosing reminders in people starting first-line antiretroviral therapy. J Acquir Immune Defic Syndr. 2015;70(5):495–502. Text message reminders linked to late doses detected by real-time adherence monitoring reduced the number of prolonged TIs, but did not significantly improve adherence or viral suppression.

    Article  Google Scholar 

  29. • Haberer J, et al. Real-time electronic adherence monitoring plus follow-up improves adherence compared with standard electronic adherence monitoring. AIDS. 2017;31:169–71. Real-time EAM is a promising approach for improving adherence.

    Article  Google Scholar 

  30. • Liu, X., et al., Usability of a Medication Event Reminder Monitor System (MERM) by Providers and Patients to Improve Adherence in the Management of Tuberculosis. Int J Environ Res Public Health. 2017;14(10). Electronic monitoring is becoming the standard of care for drug-susceptible TB patients in China and scaled implementations in several other countries with high TB burden have begun.

    Article  Google Scholar 

  31. • Hafezi H, Robertson TL, Moon GD, Au-Yeung KY, Zdeblick MJ, Savage GM. An ingestible sensor for measuring medication adherence. IEEE Trans Biomed Eng. 2015;62(1):99–109. Aggregate results from multiple clinical trials involving 412 patients and 5656 days of system usage are presented to demonstrate the device's reliability and performance as part of an overall digital health feedback system.

    Article  Google Scholar 

  32. Belknap R, Weis S, Brookens A, Au-Yeung KY, Moon G, DiCarlo L, et al. Feasibility of an ingestible sensor-based system for monitoring adherence to tuberculosis therapy. PLoS One. 2013;8(1):e53373.

    Article  CAS  Google Scholar 

  33. Kane JM. Improving patient outcomes in schizophrenia: achieving remission, preventing relapse, and measuring success. J Clin Psychiatry. 2013;74(9):e18.

    Article  Google Scholar 

  34. • Browne SH, Behzadi Y, Littlewort G. Let visuals tell the story: medication adherence in patients with type II diabetes captured by a novel ingestion sensor platform. JMIR Mhealth Uhealth. 2015;3(4):e108. Visualizations integrating medication ingestion and physiological data from the DHFS over varying time intervals captured detailed individual longitudinal patterns of medication adherence and self-management in the natural setting.

    Article  Google Scholar 

  35. Center PR Cell phones in Africa: communication lifeline. 2015; Available from: http://www.pewglobal.org/2015/04/15/cell-phones-in-africa-communication-lifeline/.

  36. Encyclopedia of Behavioral Medicine. 2013, New York: Springer Science+Business Media.

  37. • DiCarlo LA, Weinstein RL, Morimoto CB, Savage GM, Moon GL, Au-Yeung K, et al. Patient-centered home care using digital medicine and telemetric data for hypertension: feasibility and acceptability of objective ambulatory assessment. J Clin Hypertens (Greenwich). 2016;18(9):901–6. Ambulatory evaluation of medication adherence and habits of daily living appear to be feasible and acceptable using DM and passive acquisition of telemetric data.

    Article  CAS  Google Scholar 

  38. Belluck, P. First digital pill approved to worries about biomedical ‘big brother’. New York Times, 2017.

  39. First Medical Device Cleared by FDA With Adherence Claim. 2015 Feb 2018]; Available from: https://www.proteus.com/press-releases/first-medical-device-cleared-by-fda-with-adherence-claim/.

  40. Swendeman D, Jana S, Ray P, Mindry D, Das M, Bhakta B. Development and pilot testing of daily interactive voice response (IVR) calls to support antiretroviral adherence in India: a mixed-methods pilot study. AIDS Behav. 2015;19(Suppl 2):142–55.

    Article  Google Scholar 

  41. Ramanathan N, Swendeman D, Comulada WS, Estrin D, Rotheram-Borus MJ. Identifying preferences for mobile health applications for self-monitoring and self-management: focus group findings from HIV-positive persons and young mothers. Int J Med Inform. 2013;82(4):e38–46.

    Article  Google Scholar 

  42. Swendeman D, Ramanathan N, Baetscher L, Medich M, Scheffler A, Comulada WS, et al. Smartphone self-monitoring to support self-management among people living with HIV: perceived benefits and theory of change from a mixed-methods randomized pilot study. J Acquir Immune Defic Syndr. 2015;69(Suppl 1):S80–91.

    Article  Google Scholar 

  43. Haberer JE, Kiwanuka J, Nansera D, Muzoora C, Hunt PW, So J, et al. Realtime adherence monitoring of antiretroviral therapy among HIV-infected adults and children in rural Uganda. AIDS. 2013;27(13):2166–8.

    Article  Google Scholar 

  44. Curran K, Mugo NR, Kurth A, Ngure K, Heffron R, Donnell D, et al. Daily short message service surveys to measure sexual behavior and pre-exposure prophylaxis use among Kenyan men and women. AIDS Behav. 2013;17(9):2977–85.

    Article  Google Scholar 

  45. Olds PK, Kiwanuka JP, Ware NC, Tsai AC, Haberer JE. Explaining antiretroviral therapy adherence success among HIV-infected children in rural Uganda: a qualitative study. AIDS Behav. 2015;19(4):584–93.

    Article  Google Scholar 

  46. Kenneth Ngure, J.H., J Baeten, R Heffron, E Katabira, N Mugo, B Burns, B Nankya, G Kimemia, T Muwonge, “It was easy”: a qualitative analysis of participant experiences responding to short message service (SMS) surveys on pre-exposure prophylaxis (PrEP) adherence and sexual behavior in East Africa. , in 11th International Conference on HIV Treatment and Prevention Adherence. 2016: Ft. Lauderdale, FL.

  47. Ngwatu BK, et al., The impact of digital health technologies on tuberculosis treatment: a systematic review. Eur Respir J, 2018;51(1).

    Article  Google Scholar 

  48. Sangeda RZ, Mosha F, Prosperi M, Aboud S, Vercauteren J, Camacho RJ, et al. Pharmacy refill adherence outperforms self-reported methods in predicting HIV therapy outcome in resource-limited settings. BMC Public Health. 2014;14:1035.

    Article  Google Scholar 

  49. Puttkammer N, Zeliadt S, Balan JG, Baseman J, Destiné R, Domerçant JW, et al. Development of an electronic medical record based alert for risk of HIV treatment failure in a low-resource setting. PLoS One. 2014;9(11):e112261.

    Article  Google Scholar 

  50. • Haberer J, et al., Improving antiretorivral therapy adherence in resource-limited settings at scale: a discussion of interventions and recommendations. J Int AIDS Soc. 2017;20(21371). The evidence base is promising for currently available, effective, and scalable ART adherence interventions for resource-limited settings.

  51. Haberer JE, Robbins GK, Ybarra M, Monk A, Ragland K, Weiser SD, et al. Real-time electronic adherence monitoring is feasible, comparable to unannounced pill counts, and acceptable. AIDS Behav. 2012;16(2):375–82.

    Article  Google Scholar 

  52. Hill S, Kavookjian J. Motivational interviewing as a behavioral intervention to increase HAART adherence in patients who are HIV-positive: a systematic review of the literature. AIDS Care. 2012;24(5):583–92.

    Article  Google Scholar 

  53. Liu X, Lewis JJ, Zhang H, Lu W, Zhang S, Zheng G, et al. Effectiveness of electronic reminders to improve medication adherence in tuberculosis patients: a cluster-randomised trial. PLoS Med. 2015;12(9):e1001876.

    Article  Google Scholar 

  54. • Ware NC, Pisarski EE, Tam M, Wyatt MA, Atukunda E, Musiimenta A, et al. The meanings in the messages: how SMS reminders and real-time adherence monitoring improve antiretroviral therapy adherence in rural Uganda. AIDS. 2016;30(8):1287–94. Although serving as reminders, SMS messages and real-time adherence monitoring also had larger emotional and moral meanings for participants that they felt improved their adherence.

    Article  CAS  Google Scholar 

  55. Mayo, E. Social problems for an industrial civilization. 1945. 2018].

  56. Finitsis DJ, Pellowski JA, Johnson BT. Text message intervention designs to promote adherence to antiretroviral therapy (ART): a meta-analysis of randomized controlled trials. PLoS One. 2014;9(2):e88166.

    Article  Google Scholar 

  57. • Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A, et al. Mobile telephone text messaging for medication adherence in chronic disease: a meta-analysis. JAMA Intern Med. 2016;176(3):340–9. Mobile phone text messaging approximately doubles the odds of medication adherence.

    Article  Google Scholar 

  58. Kalichman SC, Amaral CM, Stearns H, White D, Flanagan J, Pope H, et al. Adherence to antiretroviral therapy assessed by unannounced pill counts conducted by telephone. J Gen Intern Med. 2007;22(7):1003–6.

    Article  Google Scholar 

  59. Williams AB, Amico KR, Bova C, Womack JA. A proposal for quality standards for measuring medication adherence in research. AIDS Behav. 2013;17(1):284–97.

    Article  Google Scholar 

  60. Haberer JE, Ngure K, Muwonge T, Mugo N, Katabira E, Heffron R, et al. Brief report: context matters: PrEP adherence is associated with sexual behavior among HIV serodiscordant couples in East Africa. J Acquir Immune Defic Syndr. 2017;76(5):488–92.

    Article  Google Scholar 

  61. • Himelhoch S, Kreyenbuhl J, Palmer-Bacon J, Chu M, Brown C, Potts W. Pilot feasibility study of Heart2HAART: a smartphone application to assist with adherence among substance users living with HIV. AIDS Care. 2017;29(7):898–904. Heart2HAART was feasible to use during a three-month pilot trial. Future studies may evaluate a more tailored approach, with more robust contingency management.

    Article  Google Scholar 

  62. WHO, Meeting Report on Assessment of World Health Organization HIV Drug Resistance Early Warning Indicators: Report of the Early Warning Indicator Advisory Panel Meeting. 2011, World Health Organization: Geneva, Switzerland.

  63. Orrell C, Dipenaar R, Killa N, Tassie JM, Harries AD, Wood R. Simplifying HIV cohort monitoring—pharmacy stock records minimize resources necessary to determine retention in care. JAIDS J Acquir Immune Defic Syndr. 2013;62(3):e106–8.

    Article  Google Scholar 

  64. Douglas GP, et al., Using touchscreen electronic medical record systems to support and monitor national scale-up of antiretroviral therapy in Malawi. PLoS Med. 2010;7(8).

    Article  Google Scholar 

  65. Tweya H, Feldacker C, Ben-Smith A, Harries AD, Komatsu R, Jahn A, et al. Simplifying ART cohort monitoring: can pharmacy stocks provide accurate estimates of patients retained on antiretroviral therapy in Malawi? BMC Health Serv Res. 2012;12:210.

    Article  Google Scholar 

  66. New Toolkit for Differentiated Care in HIV and TB Programs. Nov 2015 [cited 2018 Feb 14]; Available from: https://www.theglobalfund.org/media/2569/core_differentiatedcare_toolkit_en.pdf?u=636486807130000000.

  67. Barth RE, van der Loeff MFS, Schuurman R, Hoepelman AIM, Wensing AMJ. Virological follow-up of adult patients in antiretroviral treatment programmes in sub-Saharan Africa: a systematic review. Lancet Infect Dis. 2010;10(3):155–66.

    Article  CAS  Google Scholar 

  68. • Campbell JI, et al. Ethical questions in medical electronic adherence monitoring. J Gen Intern Med. 2016;31(3):338–42. The unique benefits as well as the potential ethical challenges that electronic adherence monitoring generates. These challenges surround autonomy, privacy and confidentiality, trust, and ancillary care obligations.

    Article  Google Scholar 

  69. • Richardson HS, Eyal N, Campbell JI, Haberer JE. When ancillary care clashes with study aims. N Engl J Med. 2017;377(13):1213–5. Providing ancillary care is sometimes obligatory in medical and health care studies. Its provision may, however, collide with achievement of a study’s aims.

    Article  Google Scholar 

  70. • Chai PR, Carreiro S, Innes BJ, Rosen RK, O'Cleirigh C, Mayer KH, et al. Digital pills to measure opioid ingestion patterns in emergency department patients with acute fracture pain: a pilot study. J Med Internet Res. 2017;19(1):e19. Deploying digital pills is possible through the ED with a short instructional course. Patients who used the digital pill accepted the technology.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Center for Global Health, Massachusetts General Hospital, 125 Nashua St, Suite 722, Boston, MA, 02114, USA

    Kate M. Bell & Jessica E. Haberer

  2. Harvard Medical School, Boston, MA, USA

    Jessica E. Haberer

Authors
  1. Kate M. Bell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jessica E. Haberer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jessica E. Haberer.

Ethics declarations

Conflict of Interest

Kate M. Bell declares no conflict of interest.

Jessica E. Haberer receives support from the United States National Institutes of Health (NIMH; K24MH114732), has received grant funding from NIH (R01MH109309, R01MH098744, R34MH100940, R21AI108329), and has received grant and travel support from the Bill and Melinda Gates Foundation (OPP113634, OPP1056051).

Human and Animal Rights and Informed Consent

This article does not contain any studies with human or animal subjects performed by any of the authors.

Additional information

This article is part of the Topical Collection on HIV and Technology

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bell, K.M., Haberer, J.E. Actionable Adherence Monitoring: Technological Methods to Monitor and Support Adherence to Antiretroviral Therapy. Curr HIV/AIDS Rep 15, 388–396 (2018). https://doi.org/10.1007/s11904-018-0413-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11904-018-0413-0

Keywords

Search

Navigation