1. Jessica Haberer, MD, MS July 24, 2017
mHealth Tools for Antiretroviral HIV Prevention and Treatment Medication Monitoring
Jessica Haberer, MD, MS
July 24, 2017

2. Funding I have no conflicts to declare
Grant funding through NIH, Gates Foundation, USAID
Consulting with Merck and the WHO
Stock in Natera
No financial interests in adherence monitoring technologies

3. Outline Why adherence is important for ART and PrEP
Electronic adherence monitors
Cell phone-based monitoring
Ingestion event monitors
Conclusions and recommendations

4. ART adherence and viral rebound
Antiretroviral therapy adherence is closely linked to viral suppression and treatment efficacy
Risk of viral rebound increases by ~25% per day and is >5% after days (NNRTI and PI regimens)
(Haberer et al, AIDS, 2015)

5. PrEP adherence and HIV incidence
Pearson correlation = 0.88, p<0.001
Red = Oral PrEP
Green = Topical PrEP
Note: Diameter of circles is proportional to number of HIV infections in the control group.
(slide used with permission from Jared Baeten)

6. Electronic adherence monitors

7. Electronic adherence monitor data
MEMS in use >25 years in >500 studies
Real-time devices in use ~10 years with >40 studies
(Permission given for photo)

8. Electronic adherence monitors
Pros
Cons
Ability to monitor between visits
May be paired with real-time interventions
Day-to-day data may enhance counseling
May be seen as extension of support
Requires adherence to adherence monitor
Susceptible to misclassification (pocket dosing, curiosity opening)
Potential for stigma
Real-time monitoring of technical function
(Cost)

9. Real-time monitoring may increase adherence
Sustained 11% increase
(Haberer et al, AIDS, 2017)

10. Cell phone-based monitoring

11. SMS surveys for self-reported adherence and associated behaviors
Partners Mobile Adherence to PrEP
(Haberer et al, IAPAC, 2016)

12. Sex with HIV-infected partner (N=5,342 surveys from
342 participants)
<6 months partner ART use (N=4,717 surveys [88%] from
333 participants)
HIV risk
(N=1,130 surveys [21%] from 194 participants)
PrEP adherence = 85% (SD 28)
<100% condom use (N=1,305 surveys [24%] from 201 participants)

13. 99DOTS for self-reported dosing

14. 99DOTS toll-free phone number

15. 99DOTS toll-free phone number
Combination of Caller ID and numbers called shows that doses are in patient’s hands.

16. Wirelessly observed therapy (WOT)
Pilots show feasibility and acceptability in high and low-income settings (Garfein et al, IJTLD, 2015; Hoffman et al, Am J Prev Med, 2010)
AI Cure

17. Cell phone-based monitoring
Pros
Cons
Cell phone usage very common
Convenient data collection in between visits
Frequent data collection may reduce recall bias
Relative anonymity may reduce social desirability bias
Ability to collect associated behaviors and circumstances
Requires action by ART/PrEP user
May be limited by literacy or numeracy
May still be susceptible to social desirability bias
(Cost)

18. Ingestion-event monitors
Feasibility study showed 95% sensitivity, 99.7% specificity (Belknap et al, PLoS One 2013)

19. Ingestion-event monitors
Pros
Cons
Objective assessment of ingestion
Ability to monitor between visits
May be paired with real-time interventions
Day-to-day data may enhance counseling
Requires adherence to adherence monitoring system
Acceptability may be a factor
Potential for stigma
Real-time monitoring of technical function
Cost

20. Conclusions and recommendations
mHealth includes both subjective and objective measures
mHealth tools offer multiple options for:
Obtaining adherence data in between visits (if real-time)
Generating day-to-day data for more informed intervention
Choice of mHealth tool depends on:
Resources
Setting
Goals

21. Measurement methods
A comparison of adherence assessment measures according to their degree of objectivity and ease of implementation in resource-limited settings
Evaluative Criteria
More objective/less objective:
Bias or potential bias in adherence measurement
More resource intensive/harder to implement:
Affordability
Patient burden
Cultural appropriateness
Technology/infrastructure fit
Ingestible
Sensors 99
DOTS
A-I
Cure
Lab Monitoring
More Objective
Electronic Dose
Monitoring
Plasma
Video
Observation
Urine
Saliva
Hair
Unscheduled Pill Count
Scheduled
Pill Count
Interviews
Questionnaires
Diaries
Qualitative Research
Methods
Medication
Supply
Monitoring
Less Objective
Self
Report
Sparse
Sampling
Rich
Sampling
Less Resource Intensive/
Easier to Implement
More Resource Intensive/
Harder to Implement
(courtesy of Bruce Thomas, Arcady Group & BMGF)