May 15, 2012
Saskatoon HIV AIDS Research Endeavour
(SHARE)
Cell phones for HIV Care and
Health Promotion: What Works
Richard Lester, MD, FRCPC
BCCDC and
University of British Columbia
WelTel.org
Disclosures – support received
Non-corporate
• PEPFAR
• CDC/CDC Foundation
• WHO
• BCCDC Foundation
• IDRC/GHRI
• AMMI/CIHR/BMS
• Gates Foundation
• ICID (UManitoba)
• NIH (NIMH)
Corporate
• Bristol-Myers-Squibb
mHealth: What is it?
 Wikipedia: a term used for the practice
of
medical and public health, supported by mobile
devices.
 NIH: the delivery of healthcare services via mobile
communication devices
 Emerged as a sub-segment of eHealth:
– Using information and communication
technology (ICT) for health services and
information, such as computers, mobile phones,
communications satellite, patient monitors, etc,
for health services and information.
Is it all
CREDIT: http://www.armybase.us/2009/04/air-force-yields-in-f-22-fighter-dispute/
mHealth applications
•
•
•
•
•
•
•
•
•
•
•
•
Emergency response systems (e.g., road traffic accidents, emergency obstetric
care)
Human resources coordination, management, and supervision
Mobile synchronous (voice) and asynchronous (SMS) telemedicine diagnostic and
decision support to remote clinicians
Clinician-focused, evidence-based formulary, database and decision support
information available at the point-of-care
Pharmaceutical Supply Chain Integrity & Patient Safety Systems (e.g. Sproxil and
mPedigree)
Clinical care and remote patient monitoring
Health extension services
Health services monitoring and reporting
Health-related mLearning for the general public
Training and continuing professional development for health care workers
Health promotion and community mobilization
Support of long-term conditions, for example in diabetes self-management
Wikipedia, accessed Jan 30, 2012
HIV-Not Hype?
Problem: People living with HIV
Response: People on ART
People with mobile phones
Kenya: Dual Epidemics
• Kenya Population= 39,002,772
• 7.1% 2007 adult HIV prevalence
•1 physician/2 nurses per 10,000 population
•~16 million mobile phone subscribers
Lester et al. AIDS Vol 20, 17 Nov, 2006
2005
Can cellphones improve HIV care?
WelTel Kenya1: RCT
Exclusion (44)
Inadequate phone access
Refused/Unable
Inclusion
Adults (> 18 years) starting ART
Adequate phone access (owned/shared)
Informed consent
Screening
(581+)
Randomized
(538)
Baseline survey
Pumwani
Coptic
Kajiado
(251)
(209)
(78)
Randomization
SMS
control
SMS
control
SMS
control
(120)
(131)
(117)
(92)
(36)
(42)
6 month
Follow-up
Follow-up
Follow-up
Follow-up
Follow-up
Powered to show 10% improvement in adherence
Follow-up
SMS n=273
Control n=265
12 month
Proportion of weekly SMS responses
WelTel Kenya1: 2-way weekly (SMS) interactive
check-ins.
0.8
0.7
0.6
0.5
0.4
0.3
No response
0.2
Sawa (fine)
(6.1% ‘SHIDA’)
0.1
Shida (problem)
(2.0% ‘SHIDA’)
0
1
2
3
4
5
6
7
8
9
10
11
Months since recruitment
n=11,983 SMS logs
12
Reason for SHIDA
responses
Total
Problem responses*
377 (100)
Unique problem
responses*
140 (100)
Health issues
272 (72)
121 (86)
Non-health issues
40 (11)
33 (24)
Missing/unreachable
67 (18)
50 (36)
Reason participant did
not respond
Non-responses
n=3730
n (%)ƚ
Cell phone problems
822 (22)
Participant factors
463 (12)
Unique participant
non-responses
n=260
n (%)ƚ
205 (79)
172 (66)
WelTel Kenya1
WelTel Kenya1: Outcomes
Outcome (ITT)
Self-reported adherence (> 95%)
Viral suppression (<400 copies/ml)
SMS group
no. (%)
168 (62)
156 (57)
Control
group
no. (%)
RR
(95%CI)
P value
132 (50)
0.81
(0.69 - 0.94)
0.006
128 (48)
0.85
(0.72 - 0.99)
0.040
1.00
(0.94 – 1.07)
0.94
Ancillary analysis
Complete case
Adherence (n=358)
168 (91)
132 (91)
Viral suppression (n=400)
156(75)
128 (66)
0.88
(0.77 - 1.00)
0.047
WelTel Kenya1: Subgroup analysis (VL)
0.125
Overall
Gender
female
male
Cell phone
shares
owns
Clinic
Pumwani
Kajiado
Coptic
0.25
0.5
1
101/177 (57)
55/96 (57)
2
0.66 (0.43 -1.00)
0.80 (0.45 -1.42)
22/34 (65)
134/239 (56)
0.36 (0.14 -0.94)
0.78 (0.54 -1.12)
75/120 (63)
20/36 (56)
61/117 (52)
0.54 (0.33 -0.89)
0.54 (0.22 -1.34)
1.05 (0.61 -1.81)
WHO stage
1
2
3
4
Residence
rural
urban
(0.44
(0.28
(0.33
(0.23
31/52 (60)
42/67 (63)
56/101 (55)
5/9 (56)
0.94
0.58
0.58
1.28
30/51 (59)
126/222 (57)
0.51 (0.23 -1.12)
0.75 (0.52 -1.10)
SMS group better
Control group better
-1.98)
-1.17)
-1.00)
-7.19)
Summary
• SMS patients 24% more likely to be adherent
to ART (NNT=9)
• SMS patients 19% more likely to have
suppressed VL (NNT=11)
• 98% said would like program to continue
• 97% said would recommend it to a friend
Lester & Karanja Lancet Infectious Diseases Vol 8 December 2008
Western Kenya RCT: One-way SMS ‘reminders’
Pop-Eleches et al. AIDS, 2011
Adherence by MEMS caps: daily vs. weekly & long vs. short reminders (VL not
available.)
Two Randomized Controlled Trials (Kenya)
Nov 27, 2010
March 27, 2011
Summary
• Short, weekly reminders improved adherence
– Weekly reminders 53% achieved 90% adherence
– Control 40% achieved 90% adherence (p=.03)
• Daily reminders no effect
LEVEL 1b Evidence that Weekly SMS can improve
ART adherence.
Centre for Evidence-Based Medicine, Oxford
243 references ID’d to Nov 2011:
What doesn’t work?
Nairobi Kenya RCT: ART counselling vs. reminders
Chung et al. PLoS Med, March 2011
• A medication
reminder
alarm device
had no effect
on adherence
or viral
suppression
Emerging ART adherence innovations:
ABSTRACT: Adherence to antiretroviral therapy (ART) represents one of the strongest predictors of progression to AIDS, yet it is
difficult for most patients to sustain high levels of adherence. This study compares the efficacy of a personalized cell phone
reminder system (ARemind) in enhancing adherence to ART versus a beeper. Twenty-three HIV-infected subjects on ART
with self-reported adherence less than 85% were randomized to a cellular phone (CP) or beeper (BP). CP subjects received
personalized text messages daily; in contrast, BP subjects received a reminder beep at the time of dosing. Interviews were
scheduled at weeks 3 and 6.Adherence to ART was measured by self-report (SR, 7-day recall), pill count (PC, past 30 days at
baseline, then past 3 weeks), Medication Event Monitoring System (MEMS; cumulatively at 3 and 6 weeks), and via a
composite adherence score constructed by combining MEMS, pill count, and self report. A mixed effects model adjusting for
baseline adherence was used to compare adherence rates between the intervention groups at 3 and 6 weeks. Nineteen
subjects completed all visits, 10 men and 9 females. The mean age was 42.7 ± 6.5 years, 37% of subjects were Caucasian and
89% acquired HIV heterosexually. The average adherence to ART was 79% by SR and 65% by PC at baseline in both arms; over
6 weeks adherence increased and remained significantly higher in the ARemind group using multiple measures of
adherence. A larger and longer prospective study is needed to confirm these findings and to better understand optimal
reminder messages and user fatigue.
Boston Medical Centre
Other Innovations: TBD
Real-Time Electronic Adherence Monitoring is Feasible,
Comparable to Unannounced Pill Counts, and Acceptable.
AIDS Behav. 2011 Mar 30.
Haberer JE, Robbins GK, Ybarra M, Monk A, Ragland K, Weiser SD, Johnson MO, Bangsberg DR.
Source
Harvard Institute for Global Health, 104 Mt Auburn St, 3rd floor, Cambridge, MA, 02138, USA,
jhaberer@partners.org.
Abstract
Second generation electronic medication adherence monitors provide real-time data on pill
bottle opening behavior. Feasibility, validity, and acceptability, however, have not been
established. Med-eMonitor is a multi-compartment adherence device with reminder and
education capacity that transmits data through a telephone connection. Monthly adherence
levels were measured for 52 participants over approximately 3 months using the MedeMonitor (unadjusted and adjusted for participant confirmed dosing) and unannounced pill
counts. HIV RNA was assessed before and after the 3-month period. Acceptability of MedeMonitor was determined. Over 92% of Med-eMonitor data was transmitted daily.
Unannounced pill counts significantly correlated with adjusted Med-eMonitor adherence
(r = 0.29, P = 0.04). HIV RNA significantly correlated with unannounced pill counts (r = -0.34,
P = 0.02), and trended toward a significant correlation with unadjusted Med-eMonitor
adherence (r = -0.26; P = 0.07). Most, but not all, participants liked using the Med-eMonitor.
Med-eMonitor allows for real-time adherence monitoring and potentially intervention, which
may be critical for prolonging treatment success.
Other cell phone studies
AIDS Patient Care STDS. 2011 Mar;25(3):153-61. Epub 2011 Feb 16.
Randomized controlled trial of a personalized cellular phone reminder system to enhance adherence
to antiretroviral therapy. N=19 adults
Hardy H, Kumar V, Doros G, Farmer E, Drainoni ML, Rybin D, Myung D, Jackson J, Backman E, Stanic
A, Skolnik PR
Trials. 2011 Jun 9;12:145.
The challenges and opportunities of conducting a clinical trial in a low resource setting: the case of the
Cameroon mobile phone SMS (CAMPS) trial, an investigator initiated trial. N=198 adults
Mbuagbaw L, Thabane L, Ongolo-Zogo P, Lang T.
AIDS Patient Care STDS. 2011 May;25(5):303-10. Epub 2011 Apr 2.
Brief behavioral self-regulation counseling for HIV treatment adherence delivered by cell phone: an
initial test of concept trial. N=40 adults
Kalichman SC, Kalichman MO, Cherry C, Swetzes C, Amaral CM, White D, Jones M, Grebler T, Eaton L.
Lancet. 2011 Aug 27;378(9793):795-803. Epub 2011 Aug 3.
The effect of mobile phone text-message reminders on Kenyan health workers' adherence to
malaria treatment guidelines: a cluster randomised trial. N=2269 children
Zurovac D, Sudoi RK, Akhwale WS, Ndiritu M, Hamer DH, Rowe AK, Snow RW.
How do cell phone communications
improve ART adherence?
• Adherence to antiretroviral therapy:
supervision or support?
– Lancet Infectious Diseases, February 2012
– http://www.thelancet.com/journals/laninf/article/PIIS1473-3099(11)70354-1/fulltext
• Adherence and Retention – social capital?
Binagwaho A, Ratnayake N (2009). PLoS Med 6(1): e18.
mHealth for HIV/AIDS control:
Where is it going?
What is the potential impact?
Improved adherence and viral
suppression (retention?)
1. Improves health
2. Improves society
3. Improves economy
4. Reduces costs (drug
resistance)
5. Controls pandemic
(treatment as prevention)
Challenges:
• Can it be improved?
• Is it cost-effective?
• Can it be scaled up?
Wireless health care
M-powered
The convergence of mobile telephony and health care is under way
Nov 11th 2010 | WASHINGTON, DC | from the print edition
...Mr Gates, however, warned the participants not to celebrate too soon. Just because an mhealth pilot scheme appears to work in some remote locale, he insisted, don’t “fool yourself”
into thinking it really works unless it can be replicated at scale. Rafael Anta of the InterAmerican Development Bank was even more cautious: “We know little about impact and
nothing about business models.”
Happily, evidence of m-health’s usefulness is at last starting to trickle in. A study this week in
the Lancet, a medical journal, shows that something as simple as sending text messages to
remind Kenyan patients to take their HIV drugs properly improved adherence to the therapy by
12%.
...
“Middle-income countries are where most innovation in health care is going to come from.”
mHealth Summit 2012 (Bella Hwang)
Scale-up
Costs
2.
1. Kenya – approx. 500, 000 ART patients
PEPFAR (global) – approx. 2.5 million ART patients
Activity Based Costing – SMS Intervention:
•$11.75 USD/year per patient – Kenya
•$10.21 USD/year per patient - PEPFAR
Cost Savings
Models used:
•Freedberg et al. J Acquir Immune Defic
Syndr 2006; 43(Suppl 1):S113-118.
•Bishai D et al. AIDS 2007; 21(10):13331340.
•Grant AD et al. Am J Trop Med Hyg
2001 65: 810-21.
mHealth Summit 2012 (Bella Hwang)
PEPFAR (n=2.5 million)
UNAIDS: 2010 Global Report
New Projects
www.weltel.org
Harnessing mobile phone usage for HIV and horizontal
health systems improvement:
Prevention of mother-to-child transmission (PMTCT)
Pumwani Maternity Hospital, Nairobi
PRINCIPAL RESEARCHER:
• Joshua Kimani, University of Nairobi, Kenya
PRINCIPAL DECISION-MAKER
• Peter Cherutich, Ministry of Health, Kenya
Africa Health Systems Initiative Support to African
Research Partnerships (AHSI-RES)
WelTel Retain
This study, funded
by the NIH, will be
conducted
with
AMREF and will
involve over 700
participants at the
Kibera Community
Health Centre in
Nairobi, Kenya.
Promoting engagement in
pre-ART HIV care through SMS
This study will determine if the
WelTel intervention improves
patient retention in the first stage
of HIV care and at 12-months.
We will also evaluate the costeffectiveness of the intervention.
What about here?
• 65,000 people
living with HIV
• ~72% of ALL
Canadians
(24 million people)
have a cell phone!
WelTel: LTBI
Latent Tuberculosis Infection
• Only 50 – 60% complete
therapy for LTBI (BCCDC)
• Pilot – 16 patients
–
–
–
–
–
median age of participants was 47 (range 21-82)
(56%) were female. (n=14)
79% of participants would like the program to continue
and 86% would recommend it to a friend.
Report side effects quickly (93%)
helped them feel hopeful about their care (100%).
• BC Lung Association:
Randomized control trial
(RCT)
WelTel BC1 (HIV)
Oak Tree Clinic
– HIV support for women and
families
• Informative study
• Clinic client survey
• Pilot: 5x5 SMS
5x5 SMS pilot
Youth
Mature
Remote
ESL:
• <24y
• >50y
• >3h away
• Immigrants
Non• Poor adherence
suppressed
Support: Bristol-Myers Squibb (BMS) through BCCDC Foundation
Barriers to adherence
•
•
•
•
•
Forgetting
Drug use
Co-morbid depression
Side effects
Lack of social support
http://womenonthefence.com/wp-content/uploads/2011/06/depression.jpg
http://forladiesbyladies.com/wp-content/uploads/2010/02/3_vomiting.jpg
http://z.about.com/d/hepatitis/1/0/k/0/-/-/InjectingDrugs.jpg
http://frank.itlab.us/forgetting/think.gif
Pre-Study Questionnaire
• Clinic attendants were
asked to fill out a brief
questionnaire re:
– Cell phone possession
and use.
– Thoughts about mHealth
interventions.
– Age
– Language
– Gender
langleytoday.ca
Demographics
Demographics
Age:
median(range)
Gender
Female
Male
Transgender
Number(%) Languages
(n=180)
used
39 (11-63)
English
French
136 (78.2%) Punjabi
35 (26.1%)
African
3 (1.7%)
At home #
To text
(%)
# (%)
152 (82.6%) 170 (94.4%)
6 (3.3%)
3 (1.7%)
1st Nations
7 (3.8%)
10(5.4%)
1 (0.5%)
1 (0.6%)
2 (1.1%)
0 (0%)
European
Asian
5 (2.7%)
3 (1.6%)
2 (1.1%)
2 (1.1%)
A majority of patients used English at home, but an even greater
number used English when texting.
Cell phone stats…
Cell Phone Statistics
Own a cell phone
No
Yes-basic
Yes-smart phone
Share a cell phone
Yes-household
Yes-other
Number (%)
33 (19.0%)
80 (46.0%)
61 (35.0%)
• 180 patients polled
• 81% owned a cell phone
• 88% used text messaging
13 (7.5%)
6 (3.4%)
Have texting plan
No
Yes-pay/text or limited
Yes-unlimited
21 (14.5%)
33 (22.8%)
91 (62.7%)
Have internet on phone
No
Yes
95 (60.9%)
61 (39.1%)
Frequency of texting
Never
Rarely (once/month)
Occasionally (once/week)
Frequently (few/week)
Very frequently (daily)
37 (22.3%)
11 (6.6%)
19 (11.4%)
41 (24.7%)
58 (34.9%)
• 43% of above access the internet
from their phone
• 71% text message at least weekly
• 83% believed the intervention
could assist in clinical care/follow
up
Risks and benefits…
Perceived Benefits/Risks
Number (%)
“Could this intervention
benefit you?”
No
Yes
Don’t know
22 (12.6%)
109 (62.6%)
43 (24.7%)
“What are the benefits?”
Easy access to care
Reminders
Ability to contact
Multiple Reasons
Would rather text
14 (20.6%)
18 (26.5%)
29 (42.6%)
4 (5.9%)
3 (4.4%)
“What are the risks /
concerns?”
None
Confidentiality
Other
84 (62.7%)
36 (26.9%)
14 (10.4%)
• 2/3 felt the intervention
could benefit them
• Major concern:
confidentiality
The Intervention
Platform sends SMS
“How are you?”
Positive response
(ex: “I’m good”)
SMS: “Great, text you
again next week”
Negative response
(ex: “I have a question”)
Phone call from RN
No response in 48 hrs
SMS: “I haven’t heard from
you, everything okay?
Negative or no
response
Positive response
Gaps in care: Avoidance
“I think I was depressed, or in a rut or something. I didn’t feel like
going anywhere or doing anything … The doctor started getting a
hold of me and they asked me to start coming back in again.
And then [outreach worker] makes it easy.”
– Non-suppressed
“I don’t know, maybe I just got tired of medicine … I didn’t want
to tell anybody, I just I didn’t want to share to anybody. Myself I
don’t even know why. I know it was not a good thing to do.” –
ESL
“I’ve avoided the clinic at times, but usually because there was
something wrong and I didn’t want to deal with it … I’d come in
and see [doctor], I just would avoid the gynecologist because I
didn’t want to go and find out if I had cancer or not.” - Distance
Interest in Texting
It wouldn’t bug me, it
would make me think
that somebody cares,
actually.” – Non
suppressed
“Just a good reminder as
well. You know, little things,
and you know, keeping me
on track, keeping me in
touch, right, that’s always a
good thing.” - Mature
I could tell you right now that I have
several clients that I think that
would really benefit who right now
we have no way of communicating
with, right, and who are less likely to
come to the clinic. – Healthcare
worker
I feel like with text messaging you can
just ask whatever you want and it’s
not going to be something that’s going
to be like embarrassing or, like, I just
feel more comfortable texting” -Youth
“I’m really technology literate,
and it would just make my life a
lot easier to be able to text my
doctor” - Youth
Texting would be great… I like to
stay in contact with Oaktree. It’s
important to me because I haven’t
been well. So to be able to have
continuous contact with them, and
I haven’t… because of lack of
phone and stable living
environment.” – Non suppressed
Concerns about Texting
“Privacy is a
must” - ESL
“If you’re sending a text, I should know who’s texting and their
questions. It shouldn’t always be on HIV.” - ESL
If there’s a serious problem I want to talk to somebody, I don’t
want to text them, especially if I’m sick”- Mature
The only problem I would have probably in the future would be
with the arthritis… right now my wrists and my thumbs are
pretty sore” – Mature
I think one thing is to get hold of them, and the other thing
is actually to provide care. And sometimes even if you
actually get hold of them, that doesn’t necessarily mean
that you actually provide care. – Healthcare worker
“A text message usually prompts other work: so, consulting
other team members, or pulling lab results, or doing other
things, so that volume could increase” – Healthcare worker
Nursing Practice
How are you?
Hi! This is Karen, we changed the
ultrasound appt to thurs at 10am.
There r a couple of instructions. Is
there a number I can call u on?
When is the appt?
I’m ok I missed my
ultrasound yesterday can u
rebook please?
Thurs at 10am at [location]. U have
to eat a fat free supper on Wed and
then fast from midnight on.
Dr. M wants to ask how your
breathing is these days. Have u
been able to take the septra?
Nursing Practice
Hi! This is Karen, I’m sorry to hear
that [name]. Let us know if there is
anything we can do to support you.”
How are you?
A really gd friend of ours
was murdered last thurs..
she was only 23
It b gd to find a frief counselor..
My x mother in law passed away
in April too along w/ 2 friends up
north .. April has been very heart
breaking
Patient put in contact with Oak
Tree counselor who referred
patient to grief counselors closer
to her, as well as opportunities
for aboriginal healing
ceremonies.
Examples of Texting…
• WTBC1-14 (Mature)
• Subject: “So im on my way getting my six
month at home group I feel awesome
awesome the best yet :-*”
• Patient letting us know how she is doing. This
patient was given a phone and taught to text
because of WelTel BC1.
•
•
•
•
WTBC1-04 (Youth)
WelTel: “How are you?”
Subject: “Good”
A typical response from youth in WelTel BC1
so far.
NIH: EPIC Enhance PrEP in Communities
San Francisco
Department of Public Health
Albert Liu, Jonathan Fuchs et al.
• Interactive SMS + Next step
counselling to improve adherence
Potential deployment sites:
• US (San Francisco, Boston)
• Peru (Lima and Iquitos)
• Brazil (Rio and Sao Paolo)
• others
Summary of RCT Evidence on mHealth
Interventions to improve ART outcomes
• Adherence monitoring by SMS? - ?
– not yet known if effective for adherence promotion
– Challenging to implement, cost, compliance, stigma?
• Targeted adherence counselling? - Y
– improves adherence and viral suppression (1yr)
• Digital alarm reminders? - N
– No improvement on adherence or VL (1yr)
• One way cell phone SMS reminders? – N/Y
– no improvement in adherence (by MEMS), for daily reminders
– effective with short weekly messages. (1yr)
• Two-way cell phone SMS çheck-ins’/access to HCW? -Y
– Improves adherence and viral suppression (1yr)
• Level of Evidence: Grade A (weekly SMS)
• Support (access to care) > Reminders?
• Adherence to antiretroviral therapy: supervision or support? Lancet ID, Feb 2012
• http://www.thelancet.com/journals/laninf/article/PIIS1473-3099(11)70354-1/fulltext
My take home messages
• Keep it simple
– Every extra step (complexity) loses someone
• Keep it low cost
– Resource limited settings, vulnerable groups
• Conduct controlled studies
– What really works, and what doesn’t
• Seize the opportunity
– mHealth is a gift
The future is now
Thanks!
“All I’m saying is now is the time to develop the technology to deflect an asteroid.”
Ref: Audio & Visuals
• Lancet podcast
– http://download.thelancet.com/flatcontentassets/audio/lancet/2010/9755_27novembe
r.mp3
• Scientific American podcast (1min)
– http://www.scientificamerican.com/podcast/episode.cfm?id=text-message-outreachimproves-hiv-10-11-10
• CBC News The National (3min)
– http://www.cbc.ca/video/#/Shows/1221254309/ID=1380546967
• The Economist:
– http://www.economist.com/node/17465455