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From Wireless Health 2014 Technical Session 6: Global, featuring speaker Mark Siedner.
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KNOW YOUR AUDIENCE PREDICTORS OF
SUCCESS FOR A PATIENT-CENTERED
MARK J. SIEDNER
MASSACHUSETTS GENERAL HOSPITAL CENTER
FOR GLOBAL HEALTH
Know Your Audience: Predictors of success for a pa5ent-‐
centered SMS applica5on to augment HIV linkage to care in rural Uganda
Research Abstract, Wireless Health 2014 Oct 29-‐31, 2014, Bethesda, MD, USA
Mark J. Siedner Massachuse1s General Hospital Center for Global Health
Conflicts of Interest and Funding
• No financial conflicts of interest to report • I receive salary and research support from: – Fogarty InternaEonal Center R24 TW 007988
– NaEonal InsEtutes of Health K23 MH 099916 – Harvard Center for AIDS Research
Great PotenEal for Mobile Health in sub-‐Saharan Africa
InternaEonal TelecommunicaEons Union, 2014
-
100
200
300
400
500
600
700
2005 2006 2007 2008 2009 2010 2011 2011 2013 2014*
Fixed-telephone subscriptions
Mobile-cellular subscriptions
Individuals using the Internet
MILL
IONS
Have we harnessed that potenEal?
Keys to Successful mHealth ImplementaEon
Locally defined and prioriEzed health problem Conceptual framework – How (and if) mobile health can address the problem
– Is it sufficient to do so?
Co-‐creaEon (or local creaEon) Comprehensive evaluaEon by the end-‐user acceptability, feasibility and acceptance
IteraEve assessment (develop pilot efficacy effecEveness implementaEon)
2) Conceptual Framework
ART Eligibility ART Ini5a5on
ART Eligibility ART Ini5a5on
Lack of Awareness of ART Eligibility (CommunicaEon)
2) Conceptual Framework
2) Conceptual Framework
ART Eligibility ART Ini5a5on
Poverty (TransportaEon Costs)
Lack of Awareness of ART Eligibility (CommunicaEon)
2) Conceptual Framework
ART Eligibility ART Ini5a5on
Poverty (TransportaEon Costs)
Lack of Awareness of ART Eligibility (CommunicaEon)
1. SMS No5fica5on of Laboratory Results
2) Conceptual Framework
ART Eligibility ART Ini5a5on
Poverty (TransportaEon Costs)
Lack of Awareness of ART Eligibility (CommunicaEon)
1. SMS No5fica5on of Laboratory Results
2. Transporta5on Reimbursement
3) Co-‐Create
• Development team – Clinic staff – Clinic database management team – Research team
• Biomedical
• Anthropology • Social scienEsts
– Dimagi Inc (web development company) – Yo! Uganda (content aggregator)
4) End-‐User Acceptability
• Pre-‐study survey of 50 clinic clients – 100% expressed interest in a cell phone-‐based system of communicaEng clinic informaEon
4) End-‐User Acceptability
“It will save the cost of transport because we come and we find nothing ready for almost four :mes of coming to the clinic and going with no achievement. So it would make us come when we are sure.”
5) IteraEve Assessment
A. Development stage – Dimagi Design
B. Pilot – Clinic and research staff pilot tesEng – Feedback to Dimagi
C. Efficacy Trial
Efficacy Clinical Trial • Eligibility – Adults in HIV care in Mbarara
– Undergoing “high-‐risk” CD4 count tesEng – Access to a cell phone
Efficacy Clinical Trial • Study groups – Pre-‐intervenEon period (standard of care) – IntervenEon period (SMS)
• Normal laboratory result: single SMS
• Abnormal laboratory result – RandomizaEon
» Direct Message
» PIN-‐protected Message
» Coded Message (ABCDEFG) – Up to 7 daily messages
– TransportaEon reimbursement (~$6USD)
Efficacy Clinical Trial
Enrollment
• Baseline Survey • CD4 TesEng
CD4 Count Result Outcomes Assessment
• Group DeterminaEon • SMS Scheduling
• Follow-‐up Survey
Efficacy Clinical Trial
Efficacy Trial • Message DisseminaEon
Efficacy Trial
DAYS TO CLINIC RETURN
Day 14
DAYS TO ART INITIATION
Why did (and didn’t) it work?
• Secondary analysis • Predictors of successful response to an SMS-‐based intervenEon for paEent end-‐users in rural Uganda
Predictors of Response
PIN SMS Message + Incen5ve:
49 Abnormal Results
Coded SMS Message + Incen5ve:
43 Abnormal Results
138 Abnormal Results
Direct SMS Message + Incen5ve:
46 Abnormal Results
Randomiza5on
Outcomes of Interest
• Self-‐reported receipt of at least one SMS • Accurate idenEficaEon of SMS
• Appropriate clinic return – Abnormal result: ≤7 days of first SMS
Cohort CharacterisEcs
• Median age 30 • 55% female
• Median HH income $100/month
• 60% primary educaEon or less
• 72% successful read a sentence on enrollment
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61)
0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61)
0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61)
0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61)
0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61) 0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
†Restricted to par5cipants with an available cellular phone on enrollment
Reported SMS Receipt Accurate SMS Identification
Return to Clinic <7 Days
AOR (95%CI) P-value AOR (95%CI) P-
value AOR (95%CI) P-value
Age <26 REF REF REF 26-32 0.97 (0.30 – 3.13) 0.97 0.33 (0.07 – 1.60) 0.17 0.71 (0.24 – 2.07) 0.53 33-39 1.43 (0.40 – 5.16) 0.59 0.98 (0.18 – 5.27) 0.99 0.72 (0.23 – 2.19) 0.56 ≥40 1.49 (0.41 – 5.45) 0.54 0.24 (0.05 – 1.19) 0.08 0.66 (0.22 – 1.95) 0.45 Female gender 0.95 (0.38 – 2.37) 0.92 1.30 (0.44 – 3.83) 0.63 1.15 (0.52 – 2.52) 0.73 CD4 Result ≤100 REF REF REF 101-350 1.08 (0.39 – 2.96) 0.89 0.51 (0.13 – 1.96) 0.33 0.28 (0.11 – 0.75) 0.011 Read a complete sentence
2.14 (0.85 – 5.39) 0.11 4.54 (1.42 – 14.47) 0.011* 3.81 (1.61 – 9.03) 0.002*
Accessed sample SMS on enrollment†
3.05 (0.76 – 12.21) 0.12 0.63 (0.08 – 4.68) 0.65 4.90 (1.06 – 22.61)
0.04*
Randomized SMS Format Direct REF REF REF PIN 0.76 (0.27 – 2.17) 0.61 0.11 (0.03 – 0.44) 0.002* 0.26 (0.10 – 0.66) 0.005* Coded 1.00 (0.31 – 3.20) 0.99 0.38 (0.08 – 1.80) 0.22 0.58 (0.22 – 1.55) 0.28
Summary 1
• Strongest predictor of receipt and response to SMS-‐based mHealth intervenEon was proved literacy on enrollment
• Cell phone literacy also appears important • Gender, age, educaEonal a1ainment not predicEve
• PIN-‐protected messages are challenging • Coded messages protect privacy without challenging feasibility
Next Steps
• Clinic wide automated intervenEon in development
• Post-‐intervenEon effecEveness • Post-‐intervenEon acceptability
Collaborators and Team
• MGH CGH/HMS • Alexander Lankowski • David Bangsberg • Jessica Haberer • Norma Ware • Richard Holden (IU)
• MUST • Yap Boum • Anthony Wilson • Bosco Bwana • Data Santorino • Winnie Muyindike • Isaac Aturinda • Evans Mwesigwa
www.wirelesshealth2014.org