wh2014 session: know your audience predictors of success for a patient centered
DESCRIPTION
From Wireless Health 2014 Technical Session 6: Global, featuring speaker Mark Siedner.TRANSCRIPT
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KNOW YOUR AUDIENCE PREDICTORS OF
SUCCESS FOR A PATIENT-CENTERED
MARK J. SIEDNER
MASSACHUSETTS GENERAL HOSPITAL CENTER
FOR GLOBAL HEALTH
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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
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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
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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
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Have we harnessed that potenEal?
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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)
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2) Conceptual Framework
ART Eligibility ART Ini5a5on
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ART Eligibility ART Ini5a5on
Lack of Awareness of ART Eligibility (CommunicaEon)
2) Conceptual Framework
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2) Conceptual Framework
ART Eligibility ART Ini5a5on
Poverty (TransportaEon Costs)
Lack of Awareness of ART Eligibility (CommunicaEon)
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2) Conceptual Framework
ART Eligibility ART Ini5a5on
Poverty (TransportaEon Costs)
Lack of Awareness of ART Eligibility (CommunicaEon)
1. SMS No5fica5on of Laboratory Results
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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
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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)
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4) End-‐User Acceptability
• Pre-‐study survey of 50 clinic clients – 100% expressed interest in a cell phone-‐based system of communicaEng clinic informaEon
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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.”
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5) IteraEve Assessment
A. Development stage – Dimagi Design
B. Pilot – Clinic and research staff pilot tesEng – Feedback to Dimagi
C. Efficacy Trial
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Efficacy Clinical Trial • Eligibility – Adults in HIV care in Mbarara
– Undergoing “high-‐risk” CD4 count tesEng – Access to a cell phone
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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)
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Efficacy Clinical Trial
Enrollment
• Baseline Survey • CD4 TesEng
CD4 Count Result Outcomes Assessment
• Group DeterminaEon • SMS Scheduling
• Follow-‐up Survey
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Efficacy Clinical Trial
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Efficacy Trial • Message DisseminaEon
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Efficacy Trial
DAYS TO CLINIC RETURN
Day 14
DAYS TO ART INITIATION
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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
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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
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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
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Cohort CharacterisEcs
• Median age 30 • 55% female
• Median HH income $100/month
• 60% primary educaEon or less
• 72% successful read a sentence on enrollment
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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
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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
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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
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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
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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
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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
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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
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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
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Next Steps
• Clinic wide automated intervenEon in development
• Post-‐intervenEon effecEveness • Post-‐intervenEon acceptability
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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
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