Telehealth Intervention for Improved Blood Pressure Control With Targeted Incentives
Telehealth Intervention for Improved Blood Pressure Control With Targeted Incentives: Using New Technologies and Insights From Behavioral Economics to Increase the Effectiveness of Behavioral Change
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Locations
-
-
California
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San Diego, California, United States, 92093
- UCSD
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-
New York
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New York, New York, United States, 10004
- Wellcare
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New York, New York, United States, 11101
- Wellth
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-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- Age 50+
- Has hypertension diagnosis
- Owns a smartphone with sufficient data plan
- Prescribed at least one daily oral antihypertensive agent
- Prescription refill data shows <80% adherence in prior 12 months
Exclusion Criteria:
- Unable or unwilling to provide informed written consent
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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No Intervention: Group A. Standard Care ("Control")
Does not receive Wellth app.
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|
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Experimental: Group B. Wellth App ("Treatment 1")
Receives Wellth app without additional financial rewards tied to adherence.
|
Patients will receive the app that provides reminders to adhere to their self-care regimen and ability to track their daily adherence via photos of the self-care related items (medications, blood pressure cuff, meals).
|
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Experimental: Group C. Wellth App ("Treatment 2") with targeted rewards
Receives Wellth app with additional ability to earn up to $150 rewards usable at local pharmacies for using the app to track adherence.
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Patients will receive the app that provides reminders to adhere to their self-care regimen and ability to track their daily adherence via photos of the self-care related items (medications, blood pressure cuff, meals).
Participants may earn up financial rewards tied to their adherence.
The rewards are only usable at pharmacies.
|
|
Experimental: Group D. Wellth App ("Treatment 3") with non-targeted rewards
Receives Wellth app with additional ability to earn up to $150 rewards usable at many stores for using the app to track adherence.
|
Patients will receive the app that provides reminders to adhere to their self-care regimen and ability to track their daily adherence via photos of the self-care related items (medications, blood pressure cuff, meals).
Participants may earn up financial rewards tied to their adherence.
The rewards are only usable at most stores, except for prohibited purchases such as alcohol, tobacco, or firearms, and is not redeemable for cash.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Medication adherence
Time Frame: Ninety (90) days
|
Improve medication adherence, as measured by prescription fill data or app adherence, in either Group C or D receiving financial incentives tied to adherence, as compared with Groups A or B receiving standard care or app with no additional incentives, respectively.
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Ninety (90) days
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Blood Pressure Reduction
Time Frame: Ninety (90) days.
|
Reduce BP in either Group C or D as compared to group A or B, as measured by data read from photos of weekly home BP measurement readouts submitted via the app
|
Ninety (90) days.
|
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Blood Pressure Reduction
Time Frame: Ninety (90) days.
|
Compare BP across Groups B, C, and D as measured by data provided from photos of weekly home BP measurement readouts submitted via the app
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Ninety (90) days.
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Compare the effectiveness of two types of incentives for blood pressure
Time Frame: Ninety (90) days.
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Compare the difference(s) in Groups C and D for blood pressure reading levels submitted via the app
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Ninety (90) days.
|
|
Compare the effectiveness of two types of incentives for medication adherence
Time Frame: Ninety (90) days.
|
Compare the difference(s) in Groups C and D for adherence to prescribed medication (via the app and/or prescription data).
|
Ninety (90) days.
|
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Compare the effectiveness of two types of incentives for self-monitoring adherence
Time Frame: Ninety (90) days.
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Compare the difference(s) in Groups C and D for blood pressure self-monitoring adherence through the app.
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Ninety (90) days.
|
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Compare the effectiveness of two types of incentives for meal logging adherence
Time Frame: Ninety (90) days.
|
Compare the difference(s) in Groups C and D for meal logging adherence monitored and submitted through the app.
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Ninety (90) days.
|
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Compare average incentive values earned by participants in group(s) C and D
Time Frame: Ninety (90) days.
|
Evaluate and compare the average earned incentive values for participants in groups C and D
|
Ninety (90) days.
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Uri Gneezy, Ph.D., University of California, San Diego
Publications and helpful links
General Publications
- Mancia G, Fagard R, Narkiewicz K, Redon J, Zanchetti A, Bohm M, Christiaens T, Cifkova R, De Backer G, Dominiczak A, Galderisi M, Grobbee DE, Jaarsma T, Kirchhof P, Kjeldsen SE, Laurent S, Manolis AJ, Nilsson PM, Ruilope LM, Schmieder RE, Sirnes PA, Sleight P, Viigimaa M, Waeber B, Zannad F, Redon J, Dominiczak A, Narkiewicz K, Nilsson PM, Burnier M, Viigimaa M, Ambrosioni E, Caufield M, Coca A, Olsen MH, Schmieder RE, Tsioufis C, van de Borne P, Zamorano JL, Achenbach S, Baumgartner H, Bax JJ, Bueno H, Dean V, Deaton C, Erol C, Fagard R, Ferrari R, Hasdai D, Hoes AW, Kirchhof P, Knuuti J, Kolh P, Lancellotti P, Linhart A, Nihoyannopoulos P, Piepoli MF, Ponikowski P, Sirnes PA, Tamargo JL, Tendera M, Torbicki A, Wijns W, Windecker S, Clement DL, Coca A, Gillebert TC, Tendera M, Rosei EA, Ambrosioni E, Anker SD, Bauersachs J, Hitij JB, Caulfield M, De Buyzere M, De Geest S, Derumeaux GA, Erdine S, Farsang C, Funck-Brentano C, Gerc V, Germano G, Gielen S, Haller H, Hoes AW, Jordan J, Kahan T, Komajda M, Lovic D, Mahrholdt H, Olsen MH, Ostergren J, Parati G, Perk J, Polonia J, Popescu BA, Reiner Z, Ryden L, Sirenko Y, Stanton A, Struijker-Boudier H, Tsioufis C, van de Borne P, Vlachopoulos C, Volpe M, Wood DA. 2013 ESH/ESC guidelines for the management of arterial hypertension: the Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J. 2013 Jul;34(28):2159-219. doi: 10.1093/eurheartj/eht151. Epub 2013 Jun 14. No abstract available.
- Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care. 2005 Jun;43(6):521-30. doi: 10.1097/01.mlr.0000163641.86870.af.
- Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005 Jan 15-21;365(9455):217-23. doi: 10.1016/S0140-6736(05)17741-1.
- Cappuccio FP, Kerry SM, Forbes L, Donald A. Blood pressure control by home monitoring: meta-analysis of randomised trials. BMJ. 2004 Jul 17;329(7458):145. doi: 10.1136/bmj.38121.684410.AE. Epub 2004 Jun 11. Erratum In: BMJ. 2004 Aug 28;329(7464):499.
- Nwankwo T, Yoon SS, Burt V, Gu Q. Hypertension among adults in the United States: National Health and Nutrition Examination Survey, 2011-2012. NCHS Data Brief. 2013 Oct;(133):1-8.
- Ostchega Y, Berman L, Hughes JP, Chen TC, Chiappa MM. Home blood pressure monitoring and hypertension status among US adults: the National Health and Nutrition Examination Survey (NHANES), 2009-2010. Am J Hypertens. 2013 Sep;26(9):1086-92. doi: 10.1093/ajh/hpt054. Epub 2013 Apr 19.
- US Food & Drug Administration. FDA issues draft guidance to food industry for voluntarily reducing sodium in processed and commercially prepared food. 2016.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- W000003
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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