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| Name | Class |
|---|---|
| University of California, San Diego | OTHER |
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Hypertension is the leading risk factor for cardiovascular disease, global mortality, and ranks third among the causes of disability. Treatment of hypertension is relatively straightforward, but patient adherence to long-term self-care strategies is problematically low. Three important behaviors that individuals can adhere to in order to help lower their BP are 1) Taking medications as prescribed by a physician, 2) Monitoring BP at home, and 3) Limiting dietary sodium intake. Adherence to these behaviors is problematic and currently ranges from 25% to 50%; the present Phase I STTR study is aimed at addressing the behavioral barriers for adherence to these three activities with the help of mobile technology. In particular, this STTR will develop and test an incentive program delivered through a mobile health app to increase adherence to prescribed BP control regimens and precipitate reduction in BP.
Hypertension, or sustained systolic and diastolic blood pressure (BP) of 140 and 90 mmHg or higher, is among the most frequently encountered conditions in primary care in the U.S. The estimated prevalence is 30% among all U.S. adults and increases with age, reaching 65% for adults over 65 years of age. Hypertension is also the leading risk factor for cardiovascular disease, global mortality, and ranks third among the causes of disability. Treatment of hypertension is relatively straightforward, but patient adherence to long-term self-care strategies is problematically low. Three important behaviors that individuals can adhere to in order to help lower their BP are 1) Taking medications as prescribed by a physician, 2) Monitoring BP at home, and 3) Limiting dietary sodium intake. Adherence to these behaviors is problematic and currently ranges from 25% to 50%; the present Phase I STTR study is aimed at addressing the behavioral barriers for adherence to these three activities with the help of mobile technology. In particular, this STTR will develop and test an incentive program delivered through a mobile health app to increase adherence to prescribed BP control regimens and precipitate reduction in BP. The target participants for the test are adults with clinically diagnosed hypertension. The product to be developed is a mobile health app for patient smartphones, which delivers reminder triggers and immediate behavioral reinforcement through incentives to establish long-term habits. The incentives in each treatment arm are either purely financial or framed to target specific "mental accounts" to maximize the behavioral effectiveness of the intervention. The specific aims of the study are to (1) Demonstrate feasibility of combining behavioral economics with state-of-the-art telehealth technology to deliver an optimal incentive strategy to the specific group of patients to promote adherence and reduce BP, and (2) Compare the effectiveness of two types of incentives, i.e., pure financial and mental accounting, on BP and adherence to all three self-care activities: medications, BP monitoring, and meal logging. Phase II will test the efficacy of this approach in a larger and more diverse population to search for statistically and clinically significant improvements in blood pressure resulting from use of the app with the optimal incentive strategy. Initial customers are health insurers and risk-bearing hospital systems (e.g. those with value-based reimbursement models), who are fiscally responsible for healthcare expenses for large numbers of patients with poorly controlled BP.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Group A. Standard Care ("Control") | No Intervention | Does not receive Wellth app. | |
| Group B. Wellth App ("Treatment 1") | Experimental | Receives Wellth app without additional financial rewards tied to adherence. |
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| Group C. Wellth App ("Treatment 2") with targeted rewards | Experimental | 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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| Group D. Wellth App ("Treatment 3") with non-targeted rewards | Experimental | Receives Wellth app with additional ability to earn up to $150 rewards usable at many stores for using the app to track adherence. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Wellth Smartphone App | Behavioral | 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). |
| Measure | Description | Time Frame |
|---|---|---|
| Medication adherence | 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. | Ninety (90) days |
| Measure | Description | Time Frame |
|---|---|---|
| Blood Pressure Reduction | 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. |
| Blood Pressure Reduction |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Uri Gneezy, Ph.D. | University of California, San Diego | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UCSD | San Diego | California | 92093 | United States | ||
| Wellcare |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 24171916 | Background | 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. | |
| 15652604 | Background | 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. |
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| ID | Term |
|---|---|
| D006973 | Hypertension |
| D010349 | Patient Compliance |
| ID | Term |
|---|---|
| D014652 | Vascular Diseases |
| D002318 | Cardiovascular Diseases |
| D010342 | Patient Acceptance of Health Care |
| D000074822 | Treatment Adherence and Compliance |
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Approximately 500 participants will be randomized into four groups (n=125 per group). Some groups will receive the Wellth app providing reminders and regimen tracking, and some groups may have the opportunity to earn financial rewards for their adherence.
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| Targeted Incentives | Behavioral | Participants may earn up financial rewards tied to their adherence. The rewards are only usable at pharmacies. |
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| Non-Restricted Incentives | Behavioral | 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. |
|
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
| Ninety (90) days. |
| Compare the effectiveness of two types of incentives for blood pressure | Compare the difference(s) in Groups C and D for blood pressure reading levels submitted via the app | Ninety (90) days. |
| Compare the effectiveness of two types of incentives for medication adherence | Compare the difference(s) in Groups C and D for adherence to prescribed medication (via the app and/or prescription data). | Ninety (90) days. |
| Compare the effectiveness of two types of incentives for self-monitoring adherence | Compare the difference(s) in Groups C and D for blood pressure self-monitoring adherence through the app. | Ninety (90) days. |
| Compare the effectiveness of two types of incentives for meal logging adherence | Compare the difference(s) in Groups C and D for meal logging adherence monitored and submitted through the app. | Ninety (90) days. |
| Compare average incentive values earned by participants in group(s) C and D | Evaluate and compare the average earned incentive values for participants in groups C and D | Ninety (90) days. |
| New York |
| New York |
| 10004 |
| United States |
| Wellth | New York | New York | 11101 | United States |
| 15908846 | Background | 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. |
| 23604493 | Background | 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. |
| 15194600 | Background | 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. |
| Background | US Food & Drug Administration. FDA issues draft guidance to food industry for voluntarily reducing sodium in processed and commercially prepared food. 2016. |
| 23771844 | Background | 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. |
| D015438 | Health Behavior |
| D001519 | Behavior |