Social Engagement Strategies to Improve Medication Adherence
Study Details
Study Description
Brief Summary
In this pilot study, investigators, in partnership with Resource Centers for Minority Aging Research (RCMAR) mentorship team and the MyMeds program, will enroll patients from MyMeds with diabetes, atherosclerotic cardiovascular disease, or congestive heart failure with poor medication adherence (medication adherence percentage<80% for statin or antihypertensive therapy) who report having a least one loved one or friend (e.g., spouse) whom they consider to be invested in their health, and with whom they would be willing to share focused medical information about medication adherence in the form of text messages. Participants will be randomized into either a private feedback arm or social network arm. In the private feedback arm, participants will only receive private consultations from a pharmacist regarding their medication adherence rates. In the social network arm, participants and their chosen loved one or friend will receive bi-weekly feedback text messages regarding the participant's medication adherence. Investigators will evaluate the effects of this social network intervention on medication adherence and examine the program's acceptability among study participants. This proposal is innovative because it leverages social networks-largely unused in medical care-for health improvement.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
N/A |
Detailed Description
MyMeds (Managing Your Medication for Education and Daily Support) is an innovative care improvement program that embeds pharmacists into 27 University of California, Los Angeles (UCLA) primary care practices with the goals of (1) simplifying and reconciling medication regimens; (2) identifying strategies to improve adherence; and (3) reducing patient costs with generic substitutions and drug assistance programs. This program targets complex older adults and adults with poorly-controlled diabetes of all ages, and has reached more than 7,000 patients since its implementation in 2012. In an evaluation of over 700 older adults (≥65 years-old) who received a MyMeds consultation, investigators showed that the program reduced hospitalizations. In another evaluation that included adults of all ages, investigators showed that MyMeds reduced emergency department use (21%), systolic blood pressure (4 mmHg), and HbA1c (0.8%). However, a major underused resource in efforts to improve the health of complex adults targeted by MyMeds is their social network. Social networks are cost-free and highly influential social relationships and interactions that influence behavior and conversely are influenced by a patient's behavior. Patients spend vastly more time interacting within their social networks than they do interacting with healthcare providers, and patients often share health information with supportive members of their social network. These interactions, which are often substantial in quantity, could be designed to beneficially influence a patient's ability to create and sustain healthy behavior change. Medication nonadherence, in particular, increases morbidity, mortality, and healthcare costs in patients with chronic disease, but the private (rather than public) nature of taking medications limits the exposure of medication nonadherence to influence from the social network. An appropriately designed social network intervention can shift the dynamic, and MyMeds is an ideal setting for this type of intervention because it has robust infrastructure for identifying eligible patients, enrolling them in a pilot study, and measuring outcomes.
In this pilot study, investigators, in partnership with RCMAR mentorship team and the MyMeds program, will enroll patients from MyMeds with diabetes, atherosclerotic cardiovascular disease, or congestive heart failure with poor medication adherence (medication adherence percentage<80% for statin or antihypertensive therapy) who report having a least one loved one or friend (e.g., spouse) whom they consider to be invested in their health, and with whom they would be willing to share focused medical information about medication adherence in the form of text messages. Participants will be randomized into either a private feedback arm or social network arm. In the private feedback arm, participants will only receive private consultations from a pharmacist regarding their medication adherence rates. In the social network arm, participants and their chosen loved one or friend will receive bi-weekly feedback text messages regarding the participant's medication adherence. Investigators will evaluate the effects of this social network intervention on medication adherence and examine the program's acceptability among study participants. This proposal is innovative because it leverages social networks-largely unused in medical care-for health improvement.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Active Comparator: Private Feedback Participants will receive a smart pill bottle that will collect data on their medication usage and provide real-time data about adherence to study staff. Study staff will provide participants with private feedback about adherence in the form of meeting with a pharmacist. Feedback will be provided at the start of the study. A semi-structured interviews will be performed among a random sub-sample of participants afterwards. |
Behavioral: Private Feedback
Participant will receive medication adherence feedback from a pharmacist at the start of the study.
|
| Experimental: Social Network Intervention Participants will receive the same treatment as the Private Feedback arm but they will additionally have Social Network Feedback. A biweekly feedback text messages will be sent to both the participant and a designated loved-one or friend of the participants for 12 weeks. |
Behavioral: Social Network Feedback
Social networks are cost-free and highly influential social relationships and interactions that influence behavior and conversely are influenced by a patient's behavior. In addition to receiving a private text message regarding their medication adherence rate, participant's feedback will also be shared to a loved-one or friend that the participant is willing to share medical information with.
Behavioral: Private Feedback
Participant will receive medication adherence feedback from a pharmacist at the start of the study.
|
Outcome Measures
Primary Outcome Measures
- Change of Medication Adherence Rate [2 weeks, 4 weeks, 6 week, 8 weeks, 10 weeks, and 12 weeks]
Rate at which participant is taking their medication. Outcome would be measured bi-weekly using a smart pill bottle and syncing data using blue-tooth capable phones.
Secondary Outcome Measures
- Change in Quality of Life measured by PROMIS-29 [Baseline, 12 weeks]
Assessed using PROMIS-29 survey.
- Use of Technology for Health assessed by a short questionnaire [Baseline]
Patients will be asked whether they use tablets, smartphones, or other mobile technology.
- Change of diet composition assessed by a dietary questionnaire [Baseline, 12 weeks]
A short dietary questionnaire will be used to assess fruit, vegetable, fat, fiber, and sweetened beverage intake. For pragmatic reasons, longer food frequency questionnaire and 24 hour dietary recalls will be avoided because they may be too time consuming to complete.
- Change of physical activity assessed using items from IPAQ-S [Baseline, 12 weeks]
Investigators will measure frequency, duration and intensity of patient's physical activity using items from the International Physical Activity Questionnaire short form (IPAQ-S).
- Change of depressive symptoms assessed using CES-D survey [Baseline, 12 weeks]
Investigators will measure depressive symptoms using the CES-D, a validated scale based on the diagnostic criteria for major depressive disorder.
- Change of medical history assessed using NHANES survey [Baseline, 12 weeks]
Investigators will use questions from the NHANES
- Change of smoking behavior assessed using the California Tobacco Survey [Baseline, 12 weeks]
Investigators will use measures adapted from the California Tobacco Survey. During follow-up, investigators will ask about smoking cessation, quit attempts, reduction in daily
- Change of self-efficacy and motivation assessed using PAM instrument [Baseline, 12 weeks]
Investigators will assess self-efficacy, outcome expectancy, motivation, and patient activation. Patient activation will be assessed with the Patient Activation Measure (PAM) (see Reddy et al, JGIM 2017)
- Change of social support usages assessed by MSPSS instrument [Baseline, 12 Weeks]
Investigators will measure social support with the Multidimensional Scale of Perceived Social Support (MSPSS) instrument.
- Program Acceptability assessed by a random sub-sample of interviews [12-weeks]
After the 12-week period, a random sub-sample of participants from both arms will be interviewed to measure the study's acceptability.
Eligibility Criteria
Criteria
Inclusion Criteria:
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age > 50 years
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non-adherence to a statin or antihypertensive medication in the preceding 3 months
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access to a phone with text messaging capabilities, Bluetooth connections and internet access.
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at least one loved-one or friend with whom adherence feedback can be shared
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ability to speak English or Spanish
Exclusion Criteria:
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Any recorded A1c values of >6.5%
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ICD-9 billing codes of 250.xx
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Use of any antiglycemic medication
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Current or past participation in the Diabetes prevention Program prior to providing informed consent
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | UCLA Division Of General Internal Medicine | Los Angeles | California | United States | 90024 |
Sponsors and Collaborators
- University of California, Los Angeles
Investigators
- Principal Investigator: Joseph A Ladapo, MD/PhD, University of California, Los Angeles
Study Documents (Full-Text)
None provided.More Information
Publications
- Asch DA, Rosin R. Engineering Social Incentives for Health. N Engl J Med. 2016 Dec 29;375(26):2511-3. doi: 10.1056/NEJMp1603978.
- Brown MT, Bussell JK. Medication adherence: WHO cares? Mayo Clin Proc. 2011 Apr;86(4):304-14. doi: 10.4065/mcp.2010.0575. Epub 2011 Mar 9.
- CLA Health. Provider Information - MyMeds 2017; https://www.uclahealth.org/mymeds/providers. Accessed July 9, 2017, 2017
- Osterberg L, Blaschke T. Adherence to medication. N Engl J Med. 2005 Aug 4;353(5):487-97. Review.
- Pew Research Center. Pew Research Center: Mobile Fact Sheet. 2017; http://www.pewinternet.org/fact-sheet/mobile/. Accessed July 9, 2017, 2017.
- Smith A. Pew Research Center: Americans and Text Messaging. 2011; http://www.pewinternet.org/2011/09/19/americans-and-text-messaging/. Accessed July 9, 2017, 2017.
- Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A, Woodward M, Redfern J, Chow CK. Mobile Telephone Text Messaging for Medication Adherence in Chronic Disease: A Meta-analysis. JAMA Intern Med. 2016 Mar;176(3):340-9. doi: 10.1001/jamainternmed.2015.7667. Review.
- 2P30AG021684-16