Impact of Texting & Predictive Potential of Health Literacy on Medication Adherence in Type 2 Diabetes
Impact of Texting & Predictive Potential of Health Literacy onMedication Adherence in Type 2 Diabetes Kevin A. Clauson, PharmD
Acknowledgments Shara Elrod, PharmD Angela Garcia, PharmD Elizabeth Sherman, PharmD Paula Eckardt, MD Fadi Alkhateeb, BSPharm, MBA, PhD Support from Mobilizing for Healthsm grant program (Disclosure)
Objectives• Review fundamentals of diabetes, health literacy, and mobile health (mHealth)• Explore decision points that informed study design in this research-in-progress interventional SMS study• Discuss hurdles experienced and future directions
$174 billionannual cost burden of diabetes Popul Health Metr 2010;8:29.
Health Literacy “degree to which individuals have the capacity to obtain, process, andunderstand basic healthinformation and services needed to make appropriate health decisions” Healthy People 2010
eHealth Literacy Lily Model J Med Internet Res 2006;8(2):e9.
mHealth is the use of mobile devices and global networks todeliver health services and information
82% of American adults owns a cell phone* Owns *Range: 57% (65+) to 90% (18-29)Pew Cell Phones and American Adults 2010 Does not own
Pew Internet Mobile Access 2010 87% of blacks and Hispanics own a cell phone**Compared to 80% of whites
Pew Internet Mobile Access 2010 Hispanics use their phone to go online and to text more frequently than any other group**English-speaking Hispanics
Primary Study Objective Improve medication adherence indiverse, underinsured population in USA with T2DM via text message reminders
Secondary Study Objective Examine predictive potential of health literacy for adherence
Why choose simple SMS as an intervention?GoLiveSMS
Methods (aka why did wemake the decisionswe did in the study)
Randomized, open-label trialAllocation method where all subjectshave equal chance of study groupassignment
Detect a significantdifference (two treatment arms)
Consumers would most prefer to receive a medication reminder via: Phone call 1.3 Buzzing drug vial 2.5 Email 15.2 19.5 Phone alarm 20.3 App 41.1 Text message/SMS 0 20 40 60 80 100 PercentSource: Consumer Health Information Corporation, April 2011 (n=395)
Smartphone OS Share 2% 3% 9% 38% Android iPhone 21% BlackBerry Windows HP webOS Other 27%Source: Nielsen Mobile Insights 2011
People will stop doing almost anything to check their text messages
Mobile allows targeting of populationshistorically associated with health disparities Annu Rev Public Health 2011;32:399-416.
Study of 130 adult patients with type 2 diabetes enrolled for 6 month intervention period
Recruitment from 5 Memorial Primary Care Centers
Images• http://cowbgonaca.blogspot.com/2011/06/wallpaper-for-android-mobile.html• http://www.mac-wallpapers.com/Apple-Wallpapers/white-apple-logo-wallpaper/• http://www.laptopsteria.com/wp-content/uploads/2011/06/blackberry-logo.jpg• http://www.iphonewallpaperblog.com/wp-content/uploads/2010/12/Windows-7black-iphone4Walpaper.jpg• http://www.mhs.net/locations/PrimaryCareCenters.cfm• http://h10010.www1.hp.com/wwpc/pscmisc/vac/us/product_pdfs/Slate_500_Tablet_Datasheet.pdf Images without citations are licensed stock photography
Hot-Button Issues• Will privacy and legal challenges stifle innovation and the delivery of mobile-mediated care to at-risk patient populations?• Could better decisions have been made about study design given the available information at the time?• Will our research result in findings consistent with our research hypotheses and mHealth model assumptions?