mobile health technologies in cardiovascular disease
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Mobile Health Technologies in Cardiovascular Disease
Mike Dorsch, PharmD, MS, FCCP, FAHAClinical Associate Professor
University of Michigan College of Pharmacy
Disclosures
• Grant/Research Support: – AHRQ, NIA, Frankel CVC, LHS
Objectives
• Overview the advances in mobile technologies
• Show a care model that lends itself to mobile technologies
• Discuss two cases for using mobile technologies in cardiovascular disease:– Geofencing technology to help patients
reduce sodium intake– Remote monitoring in heart failure
Happy 10th Anniversary!
• Cameras• Displays• GPS and GLONASS• Wireless Communications
– LTE, WiFi, bluetooth, NFC• Fingerprint sensors• Gyro• Accelerometer• Proximity sensor• Ambient light sensor• Barometer• Memory• Microprocessors
What do mobile devices have to offer?
Global Mobile Growth 2015-2020
Source: Cisco VNI Mobile, 2016
Global Connected Wearable Devices 2015-2020
Source: Cisco VNI Mobile, 2016
US Mobile Connectivity Index
GSMA Connectivity Index 2016
Smartphone Use in the US
Pew Research Center, 2015
Smartphone Use in the US
Pew Research Center, 2015
Model of Care
Credit: Larry An, MD
Cardiovascular Disease Prevalence
Dariush Mozaffarian et al. Circulation. 2016;133:e38-e360
Deaths Due to Cardiovascular Disease
Dariush Mozaffarian et al. Circulation. 2016;133:e38-e360
• Cardiovascular risk assessment– Aspirin– Statin
• Blood pressure control– Sodium intake
Million Hearts Initiative – Prevent Cardiovascular Disease
1.Starthere
2.Checkthetotalcaloriesperserving
3.Limitthesenutrients
4.Getenoughofthesenutrients
5.QuickGuidefor%DailyValue:5%orlessislowand20%ormoreishigh
Green < 120 mg of sodium per serving Yellow 120-480 mg of sodium per serving Red > 480 mg of sodium per serving
Changes in Salt Intake in England
BMJ Open 2014;4: e004549.
Greater than 2300mg Sodium Daily
Incident Cardiovascular Disease
BMJ. 2009 Nov 24;339:b4567.
Sodium Intake and CVD Mortality
CVD Mortality
Public Health Nutr. 2015 Mar;18(4):695-704.
Usual Daily Intake of Sodium Among US Adults
85-90% of US adults are above 2300mg/dayNHANES 2009-2012.
Dietary Sodium in the US
Total US food expenditures away from home and at home
Dariush Mozaffarian et al. Circulation. 2016;133:e38-e360
Restaurant Average Sodium (mg)Chili’s 2522
Burger King 894Panera Bread 1113
Subway 929
Low Sodium Options at Restaurants
Which foods contain high sodium?
Dariush Mozaffarian et al. Circulation. 2016;133:e38-e360
Patient Estimation of Sodium Intake per Day
J Am Coll Nutr. 1991;10:383-393
Focus Groups About Sodium Intake
• Patients say they struggle picking low sodium options in restaurants
• Patients think restaurants don’t serve low-sodium foods
• Patients have low confidence in picking low sodium foods at restaurants
• Patients cannot tell if a grocery store item is low in sodium
• Patients have low confidence estimating how much sodium they eat in a day
One-on-one Interviews About Following a Low Sodium Diet
Health IT and sodium
• Intervention – a mobile application– Geofencing-based alerts at restaurants with low sodium
options– Scanning foods at grocery stores and providing lower sodium
options– Top 5 sodium containing foods
• Aim 1 – Develop the messages in focus groups• Aim 2 – Study the efficacy of the mobile application in HTN
patients
Health IT and Sodium
What do I eatThat is low sodium
At McDs?
Health IT and Sodium
Health IT and Sodium
Week 0 Week 2 Week 4 Week 8
Dietary assessment -ASA24, FFQ with sodium screenSelf-care – SCFLDSClinical measures –24-hr urinary sodium excretion, spot urinary excretion of sodium, dipstick chloride, dipstick creatinine, blood pressure
Dietary assessment -ASA24, FFQ with sodium screenSelf-care – SCFLDSClinical measures - 24-hr urinary sodium excretion, spot urinary excretion of sodium, dipstick chloride, dipstick creatinine, blood pressure
Clinical measures -dipstick chloride, dipstick creatinine, blood pressure
Week 6
Abbreviations – ASA24 = Automated Self-administered 24-Hour Dietary Recall, FFQ = Food Frequency Questionnaire, SCFLDS = Self-care Confidence in Following a Low-sodium Diet Scale
Heart Failure
Prevalence:5.7 million
>8 million by 2030
Mortality:≈50% at 5 yearsEconomic costs:
≈$30.7 billion (direct and indirect)$69.7 billion by 2030
Morbidity:≈1 million hospitalizations/yr
Circulation 2015;131:e29-e322
Heart Failure
• Self-management is defined as an active cognitive process undertaken by the patient to manage their heart failure
• HF patients self-monitor weight, sodium, fluid intake and symptoms
• Patients interpret self-monitoring and perform self-management
• We developed a website application to determine if self-monitoring improved HF status
Health IT and Heart Failure
• Prospective single-center pre/post study• Patients enrolled from the Advanced HF at the
FCVC• Self-monitoring was performed for 12 weeks• HF status was measured by:
– NYHA class, MLWHF, weight, exercise, walk distance, physical exam
Telemed J E Health. 2015;21(4):267-70.
Health IT and Heart Failure
Telemed J E Health. 2015;21(4):267-70.
Health IT and Heart Failure
Telemed J E Health. 2015;21(4):267-70.
Variable Value (N=24)Age (yrs) 59 ± 9Female Gender (%) 63 (15)Ejection Fraction (%) 28 ± 10Hospitalizations in the last year (%)
0 1 or more
54 (13)46 (11)
ICD (%) 83 (20)Coronary Artery Disease (%) 58 (14)HTN (%) 54 (13)Atrial fibrillation (%) 38 (9)Diabetes (%) 33 (8)Median duration of monitoring was 67 days.
Health IT and Heart Failure
Telemed J E Health. 2015;21(4):267-70.
Health IT and Heart Failure
Telemed J E Health. 2015;21(4):267-70.
Health IT and Heart Failure
Telemed J E Health. 2015;21(4):267-70.
Parameter Pre Post P-valueWeight (lbs) 209 ± 9.6 207 ± 9.4 0.389 Exercise/week (no.) 1.29 ± 0.5 2.5 ± 0.6 0.3 Walk distance (yds) 572 ± 147 845 ± 187 0.119 JVD (cm) 8.1 ± 0.6 6.7 ± 0.3 0.083 Peripheral edema (%)
29.2 16.7 0.375
JVD = jugular venous distention
Conceptual Model for Pre-clinical Measures of Clinical Worsening
Self-Monitoring
Active
Clinical symptoms ofworsening HF
CURRENT STRATEGY
Self-managementHealth care provider
support
Self-Monitoring
ActivePassive
Weight, steps (movement)And sleep patterns
5 questions about howpatients are feeling
Self-regulation from visualgraphs of progress and push
notifications
Self-managementHealth care provider
support
FUTURE STRATEGY
Pre-clinical measurementsof worsening HF
Clinical symptoms of worsening HF
Heart Failure Progression
Hea
lth S
tatu
s
Time
= Normal Progression = Progression with adaptive mobile technologies
Health IT and Heart Failure
• Developing a mobile application that incorporates many aspects of the website
• Adding into the application passive remote monitoring and motivational messages
• Creating a predictive model to identify pre-clinical markers of clinical worsening using wearable devices
Conclusions
• Mobile technology offers a chance to collect data about patients in their environment and gives researchers access to data that has not been collected previously
• GPS and geofencing are promising technologies for contextual just-in-time interventions
• Wearable devices may offer a key into pre-clinical states in chronic disease management
Special Thanks!
• Todd Koelling, MD• Scott Hummel, MD, MS• Larry An, MD• CHCR
– Rex Timbs– Emerson Delacroix– Kristen Miller– Juan Arzac– Diane Egleston