Mobile Health Technologies in Cardiovascular Disease

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


• 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


Restaurant Average Sodium (mg)Chili’s 2522

Burger King 894Panera Bread 1113

Subway 929

Low Sodium Options at Restaurants

Which foods contain high sodium?


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?



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.





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.







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


• 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

Healthcare

Mobile Health Technologies in Cardiovascular Disease