Perspectives on mHealthbusiness development

Arto LeppisaariTampere University of Technology

Data‐Driven Medicine28.3.2012

Project Felix

Research‐based business development projectDepartment of Biomedical Engineering

Tampere University of Technology

Part of the new research group focusing intoPersonal Health Technologies

for chronic disease management and prevention

Content

mHealth promise on chronic disease challenge

Personal health monitoring

Behavior change

Mass market adoption barriers

”World is ready for mHealth”

Source: “Socio‐Economic Impact of mHealth”, Boston Consulting Group and Telenor, Research2guidance, WHO

30% of doctors in US are using smartphone or tablets in daily work 

17,000 health and medical apps available for download1 billion smartphone users by 2016

30% downloads at least one mHealth application

500 mHealth projects ongoing worldwide, showing that‐ costs related to data collection can be reduced by 24%.‐ costs in elderly care can be reduced by 25%

77% of the disease burden in Europe are accounted for disorders related to lifestyles

5

2.4.2012

ActivityExercise

Sleep

Wellness DiaryDaily ActivityWeightNutrition…

Withings

Zeo SportsTracker

Personal Health Monitoring

Blood pressure

Philips DirectLife

Weight

Ease‐to‐use connected sensorseverywhere

NFC and Low Energy Bluetooth 4.0 technologies deployedin the majority of smartphones by the end of 2012 Tapping – new, intuitive way to interact Wearable wireless sensors with long operating times

VTT HearMeFeelMeNike+ Fuelband

169.5 million wearable wireless health and fitness sensors sold in 2017, up from 21 million in 2011.~90% supporting mobile phone connectivity, compared to 5% currently[ABI Research]

Data aggregation

Standard interfaces

Connectivity platforms

Standardised interfacesPersonal Health Record (PHR)

Open interfaces

Quantified Self

Share

It’s about understanding yourself, who you are, through numbers

Compare

Health outcomes are largely producedby the citizen behaviors

Determinants of health status

Health Care(10%)

Environmental(5%)Behavioral

(40%)

Social(15%)

Genetic(30%)

McGinnis et al., Health Affairs 21(2), 2002

70–90% of cardiovascular disease, type II diabetes and stroke would be avoided with healthy lifestyles (Willet, 2002)

Lifestyle is very personal and impacted by complex motivational and value‐basedfactors

Knowledge‐behavior gap Most citizen have sufficient

information about healthy lifestylesbut this information does nottransform into behaviors

It is unlikely thatmore informationalone would significantly improvethe situation

Human being is not a rational actor Most of our daily behaviors are

automatic decisions

“Put hot triggers in the path of motivated people” B.J Fogg

http://designwithintent.co.uk/http://persuasive‐patterns.com/

Triggers

Right moment and incentive

Easy, fast feedback ‐ deep insights

mHealth adoption curve?

Diffusion of innovations[Rogers]

Leading the Way 10%

In it for Fun 17%

Value Independence 19%

I need a plan 20%

Not right now 24%

Get through the day 11%

Health & Wellness segmentation in US[The Future Company]

Healthcare provider role in mHealthmass market adoption

Evidence basedProvider engaged

Shared cost

Prescription

Case example: Exercise is medicine• Healthcare professional supervised, 

evidenced based exercise program for cardiac prevention and rehabilitation.

• Exercises could be done at home, butcurrently health insurance supportonly gym training

Take away messages

Technology infrastucture ready for mHealth

To efficiently prevent and manage lifestyle diseases, a behavioral change is needed. Citizen need to take responsibility on own health

We need solutions thatmake the healthy choice the easychoice. Persuasive technology as a great tool.

Mobile Health need to be incorporated into healthcare practices in order to create mass market adoptionMaking the healthy choice the default choice

Tampere University of Technology

Personal Health Technologiesfor chronic disease management and prevention

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