The Role of Big Data in Personalizing the Healthcare Experience: Mobile

Cheaper, faster, better technology is enabling nearly one in four people around the world to connect with each other. It’s available anytime and anywhere as online social networks have changed the way we live, work, and play. In healthcare, the data generated by mobile phones and sensors can give us new information about ourselves. In actuality, it can extend the reach of our healers and accelerate a societal shift towards greater personal engagement in healthcare.

Mobile, Gamification and Sensors

Mobile is increasingly ubiquitous: with 6.8 billion mobile subscriptions and anytime, anywhere access. Specifically, smart gadgets are now giving cheap, mobile computing power to millions of consumers and healthcare practitioners.

Gaming is popular too: 121.3 million Americans play mobile games at least occasionally. Nowadays, health apps are using games to improve health and wellness. Gaming elements are bringing deeper engagement and improving compliance. Not to mention, they help make managing chronic conditions and complicated regimens easier.

Mobile sensors: accelerometers, location detection, wireless connectivity and cameras. These all signify another big step towards closing the feedback loop in personalized medicine.

There is no more personal data than on-the-body or in-the-body sensors such as those pictured below. Sensors used to be exclusive to the laboratory (polysomnography) or hospital (EEG, EKG).  Now, body area network applications can be used not only for fitness/wellness, but also to identify, diagnose, and manage acute and chronic disease.

Online social networks like Facebook and Twitter that offer peer-to-peer support are another useful factor in enabling this shift in healthcare. 23% of people with chronic illnesses go online to find others with related conditions.

We see online social tools as a means to gather motivation and support health-related activities, similar in concept to Weight Watchers and Alcoholics Anonymous. As we all know, changing routines is hard. For some of us, adding the support of online social networks may help nudge our behaviors in a more positive direction.

Bigger Picture: Who Cares and Why?

In terms of Big Data, mobile health is a new frontier contributing new streams of behavioral, biometric, and environmental data in real time. Combining these new data flows with EMR/EHR data and giving patients’/consumers’ access may allow us to make better-informed decisions and lead healthier lifestyles.

Obviously, mobile is extending the reach of our healers: healthcare providers, fitness coaches, and other supporters. Providers are in desperate need of better educational tools to improve efficiency and lower costs. Physical therapists, fitness coaches, home aides, occupational therapists, discharge planners, doctors, nurses, public health, and other health educators are all interested in one thing: employing new ways to help patients understand their diseases and take better care of themselves.

Mobile health is enabling experimentation across the disease spectrum

Today, there are over 96,000 health apps for mobile phones that use sensors, social networking, and gaming to improve health. This explosion includes mobile fitness tracking, support networks, and brain games. Part of the app explosion can be attributed to the government, celebrity endorsements, and the growth of corporate wellness plans. These plans include Keas, Redbrick Health, Limeade, and ShapeUp, which encourage Americans to improve their health.

According to a Misfit publication, mobile health apps could help over 124 million people with hypertension and 105 million obese adults. In addition, 21 million people with sleep apnea, 79 million pre-diabetics, and 81 million adults with cardiovascular disease can benefit.

The data generated by body sensors and mobile phones can provide a rich new source of insights for patients, providers, and researchers. Companies such as Patients Like Me are using their data for various things: to support their members, but also new research initiatives in multiple sclerosis and other diseases.

Above all, active and passive data collection can provide new insights into human behavior.

In behavioral health:

Ginger.io uses passive data collection to develop algorithms that detect when behavior patterns are abnormal. It helps people better cope with depression.

OneHealth uses active data collection to gather real-time behavioral data. It can help us better understand how to cope with multiple conditions such as addiction, obesity and diabetes.

In cognitive health and wellness:

Lumosity’s database of 40 million users through the Human Cognition Project is looking for correlations between lifestyle, age, and cognitive performance.

Brain Resource uses its 20 year-old standardized brain database to better understand brain health, wellness, and disease.

Lark uses the world’s largest sleep database to tweak its automated coaching algorithm to better address the needs of its customers.

AchieveMint, a motivation tool, aggregates health data from apps as well as data from other components of the social graph. Similarly, the goal is to make customized health suggestions  to what we now get on Amazon for books or Zappos for shoes.

Just as developers and providers try to better fit the treatment to the patient, patients are increasingly likely to be engaged in their own care. Furthermore, an increasing number of healthy people are taking proactive responsibility for their own fitness and preventive care. Mobile health tools promote taking better care of ourselves to accelerate a wider adoption of healthier lifestyles and preventive care.

Nevertheless, tune in September 18th, at 10am PST for the Webinar “Using Big Data to Personalize the Healthcare Experience”. Three forward-thinking companies that are using mobile to collect new data streams will be featured.

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