Health, Fitness, Wellness: How Predictive Analytics Can Inform Healthy Lifestyles
Technology has made it possible for billions of consumers to shrink the world down to bite-sized, accessible chunks of data. But the growing popularity of analytics for health and fitness and wearable devices is motivating users to focus not only on the world around, but the world inside as well.
A Juniper Research report noted that 19 million digital-fitness wearables were in use by the end of 2014 – spurred by a population of people who believe that these devices can abet their desire to exist healthier, reduce illness – and live longer. The combination of wireless networks, non-invasive sensors and ultra-low power consumption chips enables continuous data collection from health-conscious consumers. Mobile solutions—in combination with data analytics—increasingly make it possible to provide users with a head-to-toe view of one’s health.
Of course, achieving “wellness” is very much a holistic affair—affected by nutrition, physical activity, positive relationships, mechanisms to cope with stress and career success, as well as spiritual and emotional health.
But given the proliferation of Fitbits and Jawbones, as well as the increasingly sophisticated and connected medical devices, we now sit atop a growing mountain of data being gathered today from patients in the FDA-regulated health arena as well as individuals in the unregulated health, fitness, and wellness markets.
All of this data is meaningless unless it promotes change. Consumers and physicians alike are still trying to determine how best to use this data in an actionable and insightful way. One answer: using predictive analytics techniques to analyze current and historical data, and then presenting it in a manner that promotes both awareness and action. (As a side note, you can even spend a few bucks to have your DNA sequenced and analyzed to gauge your genetic disposition to potential ailments in the future.)
Analytics is particularly valuable for measuring, benchmarking and improving health, fitness and wellness. All stakeholders in the health paradigm – including payers, providers and vendors — agree that predictive analytics can help increase the quality of health care, prevent adverse events, improve overall health and decrease costs.
Both real-time and historical data are used, aggregated from multiple data streams to create a personalized baseline for each individual. Visualizing data through dashboards is key to the consumer’s ability to leverage the wealth of data available. These visualizations must be intuitive and have a very clean user interface. Otherwise, users may feel overwhelmed and hesitant to access the information. Apps like MyFitnessPal and RunKeeper help consumers with weight loss and activity tracking while other apps address particular applications, such as FitTrace’s focus on body composition and JEFIT Workout’s focus on workouts and gym logs.
With a predictive calculation unique to each person, users can understand whether they are missing, meeting or beating their fitness targets. In addition, users can be given suggestions for making up shortfalls in daily goals, nutritional analysis and advice to stay on course toward achieving the overall objectives.
Several apps aggregate the user data and make it available on an anonymized basis for benchmarking to the overall population. For example, Jawbone’s UP fitness trackers include a Smart Coach insight and coaching engine. Smart Coach integrates knowledge about how the UP community sleeps, moves and eats with a user’s personal activity. An individual’s data is parsed into actionable insights and uniquely personalized guidance.
A great feature of several fitness apps is the ability to share and compare with social groups. This social sharing and comparing has been seen to be a key motivator – tapping into our innate need for empowerment and competition, leading to positive behavior modification to stay on track with our fitness goals.
Increasingly, consumers, at their option, can also share their personal health and fitness data with healthcare providers, personal trainers, nutritionists and physical therapists. This sharing is a growing area of importance going forward, but additional work needs to be done, especially on the diagnostic health side, to promote usage by all stakeholders. Recipients should receive succinct and pertinent information rather than be flooded with reams of data.
Last but not least, privacy can be of concern regarding the collection and sharing of health data, albeit more on the clinical health side. . Vendors are increasingly cognizant of this issue and are working on both encryption standards and technologies.
There have been early gains in our overall health with the use of predictive analytics. Such insights have given us a measure of control over our future wellness in ways that we could not have imagined. Increasing sophistication in predictive analytics techniques, right-sizing the information flow and bolstering the privacy defenses will lead to longstanding changes in our overall health, and in turn, our life expectancy.