In my last article on healthcare, I talked about the potential for blockchain and big data to save lives. Wearables are another part of the growing relationship between big data and healthcare.
Not long ago, my attitude was who gives a f#@% about the Fitbit? Consider that attitude changed. The Fitbit and other health-conscious wearables present the chance for the medical community to make a real difference through big data.
First, the data on wearables:
- 86 percent of health and wellness providers believe wearables and mobile apps will increase their knowledge of patient conditions
- 76 percent feel wearables will help patients with chronic diseases
- In the first quarter of 2017, the wearables market grew by 18 percent, an increase of 24.7 million devices; International Data Corp. (IDC) believes this is just a fraction of what’s to come
T-Mobile bills this as a wearable tech revolution, one in which you can stay connected and track your life every step of the way. Along with Fitbit, the biggest names in tech are vying for a piece of the wearables market, including Apple, Samsung, and Google. That’s because IDC’s prediction on the tech’s pending popularity are a good bet. One reason why it’s a good bet is that the medical community has a growing relationship with wearables and the data they record.
Medical Research and Big Data
Health informatics professionals are excited about wearables because of the opportunity for crowdsourced medical research. Apple’s ResearchKit open source framework is one promising example. The framework allows health organizations to create apps that work with the iPhone and Apple Watch.
Some of the apps that organizations have developed with ResearchKit only require an iPhone. Others work in tandem with the Apple Watch. Through the Apple Watch, users can transmit health-related data to apps such as SleepHealth and EpiWatch.
EpiWatch collects data on the onset and duration of seizures for people diagnosed with epilepsy. Doctors can then compare data with medication regimen to get an accurate picture what’s working and what isn’t. Over time, this will give researchers a better idea of which medications are most effective for patients with differing genes and differing lifestyles. What’s more, Apple Watch sends an alert to the patient’s family or caregiver when a seizure is starting.
Like the name suggests, SleepHealth is helping researchers gather data to help people sleep better. The Apple Watch monitors how alert the user is during the day, and then the user reports their nightly sleep patterns and quality. The app’s intent is to figure out how conditions such as diabetes and obesity play a role in sleep health.
Through ResearchKit, users give medical institutions legally-valid informed consent to use their medical data for research. That’s one of the reasons why ResearchKit is so promising: it includes a framework that works well with our current patient confidentiality laws.
Personalized Healthcare and Big Data
According to economist Peter Orszag, the US spends up to $700 billion a year on medical treatments that don’t help patients. Personalization promises to streamline treatment, so patients get the care they need and billions of dollars aren’t wasted. Wearables can transmit the data that practitioners need to make each diagnosis and each prescription accurate and relevant for the individual patient.
Personalization is a major breakthrough in healthcare. But according to researchers from South Korea and Tasmania, when it comes to wearables and personalization, There is a lack of techniques and approaches which exploit the sensory data collected by wearable devices and use them for decision making and recommendations.
In other words, there’s no comprehensive and effective analytics infrastructure in place. Wearables ”including watches, heart monitors, clothing, and sleep sensors ”can transmit a great deal of data at an alarming rate. It’s up to medical organizations and government to use analytics to do the following:
- Filter valuable data and discard irrelevant noise
- Look at the individual’s medical information and make conclusions about efficacy of treatment
- Use data to make predictions and prescriptions for the patient
- Anonymize data and put it in a database
- Use database to optimize treatment for people diagnosed with conditions that researchers have been able to treat successfully by using data from wearables and smartphone apps
It sounds complicated because it is. But that doesn’t mean it can’t work. Companies are already using the internet, apps, and analytics to personalize marketing efforts. If government and healthcare organizations can navigate through the maze of our system and focus on the goal of personalizing healthcare for everyone, there’s no reason why wearables and big data shouldn’t be able to revolutionize patient care.
