Big Data Approach to Discovery

This week at HIMSS16 in Las Vegas, the Intel Health & Life Science team displays many new and exciting ways to make health more personal through technology. In the booth, we will share the You 24x7 Cardiovascular Wellness Study – a Big Data approach to clinical research.

What’s unique about the You 24x7 Cardiovascular Wellness Study is researchers are using a big data analytics platform to bring together a wide range of data – from daily life plus clinical data – to get a more complete picture of the participants’ wellness. Hundreds of volunteers wore an activity tracker 24x7 for six-months and contributed their EHR, clinical lab reports and remote patient monitoring data, including weight and blood pressure, for a team of cardiologists and sleep experts to analyze at Oregon Health & Science University (OHSU).

Find out more: OHSU Wearables Big Data Analytics Paper

Study Details:

A Basis Peak watch provided minute-by-minute data on activities, sleep stages, pulse, calorie burn, perspiration and skin temperature. Participants told the investigators that having their own dashboard to view their information — on the watch itself, on a smart phone app, as well as in a web browser — helped them understand their lifestyle choices, quantifying their sleep quality and exercise levels, for example.

Some of the participants also had weight scales and blood pressure monitors in their home. Every time they take a reading, the data streams wirelessly to an Intel-powered remote patient monitoring gateway, and the gateway uses the 3G network to send the information securely to a cloud environment.

The Basis Peak watch, scale, blood pressure cuff, clinical data and EHR all contributed to a robust data set and this is definitely Big Data — a half-billion data points over the course of the trial.

Exploring expanded data sets:

A team of cardiologists, sleep experts and biostatisticians at the OHSU Knight Cardiovascular Institute are now drilling into all that 24x7 data using the Trusted Analytics Platform to explore associations between daily life and clinical findings.

It’s a new, big data approach to discovery, taking advantage of wearable devices, home monitoring devices and gateways, and a Big Data analytics platform. It allows scientists to shed light into blind spots like sleep quality to test associations and patterns in data never before available. We think information about the actual daily lives of patients is an untapped resource for a wide range of healthcare stakeholders, including patients themselves.