Report: the quantified self movement and predictive analytics in healthcare

By Roberta Katz, Director, Healthcare-Life Sciences, EMC

As part of the information generation our technology-driven world is dramatically changing our lives, impacting our personal interactions, business transactions, and the way we consume information. We’re always connected, using more types of devices, accessing data anywhere, anytime. When it comes to caring for ourselves and others, this digital transformation is driving us to act as both patients and consumers of healthcare information.

Smart technologies, like wearable devices and smart home devices are driving the “Quantified Self Movement,” arming us, as consumers, with personalized data to make more informed decisions about our lifestyles. In this “always on” world, our expectations for healthcare are also shifting from a focus on a single patient care episode to an overall patient lifecycle.

In the current accountable care environment, where electronic health record documentation is being prioritized, this new realm of patient generated data can build on a caregiver’s clinical expertise and augment hospital protocols. Wearables can also create positive impacts on the provider-patient relationship, engage patients and their families during a discussion.

In many cases, we are still calling our doctor’s office to schedule an appointment, to better manage a chronic condition, or have a specific health question. With the use of sensors, we can review our own data in real-time, from the number of steps we are taking, cardio output, sleep cycles, blood pressure, and even mood, to become an “empowered” patient.

As a “smart” patient, I can begin my day reviewing the previous night’s sleep on my wearable device, receive motivation to get moving, access my phone for medication time and dosage, gain a list of prescribed activities for the day, and even receive food recipes targeted to my particular health profile based on the food in my smart refrigerator. Let’s say I am trying to better manage a chronic condition such as diabetes, I can now download data directly from my insulin meter to my phone, respond to medication reminders, integrate that information with food and lifestyle information to also manage my weight and cholesterol, and then, share that information with my caregiver to make any adjustments on a recurring basis.

But, how can all of this information being generated by the Quantified Self Movement be acted upon and applied for preventative health and disease management? And, how do healthcare providers prepare for this new wave of data to help ingest clinically relevant information into the clinical setting to deliver higher quality, cost-effective patient care?

The stage is already set for FutureCare as healthcare leaders start incorporating this growing patient-generated data into their healthcare ecosystem to move forward accountable care initiatives. The next-generation of predictive analytics is at the forefront as HHS Medicare payments shift from volume-based to value-based reimbursement models, moving to 30% by the end of 2016 and 50% by the end of 2018.

How is all of this possible? Through big data analytics and a data lake. Healthcare organizations are advancing their big data strategies by creating an ecosystem of data centered on the patient to gain additional insights on best methods of care and disease management with the assistance of automated tools to help aggregate, manage, filter, and analyze useful, meaningful data. They are making the journey to a modern data center, deploying the capabilities of a hybrid cloud and data lakes – which deliver an effective, agile framework to make connections between raw data and turn it into actionable insight.  This IT infrastructure incorporates diverse internal and trusted external data sources, including patient generated data from smart devices driving the Quantified Self Movement, the EMR, PACS, payers, public health databases, genomic research centers, and more.

With the improved ability to derive clinical value through the use of advanced predictive analytics, accountable care initiatives can be accelerated with new data science capabilities to uncover trends, patterns, relationships, correlations, and discoveries for measurable clinical impacts.  And, with the patient’s ability to make more informed decisions and have meaningful dialogue with their caregivers providers as a result of the data gathered from their smart devices, patients and providers can work hand in hand to enhance the patient experience, improve clinical outcomes, and live a healthier, longer life.


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