At the Cutting Edge of Healthcare: IoT Data in Preventative Care

Efficient clinical workflows, safer patient experiences, and better predictive care – IoT at the Edge is a key strategy as healthcare organizations focus on patient-centered care and digital transformation. With Edge and IoT devices generating enormous quantities of data from physician-patient encounters and wearables, health leaders are identifying opportunities to leverage distributed analytics to derive actionable insights from IoT devices at the Edge.

We’ve moved well beyond the lean operations and financial use cases introduced a decade ago. Instead, envision a greater goal: moving from disease management to disease prevention; that’s the power of IoT devices at the healthcare Edge. It's enhanced productivity. It's improved resource utilization. All working together to quickly and safely step-down patients, maximizing value-based care models.

While much of IoT moves through the realm of big data, Edge analytics focuses on “small data” – individual personal, physical, longitudinal data points – all aggregated to provide the opportunity for instantaneous insights. Distributed analytics unlocks healthcare Edge and IoT data to see beyond episodic patient visits, creating a continuous real-time patient record – 24/7/365 – and shifting from reactive to proactive care.

Edge gateways reduce transfer and storage costs of large data sets by locally processing, buffering, filtering, and securing data before transmitting to the cloud. Using analytics as an aggregator and filter at the Edge can result in the following:

• Improving patient safety and monitoring recovery through computer vision solutions in the hospital and at home
• Expanding chronic disease management and preventative medicine with sensors that can alert providers to clinically meaningful changes and recommend early intervention
• Enhancing precision medicine research by integrating wearables into clinical trials or automatically removing PHI from data to allow data aggregation across patient populations
• Managing pharmaceuticals and improving drug supply chain safety by tracking medication from manufacture to consumption

The Edge revolution is also affecting the healthcare video surveillance and monitoring world. Real-time video analytics, also known as computer vision, is when a camera is paired with sensors and powerful machine learning capabilities — enabling the camera to truly “see,” identify, and process images in the same way that the human eye does. Computer vision solutions automate data analysis and pattern recognition, identify anomalies, and trigger responses. Healthcare organizations can leverage these functionalities for visitor and staff safety, patient sitters, and pain monitoring. The solution uses a Software Defined Data Center (SDDC) approach to integrate compute, storage, networking, and virtualization resources to help improve system orchestration and lower total cost of ownership.

Optimized analytics help patients suffering from chronic diseases leverage telehealth opportunities, such as virtual health consultations for condition assessments and remote monitoring. These capabilities help keep high-utilization, high-risk patients managing these chronic conditions out of the emergency department and controlling overall healthcare costs.

AI advancements also help to aggregate “small data” points, leading to learnings that can be used to update the relevant algorithms. This allows for continuous improvement in pattern recognition capabilities, automating the ability to flag abnormalities in order to trigger a behavior or alarm. We’re moving toward a world where real-time AI learning occurs as the patient (and their data) interacts with the healthcare organization, bringing with it the promise of improved safety and treatment efficacy. All these data points can then be analyzed retrospectively across the entire patient population to start delivering on the promises of value-based care.

As we look at the possibilities, the question isn't, "What can we do with IoT?” it’s “How do we gain insights from this critical data?” Healthcare organizations can start by considering how to efficiently deploy analytics at the Edge, securely transmit the processed signals to the data center, and then appropriately deliver it to one of the multiple cloud locations based on workload requirements.

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About Dell Technologies

Dell Technologies provides solutions to help healthcare organizations realize their digital transformation – from the point of care to the data center to the cloud. Our solutions provide transformative and essential infrastructure that make the future of healthcare real – including healthcare Edge and IoT solutions. Visit us at www.DellTechnologies.com/Healthcare and read our latest whitepaper: “Evolving from Chronic Disease Management to Preventative Care: Healthcare IoT Data at the Edge”