How Edge Computing Is Driving Advancements in Healthcare Analytics
This piece explores how edge AI enhances real-time imaging and clinician support, meets data privacy requirements, and brings analytics closer to patients and providers. Discover the synergy between cloud and edge computing in optimizing data management, and see how edge technologies enable advanced clinical applications, from AI-powered imaging to remote care solutions. This piece delves into the transformative potential of edge computing in improving patient outcomes and operational efficiency.
Read the full article from Intel here.
Edge Computing Drives Healthcare Advances
Modern health systems, hospitals, and providers are deploying new tools and building exciting new care models to better serve patients. These strategies focus on clinical decision support (CDS), helping provide clinicians with timely, filtered, and patient-specific information they can use to enhance care.
Over the last few years, this pursuit has seen a growing number of medical devices introduced to healthcare environments. These range from tablets and wearables to health monitors and artificial intelligence (AI)-powered imaging systems.
Wearables can give clinicians a timely status of key patient vitals such as heart rate and blood pressure, alerting medical staff to issues before they become problems. Health monitors can aid remote care by collecting patient data and triggering actions based on the results—for example, monitoring blood glucose levels and sending that information to a companion device such as an insulin pump to dispense the insulin. AI-powered imaging models can detect potential concerns in X-rays, prioritizing those images for radiologist or physician review.
The potential of these emerging innovations is profound, leading to better clinician workflows, lower costs, and improved patient care. But these edge devices have something else in common: they all generate data.
As a result, healthcare systems and providers must decide how to manage and make the best use of these unprecedented volumes of data. With bandwidth expense, access, and privacy in mind, what data should be sent to the cloud and what data is better managed locally?
Edge computing brings data processing, analytics, and storage closer to the source of data generation—for example, an on-premise server at a hospital or a mobile device at a patient’s home. Edge computing works as a complement to the cloud, allowing IT decision-makers to choose where to best place workloads along the compute spectrum. This strategy can help health systems optimize the collection, storage, and analysis of data—which, for the average hospital, has reached 50 petabytes each year.1
Combining Cloud and Edge Computing
In recent years, health systems and providers largely relied on the cloud for storing, analyzing, and processing data. With help from Intel, the health and life sciences industry is now forging a new data management strategy that strategically employs the cloud or edge computing based on needs, costs, and benefits. For example, it might make sense to limit the transmission of readings from patient wearables to the cloud, sending only summary totals reported at a prescribed interval.
Conversely, for systems that capture larger operational or financial data, the cloud will likely remain the preferred path as a means for forecasting organization-wide costs, purchasing and billing schedules, and supply-chain demands.
In addition, keeping personal or sensitive data on premise enables health systems and providers to comply with strict data handling and privacy requirements. This includes those outlined in the Health Insurance Portability and Accountability Act of 1996 (HIPAA). HIPAA now also includes the Federal privacy protections for individually identifiable health information as mandated by Congress in response to proliferating digital technology.
Remote Care
Companies are developing a remote patient monitoring solution that enables access to health data by connecting a wide array of medical and non-medical devices.
Platforms for remote patient monitoring and patient care services, chronic disease management, and patient health programs. These platforms are designed to help enable continuous care for patients and elderly at home while helping minimize costs.
The benefits from edge computing-based remote care could be significant. A 2015 study found a 50 percent reduction in 30-day readmissions and up to a 19 percent decrease in 180-day readmission among patients who received remote care.4 The bottom line stands to benefit as well with estimates suggesting that telemedicine alone could help cut U.S. employer healthcare costs by as much as $6 billion annually.5
Edge Analytics in Healthcare Powers Improved Patient Outcomes
It is a new world for health systems and providers, one driven and enabled by a proliferation of exciting new mobile and point-of-care devices. Companies are developing new ways to help healthcare providers harness the power of these edge devices, as well as the provider’s existing cloud strategy, to enhance CDS and care.
McKinsey estimates current healthcare data could help lead to more than $300 billion annually in reduced costs alone.1 Edge computing and edge analytics will only grow in their impact as they bring new opportunities to grow operational, clinical, and financial value across the care continuum.
