By IQnewswire 
The increasing utilization of IoT in healthcare is significantly changing the landscape of how medical care is delivered and managed. Whether through wearable devices that are constantly measuring patient vitals, or through smart sensors embedded in hospital equipment, the volume of information that is being generated from the Internet of Medical Things (IoMT) is astonishing. These devices obtain very important information- heart rates, glucose levels, oxygen saturation, and activity information; providing clinicians with an unprecedented picture of patient health.
Nevertheless, the practice of sending all of this information to a centralized cloud for processing would be an inefficient process for time sensitive use cases. Network latency, bandwidth concerns, and connectivity issues can create substantial delays in critical care situations. Edge computing solves this issue by processing information closer to the patient, and more often at or near the point in which the information is created.
In an edge-enabled healthcare architecture, information is processed in near real-time, and it does not require exclusive reliance on distant data centers. This transition from cloud-based healthcare computing to edge-enabled healthcare has the potential of creating new levels of responsiveness, reliability, and privacy in care delivery. As IoT in healthcare matures, edge computing is becoming the primary enabler to be able to deliver safe, fast, and personalized care.
Core Benefits of Edge Computing in Healthcare
Reducing Latency for Critical Care
Latency is an important problem when there could be milliseconds between life and death. In cases such as ICUs, surgical rooms, and emergency care, edge computing allows patient monitoring devices to analyze and alert people about abnormal readings instantly, rather than having to wait for the data to route through the cloud.
Increased reliability and autonomy
Internet connectivity cannot be assumed in all scenarios. A rural clinic, emergency response unit, or even a hospital with limited bandwidth may experience downtime or slow connectivity, but edge-enabled systems will autonomously continue to operate, process, and store important data locally until a data connection can be reinstated.
Bandwidth optimization and cost benefits
Edge computing will process data locally to filter, aggregate, and manage operational data and make it available for continued analysis instead of sending incremental data points to the cloud. Less data sent to the cloud means less network congestion and reduced costs associated with storing and sending all point-of-week data to the cloud.
Edge Computing Use Cases for Improved Patient Outcomes
Real-Time Patient Monitoring
Wearable sensors and bedside monitors create ongoing streams of data regarding the patient’s health status. Edge computing devices can:
- Detects arrhythmias in ECG readings.
- Identify dangerous trends in glucose monitoring.
For example, an interconnected heart monitor will identify irregular cardiac rhythms and send immediate notifications to medical staff on site using local analytics, without using servers located at a distance.
Telemedicine and Remote Care
Low-latency video conferencing and point-of-care diagnostics are critical for virtual visit engagement, especially in under-resourced or remote communities. With edge computing, video compression, diagnostics data, and sensor readings are processed locally, with low latency, and care flows efficiently.
AI-Assisted Diagnostics and Imaging
Medical imaging results in exceedingly large file sizes, an MRI or CT scan can be hundreds of megabytes. Processing imaging locally at the edge of the network significantly reduces the wait time. When combined with AI Development Services, hospitals can then run deep learning models to detect tumors or identify fractures in real-time, providing real-time diagnostic support to clinicians.
Smart Hospitals and Management Efficiency
Hospitals powered with edge-supported applications will provide additional operational efficiencies by tracking whether equipment is being used, when staff are deployed, and ensuring patient flow is managed effectively and safely. For example, edge devices that are attached to infusion pumps can track availability, and maintenance needs, in real time, creating new levels of efficiency and lowering downtime.
Security and Compliance at the Edge
Data Localization and Privacy
Sensitive PHI (Protected Health Information) can be kept within the local network of the hospital instead of being transmitted to third-party cloud environments. Storing data locally minimizes the risk of a data breach through a data transfer and maximizes control of who has access to the information.
HIPAA and GDPR Compliance
Edge architectures make compliance easier by reducing unnecessary cross-border transfers of patient data. This is important for complying with HIPAA in the U.S. and GDPR in the EU.
Securing the Distributed Network
Decreasing reliance on centralized computing resources adds redundancy, but it also expands the attack surface. Remediation strategies include:
– End-to-end encryption.
– Zero-trust network access.
– Regularly applying security patches and authenticating devices.
Challenges and Future Outlook
Implementation Challenges
The integration of edge computing within healthcare settings necessitates an initial investment in hardware, training, and tying into legacy IT systems, plus existing operational complexities around legacy medical devices and hospital information systems.
The Synergies with 5G
5G networks complement edge computing capabilities by delivering ultra-low latency and high bandwidth to support real-time transfer of complex datasets, such as surgical videos, or high-tech digital imaging, for example.
The Future: Predictive Medicine and Autonomous Healthcare
The intersection of edge computing and AI Development will likely enable predictive healthcare models, including:
- Being able to predict patient deterioration hours before the symptoms appear
- Devices could operate in automated mode, adjust insulin delivery as needed
Over the long-term, it is conceivable autonomous medical systems could react to health conditions independently, powered through a distributed intelligent edge network.
Final Thoughts
Edge computing is quickly becoming a key element of IoT-enabled healthcare systems to deliver care faster, safer, and in a more scalable manner. Healthcare organizations that process data closer to the point of collection will be able to reduce latency, secure patient privacy, and lower costs while improving patient outcomes.
For organizations that want to take advantage of IoT and edge systems, it is important to work with a trusted Healthcare Software Development Company so they can design secure, compliant, and integrated solutions that adhere to the medical standards of care. With the help of Healthcare Software Development service providers, healthcare organizations will be able to future-proof their design and architecture, fully utilize the benefits of IoT and edge computing, and transition to predictive, personalized, and autonomous care.