Feature | Information Technology | October 03, 2018 | By Inga Shugalo

The focus must remain on performance, convenience and safety

The alliance of the IoT, machine learning and cloud technology is at the service of healthcare organizations, ready to assist them in optimizing  the workflows.

The alliance of the IoT, machine learning and cloud technology is at the service of healthcare organizations, ready to assist them in optimizing the workflows.


One by one, medical software systems become more interconnected, robust and helpful. In particular, many efforts are put into enhancing examination and diagnosis processes to enable precise and well-timed decisions, which are key to ensuring appropriate care delivery and predictable patient outcomes.

Among others, the internet of things (IoT) comes into play in the form of smart medical devices and wearables, with the ability to collect varied and longitudinal patient-generated health data, also offering preliminary diagnosis options.

In radiology, the goal of the IoT is to support health specialists by bringing in comfortable and safe work conditions and help them manage patient flow. But is IoT safe enough to be used in clinical conditions? Let’s explore the potential use cases of IoT in radiology together with possible vulnerability concerns.

 

Let There Be Smart Light

The comfort of reading rooms is key for radiologists who spend most of the time there, reading up to 50 studies (1 – 1,000 images each) per day to notice even slight abnormalities. Suboptimal conditions in reading rooms can lead to musculoskeletal disorders and visual deterioration in health specialists, as well as harm their productivity.

Baltimore VA Medical Center evaluated the lighting in their reading rooms and found out that full on and off settings affected the performance of radiologists. The diagnostic accuracy went down by 14 percent compared with a balanced light setting.

The issue is that it can be challenging to balance the lighting manually when radiologists read images in different planes and modalities. They would have to stand up each time to fix the lights, which is good for the spine and blood circulation, but may distract the specialist from their current task, making them recheck themselves or waste some time on gaining their focus back.

This is where the IoT can make a difference. Using the automatic IoT-enabled sensor, the smart lighting system for radiology can adjust the reading room light brightness according to the World Health Organization (WHO) standards, customizing settings for particular modalities and specific preferences of each health specialist.

The lighting system can be connected with the radiologist’s software for viewing medical scans and create rules for it. If a specialist chooses a specific light setting for studying CT scans of the chest with contrast, their software will show only the relevant selection of scans. Alternatively, picking any modality or scan in the software without presetting the light will trigger the system to adjust the brightness to the displayed image.

 

Next-level Radiation Control

Radiation exposure is a top concern for medical imaging that involves ionizing radiation. Each new generation of scanning devices comes with improvements that allow reducing the needed radiation dose for taking the image. Still, any dose of radiation is potentially harmful to both the patient’s and the specialist’s health, which is why providers need to continuously monitor radiation levels in scanning rooms.

While health specialists working with radiation-emitting equipment wear dosimeters, they usually can’t track radiation levels in real time, especially without human assistance. An IoT-enabled dosimeter can be used for each radiographer and radiologist during the procedure to monitor the radiation and enable control over yearly exposure limits. This device will be able to transfer the readings straight to the EHR as well as the specialist’s mobile app to ensure real-time radiation dose tracking.

 

Workflows Infused With Machine Intelligence

The workflows in radiology are built around medical scanning devices, their availability and downtimes. It can be challenging to maneuver around and spread the load evenly to balance out the busy days and occasional gaps in patient flow.

The alliance of the IoT, machine learning and cloud technology is at the service of healthcare organizations, ready to assist them in optimizing the workflows. The IoT sensors can detect even slight fluctuations in device performance or surrounding conditions. The collected data then gets fed to the machine learning algorithms, enabling them to predict possible failures or malfunctions.

Here’s where the cloud comes in handy, aggregating the data on standalone MRI, CT, ultrasound, X-ray and other scanning machines across the facility and enabling 360 degree views at their current statuses.

As providers see the full picture of the current state of all devices, they will be able to optimize the workload, prevent outages and reduce downtimes. Instead of dealing with the sudden breakdowns and messed up patient examination schedules, they can plan and execute quick checks or fixes in the most convenient time slots.

 

We Might Not Be Ready for the Takeoff Just Yet

The IoT is quite new to the healthcare realm, and there are multiple concerns about connecting any piece of medical equipment to the internet. These concerns are mostly rooted in the absence of standards for particular APIs to manage IoT devices and ensure their efficient and secure communication with each other.

Without the standardized API, we can’t eliminate the possibility for hackers to exploit the backdoor connection and either get unauthorized access to PHI or gain control over the device. While the light-controlling device wouldn’t cause many troubles if hacked into, compromised medical scanners and dosimeters can cause significant damage.

 

The Aftermath

The most appealing idea of infusing the IoT into radiology lies in automating the routine processes and enabling radiographers and radiologists to do their job without distractions or safety concerns. However, the technology itself poses certain safety concerns, because there’s no valid procedure for its secure implementation in healthcare just yet. We are optimistic, but aren’t expecting a fast-paced and widespread adoption of the IoT in radiology — not until the commonly accepted security standards are in place.

 

Inga Shugalo is a healthcare industry analyst at Itransition, a custom software development company headquartered in Denver. She focuses on healthcare IT, highlighting the industry challenges and technology solutions that tackle them. Her articles explore diagnostic potential of healthcare IoT, opportunities of precision medicine, robotics and
VR in healthcare.

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