Internet of Medical Things And Changes It Brings to Healthcare
The world of information technology is advancing rapidly, contributing to MedTech innovation and influencing the development of a greater number of connected medical devices that are used to generate, accumulate, send, and analyze huge volumes of healthcare data. This data is an inevitable part of a cohesive ecosystem known as the Internet of Medical Things (IoMT).
We’ve already addressed the subject of IoMT in our article devoted to the role of Big Data in healthcare. This post will be a deeper dive into the essence of IoMT systems, their components, and major use cases. Let’s get started.
What is IoMT: Key factors influencing IoMT adoption
The Internet of Medical Things (IoMT) is a subset of the Internet of Things (IoT), often referred to as healthcare IoT. It is an interconnected structure of medical devices, software applications, and healthcare systems and services that transmit real-time data via networking technologies. An example of such a “thing” within the IoMT system can be a heart rate monitor that sends patients’ data to the hospital’s cloud software where a physician can review it right away.
IoMT adoption trends and factors behind its popularity. Statistics source: Healthcare IT News
IoMT market value is projected to reach $158.1 billion by 2022, according to the 2018 report by Deloitte. That’s three times as much as it was in 2017. Nearly 60 percent of all global healthcare organizations have already implemented the Internet of Things one way or another. It is assumed that another 27 percent are thinking of adopting the technology shortly. But what factors are driving the rapid growth of the IoMT market?
The growing need for remote patient monitoring. This factor is caused by two trends: the rise in chronic diseases (particularly asthma, diabetes, and cancer) and the aging population. According to the report presented by the United Nations, 2.1 billion people on Earth will be elderly by 2050. Since seniors tend to have more issues with their health, IoMT devices coordinated with software applications on phones can be used to ensure safety and alert on emergency events.
High healthcare costs. Healthcare is becoming more expensive and at times even unaffordable. IoMT solutions have what it takes to make the industry services cheaper by preventing serious diseases, eliminating the need of personal checkups, providing affordable means of continuous health monitoring, and much more. Analysts say that the adoption of IoMT can help the US healthcare industry save $300 billion annually in expenses.
Increased consumer health awareness. With the spread of the COVID-19 pandemic, more people have started treating their health more carefully, which resulted in the growing demand for efficient eHealth approaches and health devices to monitor vitals including body temperature, heartbeat, cholesterol levels, and sleep patterns to name a few.
With this in mind, let’s move to explaining how IoMT systems work.
IoMT ecosystem components
Much like IoT, the Internet of Medical Things systems consist of the following architecture layers:
- the perception layer, represented by the range of smart medical devices collecting all kinds of health data;
- the connectivity layer, responsible for the data transmission from the perception layer to the cloud (and vice versa) through connectivity technologies ‒ networks and gateways;
- the processing layer, presented by cloud middleware or IoT platforms to store and manage data; and
- the application layer, providing end users with data analytics, reporting, and device control opportunities through software solutions.
The building blocks of IoMT systems
Our dedicated article will provide you with more details on IoT architecture layers and components. As for now, we’ll walk you through the building blocks of IoMT systems to fill you in on how medical data is collected, sent, processed, and managed.
Smart medical devices to generate and collect data
According to the World Health Organization, “… there are an estimated 2 million different kinds of medical devices on the world market, categorized into more than 7000 generic devices groups.”
These devices come in different forms and sizes: from home monitoring gadgets to insulin pumps to pulse oximeters. All of these solutions fall into the following groups:
The major groups of IoMT devices
Point-of-care devices are a broad array of diagnostic tools aimed at producing results outside of laboratory settings. They are commonly used at the doctor’s office or at home to collect and analyze specimens such as blood, saliva, skin cells, etc.
Smart pills, also known as smart drugs or digital pills, are small electronic devices that come in the form of pharmaceutical capsules containing ingestible sensors. Such smart pills may perform an array of functions such as monitoring important well-being indicators (local pH, temperature, blood pressure), delivering drugs to a targeted area, imaging for effective diagnosis of gastrointestinal disorders, etc.
Personal emergency response systems (PERS), sometimes known as medical alert systems, are special medical devices used to call for help when an emergency event occurs via a help button. PERSs can be helpful for those who are limited in their mobility and require emergency medical care, the elderly for example.
Clinical-scale wearables are the IoT devices and supporting platforms that are certified and/or approved for use by respective regulatory and health authorities, for example, the FDA (US Food and Drug Administration). The devices in this category are commonly used at home or in clinics following the prescription or advice of a physician. Their focus is mainly to improve chronic conditions and diseases.
Consumer-scale wearables are different kinds of wearables for tracking key indicators of personal wellness or fitness. They contain built-in sensors that collect and transmit the data every time a user does physical activities. Although sometimes such gadgets may be used for specific health applications, most of them aren’t regulated by health authorities.
In-hospital devices and monitors range from huge machines such as an MRI or CT scanners to devices with smart apps that help with patient monitoring, staff and supply management, etc.
All devices by their nature are quite limited in terms of processing power and storage capacity. That’s why the use of cloud services is needed. So how does the transfer happen?
Networking technologies to send data
The transmission of data between the physical layer represented by the above-listed medical devices and the cloud happens through networking technologies such as:
- Wi-Fi (wireless networking technology that operates within a small area and allow devices to interface the Internet);
- ZigBee (wireless low power networking technology with small data-sharing capability);
- Bluetooth Low Energy or BLE (wireless technology used for short-range communication between devices);
- Near Field Communications or NFC (a set of communication protocols bridging devices over a distance of 4 inches or less); and
- Local Area Network or LAN, etc.
Message Queue Telemetry Transport or MQTT protocols are mostly used within IoMT systems for seamless data sharing between devices and with the cloud.
IoT platforms to store, process, and manage data
And here comes the heart and soul of the IoMT systems ‒ the processing layer also known as the middleware layer. Data gets to the cloud IoT platforms where it is processed, stored, and becomes available for consumption by third-party applications via APIs. Modern platforms employ many technologies such as cloud computing, databases, and big data processing modules.
To carry out this layer’s tasks, consider the heavyweights who have solutions tailored for IoMT and take care of compliance with HIPAA — the regulation aiming at protecting personal health information (PHI).
AWS IoT platform has a lot of services to offer for building an IoMT system, from AWS Cloud Trail and AmazonCloudWatch to manage compliance with regulatory requirements to IoT Greengrass that enables edge computing. In edge computing, data is processed locally, on medical devices deployed in the hospital network, so doctors get analytical results in near real-time.
Microsoft Azure IoT among other things provides the special IoT connector for FHIR. It helps securely extract biometrics data from medical devices and map it into FHIR — the main data standard in healthcare — before loading on a FHIR server.
Google Cloud IoT also grants all necessary components to design a HIPAA-compliant IoMT infrastructure, including Cloud Healthcare API that supports FHIR and DICOM (medical imaging) standards of data exchange. In 2019, Google revealed its high ambitions in the healthcare IoT space by acquiring Fitbit — the fifth largest wearable company with over 28 million users.
Software applications to work with data
The final layer is represented by applications that support different decision-making processes based on data. Due to the unique needs of each IoMT system, software solutions also range drastically both in complexity and function. More often than not, the need for custom app development arises. Applications can be built on top of the IoT platforms that provide the required infrastructure and tools or integrated with the middleware via APIs.
Real-life IoMT use cases
Along with the transportation and logistics industry that is rapidly adopting IoT for more effective fleet management, healthcare isn’t lagging behind with the number of IoT-enabled medical devices. Let’s take a look at when and where IoMT systems can be applied in real life.
Fall detection and prevention
Seniors are more prone to falling and getting fall-related injuries such as head trauma or a broken hip. There are quite a few IoMT solutions designed specifically to handle this issue. For example, the Tango smart belt from Active Protective has sensors to indicate hip-impacting falls and provides timely protection. The belt is synced with the proprietary software app, so it can notify clinic staff or caregivers of the event of the fall as well as to measure and display mobility data on a phone or computer.
Apple Watch fall alert system dashboard. Source: Apple
Apple Watch also has an integrated fall detection system capable of identifying hard fall events and displaying an alert. If a person doesn’t tap “I’m OK” for a minute, the system notifies emergency services and emergency contacts.
Capsule endoscopy is a breakthrough in gastroenterology examinations. Once swallowed, small pill-sized digital devices with a video camera take pictures of the human GI tract and send reports to a wearable digital device through a sensor. The info can then be easily moved to EHR systems.
CapsoCam Plus smart pill specifications. Source: CapsoVision
Let’s take CapsoCam Plus for example. Their smart pill for endoscopy examination procedures provides a full 360º panoramic lateral view in high resolution and connects to a software system that is compatible with both Mac and Windows OSs.
There’s a variety of sleep trackers and software applications to help monitor sleep habits, analyze key metrics, and improve the quality of rest. For instance, Apple and Samsung smartwatches are equipped with sensors that track heart rate and respiratory rate. This data draws an approximate picture of sleep duration, depth, and stages. As devices are synced with a smartphone, the data is available for in-depth analytics and can be shared with a physician.
We, at AltexSoft, have experience in developing sleep monitoring software. Our team helped a US-based sleep technology company build an app that monitors and records snoring and bruxism with sound recognition algorithms at its core.
Hospital asset management and equipment maintenance
The IoMT brings the concept of smart hospitals to life. With the help of trackers attached to medical equipment, healthcare facilities can receive signals on the whereabouts of equipment such as a defibrillator to quickly deliver it to the destination it’s needed like an emergency room. Or they can get data on when supplies are running low to refill them.
NHS Highland’s Caithness General Hospital in Wick has started a trial medical bed maintenance system. All the beds are equipped with sensors that allow for monitoring information about the location of the beds and maintenance records. Each bed has a Bluetooth-compatible tag that transfers real-time data to a central dashboard through a network.
Diabetes data monitoring and reporting
There are continuous glucose monitoring systems, like Dexcom that help people with type 2 diabetes control their condition and glucose levels without fingersticks.
Dexcom G6 CGM System for diabetes data monitoring. Source: Dexcom
The system consists of a wearable device with a water-resistant sensor placed under the skin. This sensor monitors interstitial fluid and wirelessly sends glucose metrics to a receiver, smartphone, or smartwatch every five minutes. The company also provides special software for diabetes data management and reporting.
IoMT implementation: challenges and ways to address them
While IoMT is beneficial in lots of ways, it still entails some implementation challenges you should be aware of. Below are the key things to consider if you are on the way to bringing the IoMT system to life.
Ensure security of sensitive medical data
The most significant risk patients, doctors, and device manufacturers face is falling victim to data breaches. Though connectivity in healthcare is beneficial in lots of ways, it increases security vulnerabilities. In 2020, healthcare cyberattacks doubled, costing the industry millions of dollars.
Ways to tackle the problem: While healthcare organizations can’t get rid of cybersecurity threats completely, they can mitigate the risks by establishing real-time data monitoring, performing cyber-threat modeling and analysis, and working with high-level secure networking technologies. AI and machine learning is also a smart move for those who want to predict any emerging cyber attacks and take proactive steps.
Take care of regulatory compliance
Those involved in medical technology development need to meet compliance requirements for HIPAA, FDA, and other regulatory mandates. While it is a good thing in terms of security, the regulatory landscape isn’t stable, which may be a bottleneck for producing or updating medical devices and software for them.
Ways to tackle the problem: Proactivity is the way to go. Any checks on the regulatory compliance of the technology stack should be done at the planning stage. This can save tons of time and reduce headaches throughout the implementation stages. Say, you’re picking an IoT platform to connect, make sure it offers solutions to comply with existing regulatory requirements.
Interoperability determines to what extent devices and systems can interchange and interpret data. Patients and doctors utilize different medical devices to collect different kinds of health data, which results in data silos. The lack of interoperability between individual systems remains an issue that must be solved to fully unlock the potential of health information.
Ways to tackle the problem: Interoperability between connected medical devices and software systems can be approached through unified open APIs for data exchange and implementation of uniform messaging standards for healthcare data such as FHIR.
Consider high implementation costs
In broad terms, IoMT targets the reduction of healthcare costs but the implementation of such systems is quite expensive. Things like hardware purchases, software development, storage, and maintenance require substantial initial investment, which may hinder or slow down IoMT integration.
Ways to tackle the problem: They say, only bite off as much as you can chew and swallow. It’s a good piece of advice for people starting their IoMT projects. Before implementation, it’s sensible to do some research, compare the prices for hardware and software needed, and map out an achievable strategy.
AI-powered future of IoMT
From everything mentioned, it’s clear that IoMT has a lot in store to greatly benefit the healthcare industry. What’s more, the already smart enough devices will keep evolving and get more predictive with the help of artificial intelligence (AI) and machine learning (ML) technologies.
Data generated by IoMT devices can be used for building ML-driven systems capable of detecting blood infections, heart diseases, and even certain types of cancer. And this is beyond the wishful thinking stage.
Have you heard of IBM’s Watson? It’s an AI-powered supercomputer that accurately diagnosed a rare form of leukemia in a patient in just 10 minutes by analyzing the dataset consisting of millions of oncology papers and cross-referencing it with the patient’s genetic data. This would have taken weeks for human scientists to accomplish.
So, things like instant diagnosis and smart hospitals are decidedly not futuristic. The use of IoMT in tandem with AI has the potential to bring even more powerful changes to the healthcare industry.