by Leo Petersen-Khmelnitski

This is the third, concluding part in the series on Internet of Medical Things (IoMT). It covers the main challenges to wide IoMT adoption, as well as the main areas of IoMT adoption in healthcare.

There are quite a few challenges on the way to wide adoption IoMT technologies in healthcare. They may be grouped as follows:

Data security threats

Healthcare data is highly susceptible to breaches by cyber attacks. Adding the IoMT data to the existing pool of clinically relevant medical data significantly increases the risk of exposure. As more devices become interconnected to one another and other systems, there is an increased risk of data breaches.

Interoperability of data

Data collected from the various IoMT devices is of no use if it cannot be collated and computed to give meaningful and clinically relevant results. In order to utilise the potential benefits of IoMT to the fullest, it is imperative that all IoMT devices are interoperable with one another and allow for relaying of the data to everyone using the technology including the providers and the payers.

Regulatory challenges

Clinical grade medical devices need approval and clearance from national regulators  to be able to launch in the market. IomT devices present new challenges for the regulatory authorities and legislators as well. 

High infrastructure costs

The cost of the hardware, dedicated IoMT IT infrastructure, cloud computing and creating an app that’s consumer facing result in a high initial investment. While the eventual return on investments is definitive, the high infrastructure costs act as a barrier to IoMT.

Standardisation issues

With a number of vendors and manufacturers of medical devices, all looking to achieve scalability and reduce the time to market of their product, standardisation of the IoMT devices becomes an issue. Lack of standardisation affects interoperability of medical devices reducing the overall effectiveness of IoMT. The industry alliances and coalitions are working to improve the problem, and governmental support to the industry is strong.

Strain on Existing Networks

Building the IoMT infrastructure does not mean bringing IoMT devices into the hospital and logging them into the facility wifi. Many existing hospital networks are neither robust enough nor secure enough to handle a fully-implemented IoMT system.

Scale

Scaling is a key challenge for medtech. It is about ensuring that health care organisations, clinicians and patients understand the added-value of connected medical devices and use them at scale to drive better economics and patient outcomes.

Maintaining trust

As medtech companies develop strategies and services based on the generation and transmission of patient data, they need to ensure they demonstrate clearly to patients, the public and health care professionals how their data is being used to reduce the risk of undermining the benefits that access to data can bring.

IoMT adoption

Areas of IoMT adoption, as well as major use cases are summarised below.  Researchers differ between three areas where medical devices have been adoption: in hospitals and clinics, at home, and on body. Patient monitoring is not the only application IoMT finds in hospitals and clinics. MRIs, X-ray machines, CT scanners, and other equipment can be remotely monitored for performance issues. Long before hospital staff notices a problem, the manufacturer or service vendor can detect issues that need to be corrected. GE, Siemens, Philips, and other companies use IoMT for remote diagnostics, predictive maintenance, and performance upgrades to their imaging products.

In home, medical connectivity technology, also referred to as telemedicine, extends healthcare services beyond the walls of the hospital. Remote Patient Monitoring  enables many patients suffering from chronic disease to avoid frequent visits to the doctor. Portable RTM devices can monitor patients’ heart activity and glucose levels, and automatically alert the doctor when there is a problem.

Virtual home assistants are valuable additions to the home for many elderly patients. These intelligent devices interact with the patient, remind them to take medications, and can be accessed remotely by family and physicians.

On body: advances in biosensor technology make possible wearable smart devices that monitor the user’s health. Embedded in apparel, attached to the skin, or implanted, on-the-body IoMT sensors give patients freedom, while maintaining close watch on their health conditions.

The analysis of current adoption of IoMT among major use cases demonstrates in which situations medical devices are used already:

Adhering to Doctor’s Orders

While you might think that IoMT would help diagnose patients, currently the biggest use and impact of IoMT is to ensure adherence to doctor’s orders. IoMT isn’t intended to replace healthcare providers but to provide them with the data gathered from devices for better diagnoses and treatment plans as well as to reduce inefficiencies and waste in the healthcare system. Healthcare facilities also currently use the Internet of Things to help with workflow optimisation, inventory management and medical device integration.

A connected medical device provides objective reporting of actual activity, whereas without its reporting providers must rely on subjective patient reports to detail how they feel. Similarly, IoMT devices help to monitor patient behavior and activity away from the office, so the provider will have actual data to refer to regarding compliance to patient therapy recommendations and what transpires after a patient leaves a medical facility.

Diagnostics

How can medical IoT devices improve diagnostics? Devices that track bodily metrics that could indicate medical conditions like diabetes and atrial fibrillation are becoming increasingly available. Key medical parameters like blood chemistry, blood pressure, brain activity and pain levels can be gathered on a continuous basis.

Causal indicators can be closely tracked with the right targeted sensors, once disease proclivity or risk factor have been identified. Even the most recent version of Apple Watch 4 has been declared as a class 2 medical device, because of features like heart rhythm monitoring and fall detection.

Recuperation

Postoperative recovery time for patients is a significant part of the procedure cost, and minimising that is an essential element of cost reduction. This can be accomplished by using wearable sensors that assist with exercise, compliance and remote monitoring for issues that might result in revisions if not dealt with timely.

Sensors can track various critical metrics and alert caregivers to respond in time. Sensors combined with telemedicine make it even easier to help speed up recovery. Knowing what patients are doing in between visits can help speed up the recovery time for post-surgical procedures.

Chronic Care

Sensors that track bodily parameters are getting increasingly sophisticated with blood pressure, glucose levels, sweat and even tear analysis. The benefit is not only in terms of logistics but also in terms of the frequency of data capture as compared to standardised tests. Mobility sensors can help improve gait and form in case of chronic degenerative diseases like rheumatoid arthritis. Another category of IoMT device application is in the monitoring and response of patients to treatment compliance. In chronic care specifically, poor outcomes and extended recovery can be avoided by measurement and monitoring ideally suited to IoT devices.

Prophylactics

Devices that actively engage patients with guided exercise can help prevent injury that requires medical care and associated costs. For instance, range of motion of joints in the orthopedic space, or the alignment of posture to prevent cervical spondylosis are examples of how devices can help in prevention. Wearables, for instance, may prevent catastrophic falls for the elderly by checking their activity and noticing anything unusual that might cause loss of balance and a fall. Apple’s watch uses the inbuilt IMU (Inertial Measurement Unit) to identify a fall or likelihood of one. It can even be used for measuring tremors related to nervous system disorders like Parkinson’s disease.

Remote patient monitoring

Remote patient monitoring is the most common application of IoT devices for healthcare. IoT devices can automatically collect health metrics like heart rate, blood pressure, temperature, and more from patients who are not physically present in a healthcare facility, eliminating the need for patients to travel to the providers, or for patients to collect it themselves.

When an IoT device collects patient data, it forwards the data to a software application where healthcare professionals and/or patients can view it. Algorithms may be used to analyse the data in order to recommend treatments or generate alerts. For example, an IoT sensor that detects a patient’s unusually low heart rate may generate an alert so that healthcare professionals can intervene. A major challenge with remote patient monitoring devices is ensuring that the highly personal data that these IoT devices collect is secure and private.

Glucose monitoring

Glucose monitoring has traditionally been difficult. Not only is it inconvenient to have to check glucose levels and manually record results, but doing so reports a patient’s glucose levels only at the exact time the test is provided. If levels fluctuate widely, periodic testing may not be sufficient to detect a problem.

IoT devices can help address these challenges by providing continuous, automatic monitoring of glucose levels in patients. Glucose monitoring devices eliminate the need to keep records manually, and they can alert patients when glucose levels are problematic.

Heart-rate monitoring

Like glucose, monitoring heart rates can be challenging, even for patients who are present in healthcare facilities. Periodic heart rate checks don’t guard against rapid fluctuations in heart rates, and conventional devices for continuous cardiac monitoring used in hospitals require patients to be attached to wired machines constantly, impairing their mobility.

Today, a variety of small IoT devices are available for heart rate monitoring, freeing patients to move around as they like while ensuring that their hearts are monitored continuously. Guaranteeing ultra-accurate results remains somewhat of a challenge, but most modern devices can deliver accuracy rates of about 90 percent or better.

Hand hygiene monitoring

Traditionally, there hasn’t been a good way to ensure that providers and patients inside a healthcare facility washed their hands properly in order to minimise the risk of spreading contagion.

Today, many hospitals and other health care operations use IoT devices to remind people to sanitise their hands when they enter hospital rooms. The devices can even give instructions on how best to sanitise to mitigate a particular risk for a particular patient.

A major shortcoming is that these devices can only remind people to clean their hands; they can’t do it for them. Still, research suggests that these devices can reduce infection rates by more than 60 percent in hospitals.

Depression monitoring

Information about depression symptoms and patients’ general mood is another type of data that has traditionally been difficult to collect continuously. Healthcare providers might periodically ask patients how they are feeling, but were unable to anticipate sudden mood swings. “Mood-aware” IoT devices can address these challenges. By collecting and analysing data such as heart rate and blood pressure, devices can infer information about a patient’s mental state. Advanced IoT devices for mood monitoring can even track data such as the movement of a patient’s eyes.

Parkinson’s disease monitoring

In order to treat Parkinson’s patients most effectively, healthcare providers must be able to assess how the severity of their symptoms fluctuate through the day. 

IoT sensors promise to make this task much easier by continuously collecting data about Parkinson’s symptoms. At the same time, the devices give patients the freedom to go about their lives in their own homes, instead of having to spend extended periods in a hospital for observation.

Connected inhalers

Conditions such as asthma often involve attacks that come on suddenly, with little warning. IoT-connected inhalers can help patients by monitoring the frequency of attacks, as well as collecting data from the environment to help healthcare providers understand what triggered an attack.

In addition, connected inhalers can alert patients when they leave inhalers at home, placing them at risk of suffering an attack without their inhaler present, or when they use the inhaler improperly.

Ingestible sensors

Collecting data from inside the human body is typically a messy and highly disruptive affair. With ingestible sensors, it’s possible to collect information from digestive and other systems in a much less invasive way. They provide insights into stomach PH levels, for instance, or help pinpoint the source of internal bleeding.

These devices must be small enough to be swallowed easily. They must also be able to dissolve or pass through the human body cleanly on their own. Several companies are hard at work on ingestible sensors that meet these criteria.

Connected contact lenses

Smart contact lenses provide another opportunity for collecting healthcare data in a passive, non-intrusive way. They could also, incidentally, include microcameras that allow wearers effectively to take pictures with their eyes, which is probably why companies like Google have patented connected contact lenses. Whether they’re used to improve health outcomes or for other purposes, smart lenses promise to turn human eyes into a powerful tool for digital interactions.

Robotic surgery

By deploying small Internet-connected robots inside the human body, surgeons can perform complex procedures that would be difficult to manage using human hands. At the same time, robotic surgeries performed by small IoT devices can reduce the size of incisions required to perform surgery, leading to a less invasive process, and faster healing for patients. These devices must be small enough and reliable enough to perform surgeries with minimal disruption. They must also be able to interpret complex conditions inside bodies in order to make the right decisions about how to proceed during a surgery. But IoT robots are already being used for surgery, showing that these challenges can be adequately addressed.

Healthcare Analytics

IoT technology connects multiple devices to one another. Due to this feature, IoT is helpful in the medical industry. The IoMT provides a significant amount of data from many connected devices. Doctors use this data to examine health trends. Besides, the information also helps in analysing the effects of various medicines on many patients. Health experts can also carry their study in a particular medicine after parsing data. Hence, the IoT application in the healthcare industry helps in promoting better healthcare systems.

Increased Patients’ Interests

 After the launch of medical apps, the patients’ have become more serious about their health. Hence, technology is giving birth to more conscious citizens. Today, people are trying to keep themselves fit and healthy. Therefore, they take the help of various apps available in the store. They download and install such apps on their smartphones to keep track of their health. Apart from this, people buy wearables. These wearables give accurate data about their health. Furthermore, they can also keep track of their exercise routine.