How IoMT is Transforming the Cost of Healthcare

Updated on August 29, 2023

In medicine — as in many other fields — data is power. And today, the Internet of Medical Things (IoMT) is making medical data accessible and usable at scale.

For providers and patients alike, IoMT technology can exponentially increase the efficacy of medical care, reducing the time, materials and equipment necessary for accurate and effective treatment. Less time and fewer resources translates to lower costs, and in the American system, where the cost of healthcare is one of the leading causes of consumer bankruptcy, that’s an attractive outcome for everyone.

Here’s what you need to know about how IoMT is on its way to transforming the cost of healthcare. 

Reducing in-person office and hospital visits — and their costs

IoMT refers to all the devices and software that enable medical data to be tracked and processed in real time. These technologies enable telehealth and telemedicine strategies, which allow providers to analyze that medical data and, in some cases, diagnose and interface with patients at a distance. 

Thanks in large part to the pandemic, many of us are already familiar with the concept of a virtual healthcare appointment. Video conferencing software makes it possible to bring healthcare services into the home in as low-touch — and therefore low-cost — a way as possible. 

As the IoMT continues to develop and expand, these visits may be bolstered with real-time healthcare data using technologies like remote patient monitoring (RPM), which is already used to track certain data points like blood pressure and weight. Although some diagnostics and procedures will probably always require an in-person visit, the increased efficacy of remote medical care can save on transportation costs for both providers and patients, and on overhead costs for medical care teams.

Better patient monitoring means more time (and money) spent on what matters

Even when patients do need to appear in person, IoMT technology can help healthcare professionals provide more accurate — and therefore less costly — care. Along with being used at home to aid telemedicine and help providers sniff out early signs of illness, wearable trackers and other IoMT devices can continuously monitor patients’ conditions after they’ve been admitted for inpatient care.

That means healthcare professionals — who are facing a burn-out crisis — can redirect their limited time and energy from the tedium of taking vitals toward more pressing, less automatable matters, saving money in labor costs along the way. And when such data is automatically and continuously recorded, providers have much more insight into their patients’ condition, which can speed up and improve care.

Medical algorithms and machine learning help organizing teeming data

IoMT technology means providers have access to a sea of patient medical data far vaster than ever before — which is a good problem, but one that can become overwhelming for the limited and busy human brain. Without the help of artificial intelligence and machine learning, the time and energy needed to analyze and process so much data could potentially undermine the time and cost savings that data stands to produce.

Fortunately, medical algorithms and machine learning are already helping reduce the human bandwidth necessary to understand what all that data means. In fact, these technologies can make the triage process faster than ever. With thousands of data points, medical algorithms can predict potential ailments long before human providers might be able to see the signs — or even before patients could. In this way, IoMT can make preventative wellness more preventative than ever before, and, in exponentially speeding up the process of accurate diagnostics, save lives and reduce the cost of treatment. 

Insuretech uses AI and machine learning to offer more accurate — and often lower — pricing

Along with the cost-reducing dynamics we’ve listed so far in the office, hospital and patient’s home, IoMT technology also has the ability to improve the health insurance process. By using artificial intelligence, machine learning and the wealth of data points available on the IoMT, insurtech can help consumers find plans custom tailored to their precise medical needs — and, ideally, at a lower cost than a less-bespoke (and thus more inclusive) plan.

Insurtech, already common in the auto- and home-insurance markets, is becoming increasingly common in the health insurance market as well — and given the sometimes extravagant cost of American medical care, perhaps has more potential to reduce costs in this field than any other. In addition to offering more accurate pricing based on holistic medical information sourced from IoMT-based data, the algorithms and artificial intelligence employed by insurtech could lower operational costs for the insurance companies themselves — savings that could, at least in theory, be passed down to consumers.

As skeptical as some may be about artificial intelligence and our increasingly internet-connected world, the power of these technologies can be used for good — particularly in the healthcare industry, where high costs and the natural limitations of human provider bandwidth can cost patients their savings or even their lives. 

Of course, these technologies also create their own challenges, including privacy concerns: with so much sensitive data floating around, it’s more difficult (and more critical) than ever to ensure that patients’ private medical information stays in the right hands. As we move further into our digitally connected future, we must find the balance between human innovation and machine learning to create the safest and most efficient outcomes possible — in the healthcare industry and beyond.