A recently released report from Business Insider predicts that the Internet of Medical Things (IoMT) market is expected to grow to an estimated $158 billion in the year 2022. This estimate represents a massive leap from the $41 billion valuation that was reported in 2017.
The report follows up on previous research that was published by Business Insider back in June of 2019, when analysts estimated that the install base of IoT devices in healthcare will reach more than 161 million units by the end of 2020, supporting a widespread belief that the trend towards increased IoT adoption is unlikely to abate any time soon.
IoT devices both in and out of hospitals have become permanent fixtures of the healthcare industry, enabling stakeholders ranging from medical professionals to insurance providers to collect more critical data that assists their ability to make smarter decisions.
However, with the expansion of the data being collected, there is recognition across the industry that more tools are needed to help organisations glean more actionable insights from their data, pushing them to seek out data analytics software solutions that will help their teams visualise their mountains of data.
How IoT is impacting healthcare
The twin factors of widespread high-speed connectivity and the ability to place smarter sensors on smaller, increasingly inexpensive devices have helped to bring the benefits of IoT health services to the masses.
Beyond “wellness” devices like Fitbits and the like that help to provide a wealth of data indicators about our health, an industry of approved medical devices has sprung up in recent years, capturing the largest segment of the IoT healthcare market. The growth of types of devices in use, from wearables to specific solutions — like those for monitoring patients with diabetes, cardiac complications, and other health concerns — provides medical professionals with a significantly larger data set upon which to track and predict our health outcomes.
Much of this development has been aimed at bringing the technology to care facilities, with hospitals integrating more devices to replace many of their manual processes. These include the collection and documentation of patient vitals that can help indicate a deterioration in health, giving staff the ability to take preemptive action, among a host of other uses.
Outside of its implementation in medical facilities, telemedicine for remote monitoring at home is reported to be a top growth segment in IoT. These devices are already helping to provide value with services that monitor medication consumption, collect data at home that minimise the number of trips to a clinic or hospital (reducing the stress on both patients and facility resources), along with many other uses.
As with most technologies that provide benefits, however, IoT’s integration into healthcare is not without its difficulties.
Challenges to working with data collected from IoMT devices
Healthcare institutions have found themselves with more data than they know what to do with, and many are significantly underprepared to take advantage of the potential benefits. These organisations face a range of challenges that they will need to overcome quickly as IoT takes an ever-increasing role in how they operate.
For starters, medical professionals need to deal with a wide array of connected devices at their facilities. By some estimates, there are up to 15 devices at the typical hospital bedside. These are a lot of data producing inputs that will need to be connected and directed.
Zooming out, data can be highly distributed between multiple devices, locations, and teams, with each needing to be accountable and serving the needs of the patient. This can be tricky when a patient has devices that they are using at home and at the clinic, each one sending on data to different departments at their care facility. Mismanagement of data can mean that crucial information about the patient can be missed, severely impacting their doctor’s ability to provide optimal — potentially lifesaving — care.
Possibly the biggest challenge facing the healthcare industry is that the shortage of employees who are trained on how to work with actually work data analytics. A 2019 survey of healthcare executives reported that a lack of qualified team members for analysing data was their biggest hurdle to working with predictive analytics, potentially reducing their ability to glean the benefits of their collected data.
Even for those organisations that have data analytics-ready staff, many still lack the tools necessary to work effectively with the data, pushing them to seek out new data analytics software solutions.
Data overload driving demand for healthcare data analytics solutions
On first glance, many of the difficulties in starting to manage IoT integration will fall on the IT teams at healthcare facilities, who will need to handle the implementation and configuration into existing systems. However, the real challenge for these organisations comes afterward, when it comes to making sense of this firehose of incoming data.
A common complaint from healthcare organisations is that they are facing an overload of data being collected and are not able to gain the valuable insights that they need. Given that much of this technology — and, to a greater extent, the range of available data — is still new, teams need tools to help them analyse their information.
The IoT devices that are powering the newfound capacity for wide-scale data collection and analysis are already helping medical professionals and other stakeholders to gain a better understanding of how their organisations are currently operating. However, the long term goal is not just to know how they are doing in the present but how they can utilise the data to predict the future.
Predictive analytics is increasingly important for executives across the healthcare space. Over 92% of healthcare providers surveyed by the Society of Actuaries last year responded that predictive analytics are important for the future of their businesses.
These business leaders are also planning to back their talk with the capital to move it forward, with 60% responding that they intend to invest at least 15% of their budget over the next five years towards predictive analytics capabilities.
Drilling down into the specifics of those capabilities, visualisation of data was rated as the most important to the respondents in what they are looking for in their predictive data analytics software solutions, even beating out trending technologies like Machine Learning (23% to 16%).
Mapping out the future of data analytics
Healthcare BI is expected to reach a $10.1 billion valuation by 2025 according to some researchers, hopefully driving more innovation and dollars towards improving the available technology. This is likely to open the doors to more startups and increased investment from corporations.
As IoT continues its march into more aspects of healthcare, organisations are going to need to seek out more solutions that will allow them to harness the collected data into something that becomes usable for healthcare professionals.
Given the resources that look to be behind the development of new these technologies, we can hopefully have plenty of powerful options to help drive higher quality data analysis over the coming years.