- As healthcare Internet of Things (IoT) devices grow, solutions to manage the data collected are becoming a needed feature in health IT infrastructure.
According to a Research and Markets report, the convergence of cloud, data management, and IoT solutions calls for the evolution of data analytics. The amount of data being collected needs to be analyzed and sorted in order for organizations to benefit from it.
Report authors state that a solution’s ability to sort data in an unstructured format, store it in different structural formats, and release that data for further analytics will be a defining factor of data management solutions across all major verticals, including healthcare.
The report predicts that many IoT data management solutions will be customized in the coming years, and the market could potentially save organizations 40 percent in operational savings.
IoT devices are becoming a large part of the health IT infrastructure ecosystem, from mobile devices to patient monitoring devices.
Healthcare IoT devices include clinician wearables and connected medical devices, such as physiological monitors, mobile medical apps, and MRI/CT/ultrasound scanners. Each device communicates a wealth of structured and unstructured data, constantly communicating with the network.
A second Research and Markets report pointed to the need for IoT management solutions due to increased spending on sensors, gateways, and embedded hardware and software found in many modern devices.
With the rapid growth of mobile adoption in the healthcare industry, organizations need solutions to manage the infrastructure resources used to run and deploy them. Entities must also gain network visibility to ensure secure connections for approved devices and find data management solutions to make collected unstructured data usable.
Vendors and healthcare organizations are working on different solutions to handle the influx of data collected by IoT devices. Many organizations have valuable data stored, but have no way to use it because they don’t have the necessary data management or analytics solution.
IBM Watson and Teva have recently partnered to produce an analytics tool that will discover new treatment options and improve chronic disease management by using the data collected by IoT and other devices.
The structured data found in electronic health records (EHRs) is simple to process compared to the free text entries or the unstructured data gathered by IoT devices.
With large unstructured data repositories, many vendors and organizations are turning to artificial intelligence to make use of the data. IBM Watson and Teva are also implementing natural language processing and machine learning to get the most out of the data they have collected. They hope to structure the data so it can be properly used.
"Teva envisions a future where we can empower patients and their families to better understand diseases, like asthma, and cope with health challenges in a more systematic, data-driven manner, with the ability to be proactive, rather than reactive," Teva Global Specialty Medicines President and CEO Rob Koremans, MD, said in a statement. "In doing so, we aim to cut treatment costs by providing patients, payers, healthcare providers and caregivers with relatable data that can inform action and insights into a patient's total disease management plan."
Using IoT data for population health management and better insight into chronic diseases is an important goal for healthcare organizations embracing value-based care initiatives.
Utilizing the insights gained from IoT data can improve patient care, but the data cannot be used if organizations do not have solutions that can manage the data and give administrators insight into the devices and how they communicate with the network.