Internet of Things (IoT) in healthcare has enormous potential to transform medical treatment and boost global health indicators.
Both doctors and patients can benefit from automated, asynchronous medical data flow, especially when it comes to treating individuals with chronic diseases and critical health conditions.
Currently, patients communicate with doctors during in-person visits, where they are diagnosed and treated (usually having been tested beforehand) or instructed on further procedures. This is effective in cases of common illness such as flu or cold, but does it work as well for patients with chronic conditions? Not necessarily, as not only do patients with chronic conditions require regular attention and monitoring, but they also find it more difficult to arrange ad-hoc doctor visits when needed.
Applying IoT in healthcare could help alleviate such challenges and ensure better patient care, for example, for individuals who suffer from chronic illnesses and need constant monitoring and for individuals who live in rural areas where access to medical care is limited. In this article, we’re taking a closer look at the potential of IoT in the healthcare industry.
How does the Internet of Things work?
Internet of Things refers to an ecosystem of connected computing devices or machines where each has its unique identifier and is able to exchange data collected with other devices without human-to-human or human-to-computer interaction.
Such networks can consist of thousands of IoT devices that together create an enormous ecosystem. Virtually every industry can benefit from IoT in different ways, including the healthcare industry.
Our lives today are largely IoT-driven. We already have all the software and hardware required to enable tens of thousands of devices to communicate with each other instantly.
Powerful processors, increasing memory, Bluetooth, WiFi, and 5G are already being used to deploy robust and complex systems that constantly transfer and analyze data between each other. Every piece of data has a date and time of issue and these properties allow for live or near-live sharing.
Examples of how healthcare can benefit from IoT
In existing software and hardware, we also have numerous sensing technologies in health-oriented mobile applications, and wearable devices such as fitness trackers, pulse oximeters, blood pressure watches, EEG headbands and many others. Some of them are used in hospitals to monitor medical indicators, and we use others voluntarily to track real-time health data when we’re at home.
Combined with Data Engineering, these connected IoT devices could enable remote monitoring and improve healthcare operations. They could be applied to monitor multiple indicators and use live data to streamline asynchronous interactions between healthcare professionals, patients, and smart hospitals.
In such a scenario, doctors could easily access patients' data remotely and react accordingly as soon as symptoms are discovered, eliminating the need to arrange a visit at the doctor’s office. Such an approach has already been implemented in several healthcare facilities in Oregon to deal with the pandemic more efficiently.
Meanwhile, application of IoT devices in healthcare is still limited because of integration issues that require manual data sharing with external systems. Data privacy and data security also play an important part in this equation.
Nonetheless, we already have all the technologies at hand to benefit from the potential of IoT analytics to enhance medical treatment and numerous startups are already working to fill this gap. Let’s take a closer look at some of the benefits of IoT in healthcare.
Opportunities in healthcare IoT
Existing medical devices can be programmed to establish a connection with other devices or a data center to automatically exchange information as soon as it appears. This creates a lot of opportunities that were never available before in the healthcare sector.
Medical IoT devices could gather new live data on an ongoing basis, so that doctors and healthcare providers are able to make more informed diagnoses, based on multiple indicators. However, live or near-live data streaming can support more than just information gathering.
Data could be used for IoT analytics that can support more sophisticated healthcare processes, where multiple connected medical devices are used to monitor several indicators, such as a patient's heart rate, blood pressure, insulin level, and body temperature. With comprehensive data accumulated over a long period of time, rather than from isolated tests, more accurate diagnoses can be made.
This approach is called precision medicine — it’s about devising treatments tailored to each patient individually, based on multiple health indicators. In such a scenario, doctors are able to conduct treatment asynchronously — whenever the doctor needs to consult a patient’s health results, they log into the system and can access all the data collected to decide on further medical procedures.
IoT devices could also be programmed to notify medical staff immediately when immediate patient care is needed.
IoT-driven precision medicine could enable ongoing remote monitoring of non-critical patients at home, reducing the number of medical appointments and reducing unnecessary costs of management of chronic illnesses.
With that, doctors and healthcare facilities alike would have greater capacity to focus on patients with critical health conditions. Ongoing remote patient monitoring can also contribute to reducing stress for people who are in need of medical care, which supports faster recovery.
IoT in healthcare supported with EDGE technology can enable computers to make decisions for humans. EDGE solutions are currently developing at the speed of light. Such devices are capable of performing initial calculations when gathering data. These calculations could be extended to include algorithms and other advanced functionalities that would allow them to perform IoT analytics.
Such analytics could be used e.g. to determine what a particular EED signal means. This information can then be used to fuel quicker, automated diagnoses.
The IoT analytics solutions are already being used to perform basic medical analyses, such as notifying patients about their cholesterol levels or alerting diabetics when their next insulin shot is required. In fact, the latest smart devices are capable of delivering insulin whenever required.
Let’s take a look at how Automated Insulin Delivery (AID) works.
Case study: Automated Insulin Delivery
AID systems are a great example of how IoT, data engineering, and healthcare can work together to save people’s lives. AID systems are designed for diabetics and unlock the full potential of digital medicine.
They consist of a programmed insulin pump, an infusion set with a flexible tube, and a wireless Continuous Glucose Monitor (CGM) that a patient must have on them at all times.
The CGM is equipped with a sensor that gathers live or near-live blood glucose level data and other indicators pertinent to diabetics. They fetch the data even when a patient is asleep. Finger-prick tests are not required with this solution, which is incredibly convenient for patients.
Whenever the measures fall below the accepted thresholds, the insulin pump starts to work. In addition, the live data is shared with doctors to enable more advanced analysis. Such analysis utilizes broader patient data and applies additional algorithms to those in the CGM.
IoT in healthcare promises more advanced and personalized treatment
IoT is redefining healthcare by bringing patients much closer to doctors, to improve their comfort and safety. It can also greatly improve the quality of treatment they receive — by tracking multiple health indicators on an ongoing basis, healthcare professionals can draw more precise conclusions about a patient’s health.
Ongoing remote patient monitoring is also vital in individuals with chronic illnesses — it’s something that overburdened healthcare organizations cannot ensure without the aid of technology.
The IoT analytics solutions have the potential to not only solve numerous healthcare issues, but also improve the quality of healthcare operations and services. Automated, data-driven decision-making could eliminate potential human errors and reduce healthcare costs. Thus, healthcare providers, technology specialists, and data engineers should be working together on delivering healthcare solutions to support people’s health.
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