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The concept of Connected Industry is an unfolding vision where the full spectrum of technological innovation – including IoT, connectivity, data management, artificial intelligence (AI) and machine learning (ML) derived from the fourth industrial revolution – benefit all industries and the world at large.

In healthcare, it’s already transforming the experience for providers and patients alike. Now, it’s possible to uncover data insights that deliver improved quality, drive productivity, increase cost-effectiveness and ensure optimum care reliability at a time where skills in the industry are scarcer than ever.

But while progress in recent years has been impressive, we’ve really only scratched the surface of what’s possible by creating a truly connected healthcare industry.

IoT in healthcare – the next frontier

Healthcare has an established track record in the realm of IoT. However, many devices still aren’t connected – or optimally so – largely due to the sector having a fair amount of legacy technology within its installed infrastructure base (think of basic blood pressure or glucose monitors, for example.) This brings the requirement to manually move patient data captured by these devices from one system to another.

Another IoT-related challenge for healthcare organizations is security. Never before have we had so many medical devices, and each one has its own operating system, often connected to our networks. As those systems age, it becomes more difficult to secure them, which creates risk for the data in our systems. Mindful of these areas of potential vulnerability, healthcare organizations are increasingly focusing on strategies to secure and manage their devices to ensure that their patient data isn’t compromised.

Adding to the challenge is the distributed nature of these IoT devices. In larger hospitals and healthcare facilities, it’s not always easy to establish the precise location of each device – or even if it’s still in commission. As a result, we’re seeing the concept of real-time services coming to the fore. This allows healthcare organizations to monitor exactly where each piece of equipment is at any given time. It extends further to monitoring the location of patients themselves within the campus to make care more effective and efficient.

Data management – critical to uniting the care ecosystem

While the industry has been highly effective in ensuring much of the data generated is captured in electronic healthcare records, the promise that this would deliver rich sets of insights hasn’t come to fruition. That’s largely a result of a lack of interoperability between systems. For example, all physicians’ offices might not be able to share data quickly and easily with the hospital; rarely can the hospital’s systems share data with the long-term care facility.

To illustrate the downside of this siloed arrangement, imagine your doctor prescribed you a medication to which you had an adverse reaction. You’d like to think that if the following year, you were admitted to the hospital for a related procedure, your treating physician would already be aware of your allergy on the day of your admission (without you having to share that information and wrack your brain trying to remember the name of the drug that cause that nausea or nasty rash.)

Cloud is the great enabler of this level of interoperability we seek as an industry. In the next few years, it will support a level of data exchange across locations that allows more granular insights and reporting on patient conditions. Cloud will also enable faster and more timely sharing of important medical information. For example, if a certain medication is withdrawn, doctors will be able to immediately see which of their patients are taking it, alert them, and prescribe a suitable alternative.

A professional healthcare in a lab

Triaging healthcare with AI and ML

With so much more data now in hand, it’s possible for healthcare leaders to look at ways to bring the power of AI and ML to bear to solve large-scale, longstanding population health challenges such as COVID, outbreaks of influenza or other public health emergencies in certain geographies.

These technologies are also breaking new ground in helping us better understand and model rare diseases, across every population from pediatric to diseases of the elderly. By aggregating and analyzing data at a faster rate than humans can, AI and ML allow the medical community to diagnose and treat these rare conditions early. The sooner most diseases are diagnosed, the easier they are to treat.

In the realm of radiology, AI and ML algorithms (rather than physicians) are already being used to perform the first-level analysis of X-rays and other digital images, which speeds and simplifies the process of providing patients with a medical diagnosis. They’re programmed to understand what ‘normal’ versus ‘abnormal’ anatomy looks like, automatically alerting a radiologist to take a closer look if an anomaly is detected.

AI and ML are also effective in quickly and accurately diagnosing diseases and conditions that are common but sometimes overlooked. For example, it’s not unusual for a patient who is suffering from a stroke to present with symptoms similar to those of a migraine. AL and ML models can be programmed to flag certain combinations of symptoms that could potentially point to a more serious condition that might not be immediately diagnosed.

With unprecedented healthcare skills shortages and many emergency rooms simply overwhelmed, the concept of using AI and ML to triage care is becoming increasingly important.

AI and ML are also allowing healthcare facilities to improve their levels of patient communication and support. For example, these technologies allow healthcare providers to quickly assist patients in their mother tongue without needing to locate somebody in the facility or call center to translate. Or they can automatically detect if an administrator or call center agent in one area isn’t busy and reallocate them to another part of the facility that’s experiencing a large volume of patient queries.

A seamless care journey

As we look ahead to 2022 and beyond, we can expect connected technologies to play an increasingly central role in helping healthcare providers expand access to quality care cost-effectively, while improving clinical outcomes.

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