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The world’s older population is growing dramatically; 8.5% of people worldwide (617 million) are aged 65 and over, and this number is projected to jump to nearly 17% of the world’s population by 2050 (1.6 billion). In addition, global life expectancy at birth is projected to increase by almost eight years, climbing from 68.6 years in 2015 to 76.2 years in 20501. Chronic diseases and conditions are on the rise, which will push the current healthcare systems beyond its current limits and capabilities. Societies have rising expectations for robust health care services; and healthcare facilities are facing many new and serious challenges in balancing the expectations against the available resources. Luckily, continuous technological developments are helping to improve some medical processes, ease the workflow of healthcare practitioners, and ultimately, to improve the situation in an overloaded hospital. 

Digital transformation of healthcare

Internet of Things (IoT), or to be more specific, Internet of Medical Things (IoMT), is revolutionizing the healthcare industry. The number of connected medical devices is expected to increase from 10 billion to 50 billion over the next decade2. Cisco estimates that by 2021, the total amount of data created by any IoT device will reach 847 Zettabytes (ZB) per year3. At some point, IoT will become the biggest source of data on Earth. Imagine the possibilities if human-oriented data, like medical history, allergies to medication, laboratory test results, personal statistics, amongst many other things, were to be digitized as part of the electronic health initiatives. Healthcare practitioners will be able to interpret and leverage the plethora of big data from connected systems to make informed patient care decisions as well as understand and predict current and future health trends. The answer? Machine Learning (ML).

Machine learning helping to propel healthcare IoT

ML is an approach to achieve artificial intelligence (AI); algorithms are utilized to analyze data, learn from it, and identify patterns, then makes decisions with minimal human intervention. Healthcare providers and device makers are integrating AI and IoT to create advanced medical applications and devices that can provide person-centric care for individuals, from initial diagnosis to ongoing treatment options, while solving a variety of problems for patients, hospitals and the healthcare industry. At the same time, these AI-enabled medical IoT devices will make healthcare treatments more proactive rather than preventive.

An autonomous “nurse” is an example of an AI-enabled medical IoT application. It will be able to answer patients’ questions since it is connected via the internet to a large range of data from previous health records. By integrating facial recognition, the robotic ‘nurse’ will be able to recognize the patient’s mood and will adapt its behaviour and reaction accordingly. It will also be able to remind its patients to take medication, as well as reminding them of their doctor’s appointments. Now, imagine if a hospital were to “hire” robotic “nurses” that can reason, make choices, learn, communicate, move and are connected to the hospital’s network and connected to each other, they would be able to help the nurses with tasks like administering medication, maintaining records and communicating with doctors and educate patients and on disease management, just to name a few. This will be a good solution to the situation where the nurses sometimes are pushed to handle more than they are capable of.

Soon, ML will bring a set of bots to the healthcare industry, with billions of “dumb” machines transformed into smart machines.  This change is going to transform the way patients are assessed and treated; and healthcare professionals can provide a better quality of care that is tailored to each patient.

A bright future for telehealth

Another new development the healthcare industry is experiencing today is a general shift of in-office visits to remote health monitoring or telehealth. Many patients have agreed that home is the best place for healthcare, with patients being in their “normal everyday environment”.  A survey conducted in 2016 concluded that 94-99 percent of 3,000 patients were very satisfied with telehealth, while one-third of the respondents preferred the telehealth experience to an in-office doctor visit4.

With IoT, remote health monitoring, or telehealth is feasible, especially for patients living in remote areas. Another reason why remote health monitoring is getting popular is because of the vast varieties of biosensors and medical wearables that are available readily in the market today. So, what’s in it for the healthcare practitioners? All data coming from their remote patients will be able to help them detect patterns and gain new insights into health trends. That’s what IoT, big data and analytics software can help to achieve. 

 Conclusion

The healthcare landscape has changed and is still changing.  Patients are starting to embrace the change, using medical IoT devices to manage their health requirements. Healthcare providers are starting to incorporate connected healthcare to drive excellence, be competitive and improve treatment outcomes to give patients better healthcare experience, while medical device makers are developing solutions that are more accurate, intelligent, and personalized. Ultimately, leveraging technologies in an effort to improve treatment outcomes, the management of drugs and diseases, and the patient experience, will lead to a more efficient hospital.

If you are looking for more information on Keysight IoT solutions, please go to www.keysight.com/find/IoT.

Keysight Technologies helps customers bring breakthrough electronic products and systems to market faster and at a lower cost. Keysight’s solutions go where the electronic signal goes - customers span the worldwide communications ecosystem, internet infrastructure, aerospace & defense, automotive, semiconductor and general electronics end markets.
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