The healthcare industry has always been bound to technological advances. From the late eighteenth-century vaccine to late nineteenth-century medical imaging (x-ray), technological innovation is how healthcare continues to evolve. Today embedded systems in hospitals and artificial intelligence (AI) are setting the stepping stones.
Hospitals are critical infrastructure for societies; one of the pillars sustaining the constant growth of better living standards and life expectancy increase. Therefore, the most innovative tech has to be part of the services and solutions provided in these buildings. Continue reading to learn about the opportunities and challenges the future of embedded systems have in hospitals.
The importance embedded technology has in hospitals is visible when talking about MRI and CT scanners, ultrasound imaging, and wearables, among others. All these use embedded systems. Embedded systems are installed in almost all the devices we use daily, such as refrigerators, microwave ovens, digital cameras, smartphones, mp3 players, cars, and even the toys kids use.
Currently, advancements are developing processes pushing the performance of embedded systems to unsuspected levels. For example, artificial intelligence can now be used in an embedded system, i.e., embedded AI (EAI). Applying this technology to hospital processes and procedures offers a multitude of opportunities. In 2019, there were over 36 million hospital admissions in the U.S. to give you an idea of the data generated by hospitals.
Deploying embedded AI provides a way to automate many tasks and reduce the time of finding patient records.
Medical diagnosis improves immensely with embedded AI, opening an excellent opportunity to confront the medical error challenge. A reality that, in the U.S., results in approximately 100,000 people dying each year, costing around $20 billion a year. EAI's analysis speed processes historical data in a question of minutes. In contrast, the same amount would take a team of physicians years to analyze the same data.
As EAI can predict earlier and with higher accuracy, diagnose a disease, the rate of deaths due to medical error drops drastically. Another benefit comes with drug testing because they currently average nine-year trials and costs $1.3 billion. These clinical trials procedures go through various arduous steps:
It is a rudimentary process where human error is possible and is time-consuming. Only one out of ten drugs trialed will be approved by the FDA. Actioning AI into the entire process can significantly improve time to market and results.
Essential to all businesses is customer satisfaction. As mentioned earlier, over 33 million people were admitted into one of the +6,000 U.S. hospitals. Since admissions come with different ailments, insurance coverage, and conditions, providing smooth service takes work.
Embedded AI is helping hospital staff process millions, if not billions, of data points faster and more efficiently. This results in smoother admittance, treatment, and shorter stay, giving patients a better experience. As we can appreciate, data management is vital for healthcare to invigorate the industry, and artificial intelligence is the best tech tool. It breaks down data silos and connects information in minutes that used to take years to process.
Up to now, robotics has addressed basic autonomous tasks, but with embedded technology's development, precision and life-threatening jobs are being aided by robots. This is why, today, robot-assisted surgery is becoming more and more commonplace. Assisted with the cameras, mechanical arms, and surgical instruments, surgeons augment their experience, skill, and knowledge while seated at a computer console.
Robotics gives doctors a three-dimensional, magnified view of the surgical site, exceptionally heightening the perspective compared to relying on their eyes alone. Robot-assisted surgeries have led to fewer surgery-related complications, less pain, and quicker recovery. Consequently, complex procedures reach a level of precision, flexibility, and control that goes beyond human capabilities.
Looking at other benefits coming from robotic surgery, it makes minimally invasive surgery possible. The benefits of minimally invasive surgery include the following:
Hospital maintenance ensures equipment performance, localization, and environmental standards. Healthcare-associated infections (HAI) are common; one in 31 hospital patients has at least one HAI daily. Deploying embedded systems in hospitals to measure temperature, air quality, and humidity helps to keep track of possible outbursts of HAI. It also provides an alert for medicine storage inside refrigerators and freezers, autonomously safeguarding hospital medicine and stock inventory.
As for equipment maintenance, embedded technology AI assisted can predict issues with machinery or equipment. Via historical data analysis from vibrational analysis, acoustic emissions, and ultrasound, among others, failures can be predicted before severe harm is done. A study by the U.S. Department of Energy indicates predictive maintenance:
Embedded technology and artificial intelligence are setting the grounds for considerable benefits in the healthcare industry. But as mentioned previously, some challenges don't permit the full potential of embedded systems in hospitals to be achieved.
The overhaul embedded tech is going through raises some essential blocks that slow down the deployment of its advancements. These include cybersecurity issues, the ability to manage data generation cost-efficiently, and the possibility of ensuring the data is reachable in real-time. Let's look at these significant challenges in more detail.
Unfortunately, cyberterrorists are growing with the introduction of embedded systems connected to web-based platforms. The key to the problem resides in the centralized nature of these platforms. It is nothing new data breaches, ransomware, and distributed denial of service (DDoS) attacks have been part of the World Wide Web (WWW) since its beginning.
A fundamental fact must be remembered: in the beginnings of the internet, security wasn't built-in by design. This makes the cybersecurity issue gain even more power, and with the constant addition to the WWW of sensors, devices, and machines, the attack surface doesn't stop increasing. More worrying is that Industry 4.0, or the fourth industrial revolution, is data-driven and is entering all industry verticals. This means pillars in society sustaining our people's health, food, and energy supply are targeted by hackers putting whole communities at life-threatening risks.
Regarding the healthcare industry, hospitals account for 30% of all large-scale data security incidents. Looking at some of the most critical cyberattacks in healthcare history:
Another significant vulnerability, even more worrying, is the ease with which medical devices such as insulin pumps, continuous glucose monitors, and pacemakers or defibrillators can be accessed by hackers.
Digital data is reaching the zettabyte (10²¹) era, and this tsunami of data must be managed adequately to provide tangible returns. Today, solutions are based on centralized data management centers that move all the raw data to these server centers for storage, processing, AI analysis, and delivery back to the source.
This way of proceeding opens various problems, making the investment in these data management solutions not worthwhile. The costs of moving data to centralized solutions in an ever-growing data generation environment will only keep increasing. Considering a recent report indicating respondents estimate that 30 percent of cloud spend is wasted, cost-efficiency still needs to be reached.
In addition, the burden of cloud service providers must be a sustainable asset for the UN's SDGs. For example, a Carnegie Mellon University study concluded that data transfer and storage costs about 7 kWh per gigabyte. While saving it to your hard disk requires about 0.000005 kWh per gigabyte to save data. Therefore, cloud service providers act upon economic and sustainable cost-efficiency.
We all agree that real-time data 24/7 is a must for the correct functioning of a hospital. Managing zettabytes of data is only possible if this data to information analysis can be assured in real-time. A surgeon must know at all moments that data is real-time and trustworthy; otherwise, the risks of incorrect procedures are high.
In this sense, centralized data management services require data to be moved to server centers that can be thousands of kilometers away. This trip that critical data has to do opens up latency issues and bandwidth bottlenecks. In other words, data travels and takes time to return to the source; this can be seconds, minutes, or hours.
A problem that needs to be addressed for case-sensitive data like the one generated by surgeons, nurses, and physicians. Outages can come from various issues like network failures, hardware or software malfunction, power outages, cyberattacks, and human error. The economic costs are estimated to be around $9,000/min. People loss has no price tag; therefore, hospital decision-makers must carefully study the options.
If you've reached thus far, you are looking into innovative approaches to handle case-sensitive data management for hospitals. Access the EDEN system, a decentralized software platform working at the edge. Its blockchain and quantum-safe tech are ideal for critical infrastructure like healthcare. Its embedded AI working at the source mitigates all the challenges embedded systems stumble upon with centralized solutions.
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