How Medical Automation is Changing Healthcare

The use of automated tools is rising in dozens of industries. From manufacturing production lines to driving assistance systems, it comes as no surprise that healthcare too is watching automation grow in use year over year. Innovation within artificial intelligence (AI), particularly within generative AI, is booming. The growing possibilities of its use in medical settings have encouraged many organizations to study the effects on patients and staff alike.

There are limitations to how effective automation and AI are within healthcare. The implementation of AI and automation is still in its infancy, but its use has proven beneficial. Improvement and optimization of processes due to advanced technology’s efficiency has led to a greater adoption rate of such tools.  This can be seen in the overall global market growth in AI that’s picked up over the last several years.  ‍

Grand View Research states, “The global artificial intelligence market size was valued at $136.55 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030.” Grand View Research’s report noted that innovation within artificial intelligence applications has increased its utilization rate through notable circumstances. A prime example can be seen in late 2019 and early 2020, when “AI-enabled computer systems [were used] to fight against the outbreak, as several tech giants and start-ups started working on preventing, mitigating, and containing [Covid-19].”

AI models were used to help identify positive coronavirus cases from X-rays through diagnostic algorithms to aid exhausted and understaffed medical personnel. This AI model is similar to another program that is currently being used to detect positive signs of breast cancer in radiographs.

The use of AI and automation within healthcare is continually growing through cases studies, clinical trials, and theoretical applications by the day. The medical industry is comprised of dozens of different specialties all required to maintain a healthy society. It’s no surprise that AI and automation would flourish in this particular setting.

Ironically, as with vehicles, the industry has yet to experience a fully automated healthcare system, but has different levels of automation. The industry is still far from a widely used, and successful, completely autonomous medical system that outperforms human staff. However, each level provides a positive effect that benefits staff and patients alike.  

Humans Only: No AI

On one end of the spectrum, the first level of AI and automation within healthcare is, ironically, no AI. It’s easy to spot a healthcare system that lacks advanced technology or digital data; it’s as traditional as healthcare can get. This means patients are examined by doctors with human staff doing the manual work of inputting data, generating processes, or alerting patients to upcoming appointments.  

Similarly, this extends to all medical procedures being accomplished manually, such as laparoscopic surgeries or medical researchers gathering data for a meta-analysis without the aid of data collection tools. While there is nothing inherently wrong with this version of healthcare, it can be significantly improved with artificial intelligence and automation, assisting in patient scheduling, data analysis, and process optimization.  

Human error, a frequently unavoidable side-effect of manual processes, happens at a rate of 4%, with 14% of all errors containing dangerous discrepancies. This can be significantly decreased through the use of automation and advanced technology.  ‍

Shadow Mode: AI Learns, and Humans Lead

The second stage of AI and automation within healthcare is utilizing advanced technology as an “assistant” and “student” under a medical professional. To help train algorithms on proper detection, AI is included in whatever process it needs to specialize in. This could be anything from following along during an X-ray, checking the physician’s accuracy, and quietly logging all information associated with a specific case for future diagnostics on behalf of the AI.

These training modules can help teach other AI models to either conduct the same task or a more complicated, multi-step process.  

In 2020, Imperial College London researchers proposed a framework that “evaluates the accuracy and uncertainty of human clinicians against that of AI in shadow mode’s recommendations. This can help determine how efficient the AI “student” is and where it needs improvement to help it move to the next stage.”

With this framework, the AI “student” can be corrected by its “teacher,” the human physician, early in the learning phase, decreasing the kinds of errors it could make in future processes where it becomes a “physician.”  ‍

AI Assistance: AI is On the Same Level

The third level of automation within healthcare is rising in use within the medical industry. With the third level, AI systems support physicians in clinical decision-making through suggestions based on their training and analysis. AI can be viewed as a valuable assistant or “second opinion” for physicians to compare their findings against to confirm or deny.

A prime example of this can be found in many ongoing real-world applications. A popular AI assistant type of third-level automation detects breast cancer in CT scans and radiographs. The AI program will compare the patient’s chest scan images against other scans from its database. It will use pattern recognition to investigate and highlight suspicious indicators that could lead to cancer.  

It’s important to note that an AI assistant, while often correct, as case studies show, cannot and does not have the final say on cancer or any other kind of diagnosis. That is still left to the human physician’s determination.  ‍

Partial Automation: Human Assistance Still Required

The fourth stage of automation within healthcare is where the AI program graduates from assistant to physician. At this stage, an AI model can present its diagnosis that can be used to determine treatment plans. However, if the AI program is not confident in its diagnosis, it can request further confirmation from a physician.  

While partial automation using this kind of AI is not being used to a similar extent as the third type of automation, medical AI technology companies are actively implementing programs where they can. Two companies, Behold.ai and Nines, have recently succeeded in their medical AI endeavors. Behold.ai’s AI-based red dot system classifies chest X-rays based on abnormalities within Covid-19 patients. It has been used to accelerate diagnoses and quickly allocate hospital resources for an “instant triage” of cases.  

Nines developed its own AI system to identify potential intracranial hemorrhages and mass effects from CT scans, which are flagged for radiologists to make a final review. In April 2023, results of an anonymous and randomized clinical trial showed cardiologists agreed more often with the AI's assessments, saving time for the human sonographers and cardiologists. ‍

Full Automation: No Human Assistance Needed

The final stage in the automation ranking is full automation. At this level, AI can perform processes alone and does not require human input. At this stage, an AI system could analyze a chest CT scan and request subsequent testing without consulting a human physician. Latter tests and a final diagnosis can be done without the medical staff’s input. Some scientists believe even some surgeries, such as ophthalmologic, could be fully automated. Already, a few of these surgeries are partially automated.

Even now, fully automated medical process studies are being carried out. At John Hopkins University, a robot performed laparoscopic surgery on pig tissue without a human directing it. More impressive, the University’s STAR robot operated on four animals, reconnecting two ends of intestines in one surgery with better results than the human surgical team performing the same procedure.  

Despite these successes, experts believe it is unlikely that any true full automation in the medical setting will soon be achieved. It would take dozens more clinical trials and studies before anyone would see it in a standard medical environment.  

It should be noted with AI systems that outperform human staff that the goal of AI in any industry, not just healthcare, is to assist human staff, not replace them. With partial and complete automation, the tools are designed to optimize processes so that human medical staff can focus on more significant tasks that even the most advanced AI system cannot perform.  The benefits of automation and AI within healthcare can be broken down into four main areas, though plenty more can be found.

1. Improved Patient Safety

Advanced AI systems can significantly reduce the risk of human error often found in manual processes. Unfortunately, one of the leading causes of death and injury in healthcare is attributed to human error. Due to understaffing, physician exhaustion, and many other issues, even the most competent physician can accidentally produce a disastrous error.  

With advanced technology and automated systems, human errors can be significantly decreased or removed entirely. With these errors lessened, more effective treatment plans can help increase patient mortality and provide greater insight for faster diagnoses in future cases. Improved administrative operations through automation of data collection can help decrease wait times for essential procedures such as surgery or chemotherapy, thereby reducing the time spent for patients to find and recover from treatments.  ‍

2. Increased Operational Efficiency

Along the same lines as reducing human error, AI systems can help improve the efficiency of human physicians, surgeons, and other staff by increasing process effectiveness during complex procedures that require precision and accuracy. Robot-assisted surgery can help decrease time spent in the operation room, lowering surgeon fatigue, patient recovery time, and mortality rate.  

Outside the operating room, automated systems can help streamline the transfer and access of private patient data in secured databases. This can allow for the quick sharing of vital data among facilities, preventing bottlenecks that often arise when there is communication between multiple facilities treating a patient. This capability saves time by reducing administrative overhead, and heightened cybersecurity ensures privacy and compliance with HIPAA and TCPA security standards.  ‍

3. Enhanced Healthcare Accessibility

One of the most significant examples of advanced technology aiding healthcare was the explosion in the use of telemedicine during the pandemic. With telemedicine, patient appointments boomed, increasing patient attendance in rural and highly urbanized areas. Increasing telemedicine coverage will help patients in less-developed countries or more remote regions access healthcare, improving patient health and safety.  

4. Reduced Costs

The main reason healthcare executives in all sectors advocate for automated solutions is the eventual reduction in costs AI systems will bring. AI solutions will help decrease overtime for exhausted and understaffed medical teams with AI systems' improved efficiency in operations. Fewer errors will reduce overall stress among medical groups, allowing them to focus on increasing patient care and limiting the possibility of medical malpractice suits.

With advanced technology, taking care of other tedious but necessary tasks, such as scheduling time spent sorting through Excel spreadsheets or binders littered with sticky notes, would take seconds compared to minutes or hours.  

Access to an efficient healthcare system is pertinent to a modern society, especially with tools that can help bring any country’s medical system into the digital age. It’s time to get started advancing healthcare.  ‍

How to Kick Off the Next Medical AI Project

Automation is becoming more common in industries across the globe, from automotive to healthcare. AI systems can help automate or assist with many manual tasks within the medical world by lowering costs, increasing patient safety, and optimizing staff efficiency. There is no need to worry about losing jobs to automation, either. Experts agree that AI systems will only assist, not replace, medical professionals, regardless of the automation level. To get to this stage, original equipment manufacturers (OEMs), contract manufacturers (CMs), and electronic manufacturing service (EMS) providers will need the right components to power the tools of the future of medical care.  

Sourcengine is one of the largest global marketplaces for electronic components, with over 1 billion part listings from 3,500+ factory direct, authorized, and qualified third parties. Users can learn all they need about components from datasheets, lifecycle status, and, if applicable, alternates.

As a global company, Sourcengine has procurement agents, inspectors, and warehouse personnel to facilitate the movement of electronic components worldwide whenever or wherever a delivery is needed. So, no matter where or when you’re working on your next AI system or automation solution for healthcare, Sourcengine can get you the hard-to-find components you need anytime.

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