Artificial Intelligence Uses in The Healthcare Industry

Artificial intelligence is beginning to revolutionize healthcare nationwide. AI is and will continue to be used to help doctors communicate with patients better, diagnose diseases earlier, develop treatments better and faster, and in many other ways. The companies that design AI software applications for the healthcare industry need to understand what FDA regulations might govern their software – for example, when the AI might be considered a drug or a medical device. Physicians need to understand any privacy issues that might affect the use of AI for their patients. The promises that AI companies and health practitioners are regulated by the Federal Trade Commission (FTC) for honesty with regard to any representations.

This article summarizes some of the current applications and trends for the use of artificial intelligence in the healthcare profession. Artificial intelligence in general is the use of software that is based on the software continually learning and adapting from prior knowledge that the software gains from the initial application through all subsequent uses of the software. AI is able to analyze large amounts of medical records, lab results, diagnostic results, and other data to develop new insights into the practice of medicine.

FDA POLICY ON WHEN SOFTWARE THAT USES ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING QUALIFIES AS A MEDICAL DEVICE

As more artificial intelligence products become available, the FDA is reevaluating its approval criteria. For now, De novo approval and 501(k) are being used along with premarket approval.

ARTIFICIAL INTELLIGENCE AND THE HEALTH INSURANCE PORTABILITY AND ACCOUNTABILITY ACT OF 1996 (HIPAA)

AI in the healthcare industry almost by definition, requires constant access to patient information. Developers and covered health providers need to understand when and how HIPAA applies to their […]

Johnson and Johnson, a large pharmaceutical company that is conducting much research into AI and its healthcare applications, emphasizes that AI should supplement human decisions and actions – and not replace those decisions and actions. Some of the focal points of AI use that Johnson and Johnson (and other AI companies) are studying include the following:

Earlier detection of diseases

AI is being used to help detect and diagnose diseases earlier by using AI to analyze common diagnostic tests such as electrocardiograms and echocardiograms. Early diagnosis of a disease can help doctors provide more timely and more accurate treatments.

As an example, Johnson and Johnson states that “pulmonary hypertension (PH) and cardiac amyloidosis, two progressive and often-fatal diseases” are often misdiagnosed – even though treatments for these diseases do exist. Early diagnosis without AI is difficult because the early symptoms of these diseases are also common to other diseases. Johnson and Johnson stated their company worked with Anumana and Mayo Clinic (for the analysis of pulmonary hypertension), and Ultromics Ltd. and Atman Health (for the diagnosis of cardiac amyloidosis) to develop AI algorithms aimed to help identify the two diseases accurately and earlier.

One of the J&J researchers and physicians said that the goal of the company is to “develop AI-enhanced tools that can be seamlessly integrated into the current clinical workflow of physicians.” The researcher/physician said:

“We determined which tests patients commonly receive early in their journeys to diagnosis—electrocardiograms in the case of PH and echocardiograms in the case of cardiac amyloidosis—and developed AI algorithms that could detect subtleties that are invisible to the naked eye, suggesting patients should be flagged for confirmatory testing.”

The algorithms (the one for PH and the other for cardiac amyloidosis) have each received “Breakthrough Device Designation” from the FDA. If the algorithms are approved, the algorithms could help detect and treat the diseases sooner.

Other examples of medical devices that use artificial intelligence include “connected devices, robotic platforms, and digital solutions.” Using another example, a J&J product that uses AI and machine language (ML) will help doctors use flexible robotic systems (instead of conventional bronchoscopes) to help detect lung cancer earlier by using “preoperative CT scans of the lungs to inform the procedure.” The AI/ML technology “helps physicians guide the bronchoscope during lung biopsy procedures and allows them to locate a potential tumor more accurately” leading to better diagnoses and better treatments.

Breakthrough Device Designation is an FDA voluntary program “for certain medical devices and device-led combination products that provide for more effective treatment or diagnosis of life-threatening or irreversibly debilitating diseases or conditions.” The program aims to help patients and doctors provide timely access to medical devices – by speeding up some of the FDA approval requirements. The approval process does require that the medical device meets “the FDA’s rigorous standards for device safety and effectiveness.” The Breakthrough Devices Program helps manufacturers interact with FDA experts during the premarket review process.

PROPOSED REGULATORY FRAMEWORK FOR MODIFICATIONS TO ARTIFICIAL INTELLIGENCE/MACHINE LEARNING (AI/ML)-BASED SOFTWARE AS A MEDICAL DEVICE (SAMD) – PART TWO

Key provisions of the FDA’s proposed regulatory framework of software that uses and adapts to artificial intelligence and machine learning

Driving drug discovery

Pharmaceutical companies need a lot of time and work to discover and develop new drugs. Developing new medicines requires understanding “what biological and genetic variations cause diseases to develop.”

Artificial intelligence with the development of medicines by examining electronic health records, lab results, and other “anonymized medical datasets” to “fill in missing information” as to the causes of the diseases. With AI, researchers can develop medicines that are more targeted and more precise.

For example, in oncology, AI can study digitized images of biopsies to help identify “subtle differences between tumors, pointing to the presence of genetic mutations in a subset of patients.” Researchers can use AI to develop medicines for patients within that subset. The AI algorithms could also help “identify genetic mutations” to find patients with the disease in the real world – to recruit and conduct clinical trials.

Only a small percentage of drugs move to the clinical trial stage. Another J&J researcher states that

“AI is not only helping us identify the right targets for complex diseases, but it’s also helping us design fit-for-purpose molecules to treat diseases and optimize them to provide targeted treatment to the disease while also reducing the impact of side effects.”

With AI, the most promising medicines can be placed into the clinical development stage increasing the odds of approval by the FDA as a drug.

More targeted clinical trial recruitment

AI, as mentioned above, can help recruit and enroll patients that meet specific clinical trial criteria. With AI, the clinical trial team can “bring trials to more patients, rather than waiting for patients to come to us.” Typically, clinical trials take place at major academic medical centers which don’t include people who don’t have access to the centers. AI helps bring clinical trials to the patients who can’t come to the medical center – to locations and healthcare institutions where the patients are more likely to seek treatment.

AI is also “helping researchers diversify clinical trials.”

AI helps ensure that treatments reach patients

Once medications, treatments, and other healthcare products are developed, AI can help ensure that hospitals, clinics, pharmacies, and other healthcare facilities are properly stocked. More specifically, AI helps with supply and demand issues, supply chain logistics, and market trends to help ensure patients can have access to the medications patients need when patients need the medicines the most. For example, AI can help prioritize which locations should be targeted depending on various risk factors.

Another AI application is using ML to understand the progression of different diseases.

AI is helping with operating room efficiency and physician learning

Johnson and Johnson states that their company is using AI to analyze operating room surgical videos to educate physicians, develop research methodologies, and improve quality for medical professionals. With AI, surgeons will be able to “re-watch significant events from their procedures” in a few minutes – instead of waiting hours or days. These videos help the surgeon who performed the surgery and other surgeries who can view the “highlight” videos to learn from other surgeons.

A second benefit of AI in the operating room is that when enough highlight videos are made, AI algorithms can help analyze what “behaviors, tactics, and movements” create positive and negative outcomes during surgery.

Additional AI applications

The US National Institutes of Health (NIH) states that AI is being used in the healthcare profession in the following ways:

  • To provide precision medicine. “Precision medicine provides the possibility of tailoring healthcare interventions to individuals or groups of patients based on their disease profile, diagnostic or prognostic information, or their treatment response.”
  • Genetics-based solutions. “It is believed that within the next decade, a large part of the global population will be offered full genome sequencing either at birth or in adult life. Such genome sequencing is estimated to take up 100–150 GB of data and will allow a great tool for precision medicine.”
  • Drug discovery and development
  • Helping to “visualize” medical data
  • Machine vision for diagnosis and surgery
  • Medical image recognition
  • Augmented reality and virtual reality in the healthcare space
  • Intelligent personal health records. The goal is to allow ample freedom for patients to manage their conditions while freeing up time for clinicians to perform more crucial and urgent tasks. Examples include:
    • Health monitoring and wearable devices
    • Helping computers and humans understand each other better. A few examples include:
      • “Efficient billing: extracting information from physician notes and assigning medical codes for the billing process.”
      • “Authorization approval: Using information from physician notes to prevent delays and administrative errors.”
  • Integrating healthcare records to identify healthcare trends within different disease areas
  • Robotics and artificial intelligence-powered devices to help with minimally invasive surgery, neuroprosthetics
  • Assisted living technologies
  • Smart homes
  • Assistive robots
  • Cognitive assistants
  • Social and emotional stimulation

Many other uses of AI in healthcare are being explored such as using AI to help doctors develop a better bedside practice with their patients.

Artificial intelligence offers exciting opportunities for developing better drugs and treatments. Research applications include creating more relevant and timely clinical trials. Doctors can use AI to learn how to be better doctors. Each application and use of AI software may have FDA, FTC, HIPAA, and other healthcare compliance issues which should be reviewed with an experienced healthcare lawyer.

AI developers and researches, and physicians should contact Cohen Healthcare Law Group, PC to discuss the legal and healthcare compliance requirements of marketing and using artificial intelligence. Our experienced healthcare attorneys advise businesses and medical practices about healthcare compliance laws and regulations.

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