Florence Joffroy-Black and Dave Sheppard, MedWorld Advisors05.09.23
Recent headlines from tech industry giants have spawned an interesting debate about the use of artificial intelligence (AI) in overall society and in healthcare.
“AI stresses me out,” Tesla CEO Elon Musk said at a March 1 investor day event for his firm. He is a co-founder of OpenAI and his automobile manufacturing company uses AI for an autopilot system. “It's quite dangerous technology. I fear I may have done some things to accelerate it.”
In late March, Musk joined other industry bigwigs in calling for a six-month pause in developing AI systems more powerful than OpenAI’s GPT-4, its newest language model that powers applications such as ChatGPT and the new Bing. “Contemporary AI systems are now becoming human-competitive at general tasks, and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization?” the group of tech titans asked in March 22 open letter. “Such decisions must not be delegated to unelected tech leaders. Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system's potential effects.”
As we gain more experience negotiating and closing AI healthcare-related deals, Musk’s statement and the open letter raise an interesting issue—is AI helping medtech manufacturers and developers achieve greater patient outcomes or is it more of a risk to human health?
In considering this question, we’ve compiled eight arguments that support AI utilization in healthcare. They include:
Improved Accuracy and Precision: AI can identify patterns that are difficult for humans to detect, leading to more accurate diagnoses and treatment plans.The potential benefits are many, including personalized medicine (the next supportive argument).
Personalized Medicine: AI can help physicians tailor treatment plans to patients’ unique needs. Obviously, such customization is only possible through the mind-blowing software being developed by life sciences companies that enhance their medical technology offerings.
Predictive Analytics: AI algorithms can identify potential health risks and calculate the likelihood of certain patients being more “at risk” for certain conditions. These algorithms can also help to predict which patients are more likely to benefit from certain types of treatments, procedures, medications, etc.
Patient Engagement: AI-powered chatbots can help patients better understand their health conditions and treatment plans, leading to better engagement and improved outcomes. Amazingly enough, some of these chatbots already in use are helping patients battle severe mental health issues like anxiety and depression, all while using clinically proven methodologies with established efficacy.
Remote Patient Monitoring: AI allows patients to be monitored remotely, thereby allowing healthcare professionals to track various conditions and recoveries in real-time. Some of these algorithms go so far as to help patients avoid broken bones and other debilitating conditions by predicting when they may be at risk of falling.
Medical Imaging: AI can help analyze medical images such as X-rays, computed tomography, and magnetic resonance imaging to identify potential abnormalities and assist physicians in diagnoses; or help surgeons with navigation, robotics, and automated planning.
Reduced Healthcare Costs: By automating many tasks, AI can improve the healthcare system’s efficiency and reduce costs. Whether it is simple task management or more complex assignments, software can help complete time-consuming activities in a transparent and efficient manner.
Improved Patient Outcomes: By improving diagnostic accuracy while also creating more personalized treatment plans, AI can improve patient outcomes as well as reduce adverse advent risks. This is already occurring across multiple levels of medical treatments and applications. As the healthcare worker shortage continues AI could ultimately help fill some of the void, thus benefitting patients.
The benefits of these technologies are clearly evident in some of the M&A transactions that have transpired in recent months. Over the last six months, Bayer has purchased Blackford Analysis and its radiology software solution (Blackford Platform); GE HealthCare agreed to buy Imactis, a French firm whose CT navigation system helps surgeons in minimally invasive procedures; and Beckman Coulter acquired StoCastic, an AI firm that provides evidence-based decision support for hospital emergency departments.
There are, of course, downsides to developing AI too quickly in healthcare applications. Some of those reasons follow:
Data Bias: AI algorithms rely on data to make decisions. If the data is biased, however, the algorithm’s output may also be biased, which could lead to disparities in results and outcomes for some patient cohorts. It’s helpful to note that awareness about this bias potential has increased; hopefully, this will minimize its impact remove it completely.
Lack of Human Oversight: It’s entirely possible for AI algorithms to make mistakes if not trained properly. Without human supervision, some of these errors could have major impacts on patient health and safety. While “closed-loop” systems are the most efficient, there will need to be a high degree of efficacy for any type of closed-loop solution to be implemented without the ability for quick human intervention. AI does not replace human involvement unless humans have verified the implementation results.
Ethical Concerns: If AI is ultimately going be utilized to make “life or death” choices or some other type of serious decision on a patient’s behalf, there are ethical considerations that must be addressed. On a personal level, a patient might prefer true data (from AI) to inform family members about possible outcomes as opposed to a highly fallible (yet educated) physician’s recommendations. Of course, there must be some assurance that the AI was validated appropriately.
Privacy Concerns: Most everyone has been impacted by some type of data breach. But healthcare’s digitization has increased the risk of exposing patient data and breaching personal privacy, which more often than not lead to harmful outcomes. It’s going to be important that industry gains confidence in securing patient data.
Regulatory Challenges: Historically, there have been few regulations relating to healthcare AI. But recently, the U.S. Food and Drug Administration has become more involved in an attempt to ensure that AI is used safely and effectively. It remains to be seen how the positive uses of AI are balanced with some of its known risks and the ways in which regulatory authorities will manage this defining line.
AI has the potential to revolutionize healthcare delivery. The possibilities are truly endless for improving both the manner and form of treatments for some of today’s most challenging medical conditions. As Musk noted, artificial intelligence is not without its risks but the benefits far outweigh the danger. Musk has confidence in the technology, as AI factors heavily into his own core businesses.
Since AI is likely to greatly improve patient outcomes and safety, it is important the healthcare industry continues to explore its potential applications while also addressing its potential risks. As with any technology, it is important that AI is used responsibly and ethically, with a focus on improving patient outcomes while providing high-quality, compassionate results.
Florence Joffroy-Black, CM&AA, is a longtime marketing and M&A expert with significant experience in the medical technology industry, including working for multi-national corporations based in the United States, Germany, and Israel. She currently is CEO at MedWorld Advisors and can be reached at florencejblack@medworldadvisors.com.
Dave Sheppard, CM&AA, is a former medical technology Fortune 500 executive and is now focused on M&A as a managing director at MedWorld Advisors. He can be reached at davesheppard@medworldadvisors.com.
“AI stresses me out,” Tesla CEO Elon Musk said at a March 1 investor day event for his firm. He is a co-founder of OpenAI and his automobile manufacturing company uses AI for an autopilot system. “It's quite dangerous technology. I fear I may have done some things to accelerate it.”
In late March, Musk joined other industry bigwigs in calling for a six-month pause in developing AI systems more powerful than OpenAI’s GPT-4, its newest language model that powers applications such as ChatGPT and the new Bing. “Contemporary AI systems are now becoming human-competitive at general tasks, and we must ask ourselves: Should we let machines flood our information channels with propaganda and untruth? Should we automate away all the jobs, including the fulfilling ones? Should we develop nonhuman minds that might eventually outnumber, outsmart, obsolete and replace us? Should we risk loss of control of our civilization?” the group of tech titans asked in March 22 open letter. “Such decisions must not be delegated to unelected tech leaders. Powerful AI systems should be developed only once we are confident that their effects will be positive and their risks will be manageable. This confidence must be well justified and increase with the magnitude of a system's potential effects.”
As we gain more experience negotiating and closing AI healthcare-related deals, Musk’s statement and the open letter raise an interesting issue—is AI helping medtech manufacturers and developers achieve greater patient outcomes or is it more of a risk to human health?
In considering this question, we’ve compiled eight arguments that support AI utilization in healthcare. They include:
Improved Accuracy and Precision: AI can identify patterns that are difficult for humans to detect, leading to more accurate diagnoses and treatment plans.The potential benefits are many, including personalized medicine (the next supportive argument).
Personalized Medicine: AI can help physicians tailor treatment plans to patients’ unique needs. Obviously, such customization is only possible through the mind-blowing software being developed by life sciences companies that enhance their medical technology offerings.
Predictive Analytics: AI algorithms can identify potential health risks and calculate the likelihood of certain patients being more “at risk” for certain conditions. These algorithms can also help to predict which patients are more likely to benefit from certain types of treatments, procedures, medications, etc.
Patient Engagement: AI-powered chatbots can help patients better understand their health conditions and treatment plans, leading to better engagement and improved outcomes. Amazingly enough, some of these chatbots already in use are helping patients battle severe mental health issues like anxiety and depression, all while using clinically proven methodologies with established efficacy.
Remote Patient Monitoring: AI allows patients to be monitored remotely, thereby allowing healthcare professionals to track various conditions and recoveries in real-time. Some of these algorithms go so far as to help patients avoid broken bones and other debilitating conditions by predicting when they may be at risk of falling.
Medical Imaging: AI can help analyze medical images such as X-rays, computed tomography, and magnetic resonance imaging to identify potential abnormalities and assist physicians in diagnoses; or help surgeons with navigation, robotics, and automated planning.
Reduced Healthcare Costs: By automating many tasks, AI can improve the healthcare system’s efficiency and reduce costs. Whether it is simple task management or more complex assignments, software can help complete time-consuming activities in a transparent and efficient manner.
Improved Patient Outcomes: By improving diagnostic accuracy while also creating more personalized treatment plans, AI can improve patient outcomes as well as reduce adverse advent risks. This is already occurring across multiple levels of medical treatments and applications. As the healthcare worker shortage continues AI could ultimately help fill some of the void, thus benefitting patients.
The benefits of these technologies are clearly evident in some of the M&A transactions that have transpired in recent months. Over the last six months, Bayer has purchased Blackford Analysis and its radiology software solution (Blackford Platform); GE HealthCare agreed to buy Imactis, a French firm whose CT navigation system helps surgeons in minimally invasive procedures; and Beckman Coulter acquired StoCastic, an AI firm that provides evidence-based decision support for hospital emergency departments.
There are, of course, downsides to developing AI too quickly in healthcare applications. Some of those reasons follow:
Data Bias: AI algorithms rely on data to make decisions. If the data is biased, however, the algorithm’s output may also be biased, which could lead to disparities in results and outcomes for some patient cohorts. It’s helpful to note that awareness about this bias potential has increased; hopefully, this will minimize its impact remove it completely.
Lack of Human Oversight: It’s entirely possible for AI algorithms to make mistakes if not trained properly. Without human supervision, some of these errors could have major impacts on patient health and safety. While “closed-loop” systems are the most efficient, there will need to be a high degree of efficacy for any type of closed-loop solution to be implemented without the ability for quick human intervention. AI does not replace human involvement unless humans have verified the implementation results.
Ethical Concerns: If AI is ultimately going be utilized to make “life or death” choices or some other type of serious decision on a patient’s behalf, there are ethical considerations that must be addressed. On a personal level, a patient might prefer true data (from AI) to inform family members about possible outcomes as opposed to a highly fallible (yet educated) physician’s recommendations. Of course, there must be some assurance that the AI was validated appropriately.
Privacy Concerns: Most everyone has been impacted by some type of data breach. But healthcare’s digitization has increased the risk of exposing patient data and breaching personal privacy, which more often than not lead to harmful outcomes. It’s going to be important that industry gains confidence in securing patient data.
Regulatory Challenges: Historically, there have been few regulations relating to healthcare AI. But recently, the U.S. Food and Drug Administration has become more involved in an attempt to ensure that AI is used safely and effectively. It remains to be seen how the positive uses of AI are balanced with some of its known risks and the ways in which regulatory authorities will manage this defining line.
AI has the potential to revolutionize healthcare delivery. The possibilities are truly endless for improving both the manner and form of treatments for some of today’s most challenging medical conditions. As Musk noted, artificial intelligence is not without its risks but the benefits far outweigh the danger. Musk has confidence in the technology, as AI factors heavily into his own core businesses.
Since AI is likely to greatly improve patient outcomes and safety, it is important the healthcare industry continues to explore its potential applications while also addressing its potential risks. As with any technology, it is important that AI is used responsibly and ethically, with a focus on improving patient outcomes while providing high-quality, compassionate results.
Florence Joffroy-Black, CM&AA, is a longtime marketing and M&A expert with significant experience in the medical technology industry, including working for multi-national corporations based in the United States, Germany, and Israel. She currently is CEO at MedWorld Advisors and can be reached at florencejblack@medworldadvisors.com.
Dave Sheppard, CM&AA, is a former medical technology Fortune 500 executive and is now focused on M&A as a managing director at MedWorld Advisors. He can be reached at davesheppard@medworldadvisors.com.
