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How generative AI is transforming healthcare

The world is aging. After centuries of relentless growth, many advanced economies are aging, and even in poorer countries the proportion of elderly people is rising. Larger and older populations are placing historic strains on healthcare systems around the world. There are not enough doctors, nurses and other healthcare workers, even as the number of patients increases. Healthcare workers are under constant pressure; many are suffering from burnout and others are planning to leave the industry. According to the New England Journal of MedicineIn 2022, 52% of nurses and 20% of doctors, exhausted by the pressure they were under, said they wanted to leave the sector. Data from the Health Resources & Services Administration (HRSA) shows that, true healthcare workforce shortages have been identified, the United States needs more than 13,023 primary care physicians, 9,926 dentists, and 6,140 mental health physicians. The impact of this is a sharp reduction in the quality of healthcare. Researchers believe that generative artificial intelligence (AI) can be used to improve the quality of care by making it possible to do more healthcare work with the healthcare workforce we have.

Source: HRSA

More than ten years ago, venture capitalist Marc Andreessen said that “software is eating the world”. Since ChatGPT launched in November 2022, generative AI has taken such a place in the cultural consciousness and received so much investment that we can now say AI is eating the world, disrupting industry after industry and offering new use cases from code editing to writing essays. Healthcare has not been left behind. While AI has been around for decades, so much so that researchers joke that AI is something that can’t be done until it can be done, generative AI brings something completely different. Scientist Stephen Wolfram explained that,

‘The first thing we need to explain is that what ChatGPT is always fundamentally trying to do is produce a “reasonable continuation” of whatever text it has so far, where by “reasonable” we mean “what you would expect someone would write after seeing what people have written on billions of web pages, etc.”

In other words, ChatGPT and generative AI tools in general make probabilistic predictions of what should appear, based on training data that today essentially spans the entire Internet. Generative AI produces content without understanding what that content is. Generative AI can be trained on very specific personal, business, or academic data, reducing computing needs and costs while providing specialized technology. The average hospital produces 50 petabytes of data per year, or 137 terabytes per day, and given the increase in the amount of technology in use, the collection of patient-generated health data, and the universal use of electronic health record (EHR) systems, the amount of data generated has increased by a speed of 47% per year.

In a report on use cases of generative AI in healthcareMcKinsey gave the example of a ChatGPT-enabled technology that adds patient information to a mobile platform in real time. A doctor records a patient’s visit and the platform talks to the doctor to fill in any gaps, converting the conversational language into a structured note. After the visit, the physician can edit the notes by voice or typing before sending the notes to the patient’s EMR. This reduces the friction of note-taking and speeds up administrative work, freeing up the doctor for the actual practice of healthcare. That example reflects the ability of generative AI to take unstructured data sets, analyze them, and convert them into structured content. For example, that patient’s EHR can quickly be attached to an insurance claim.

Overall, companies like Mercy Health and Intermountain Healthcare have developed generative AI-enabled platforms to automate bookings, patient registration, prescription refills, and other administrative tasks. Mercy Health, for example collaborated with Microsoft developing a tool to communicate laboratory results, schedule appointments, provide patient recommendations and, for its employees, provide HR services and information about company policies and procedures. Mercy Health $30 million saved by 2023 Thanks to these instruments, savings can be used to improve the quality of healthcare.

Generative AI-enabled technologies can be used to guide patients through treatments for simple health problems, with patients referred to the doctor for more serious or complex problems. This would allow doctors to focus on more serious cases and patients to receive prompt treatment for simple health problems. Sanofi, the French pharmaceutical company, has done this and also collaborated with OpenAI, the non-profit organization that developed ChatGPT, to aid in drug discovery. The CEO of the company, Paul Hudson, said that,

“This unique collaboration is the next important step in our journey to become a pharmaceutical company largely powered by AI. The next generation, unique AI model adaptations will provide an important foundation in our efforts to shape the future of drug development for the pharmaceutical industry and for the many patients awaiting innovative treatments.”

Not only is generative AI used on the platform to aid in treatments, they also believe that generative AI can be used to refine the models, which makes sense considering that generative AI is quite good at coding and debugging code. Generative AI seems to shine in these types of jobs.

It remains to be seen how far this revolution can go. I think a crucial element will be getting better data. We’ve already seen a slowdown in generative AI progress after they’ve essentially trained themselves on all publicly available data. The next step in progress will require improving that data to deepen insights and open new use cases.

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