very week, Eli Gelfand, chief of general cardiology at Beth Israel Deaconess Medical Center in Boston, wastes a lot of time on letters he doesn't want to write — all of them to insurers disputing his recommendations. A new drug for a heart failure patient. A CAT scan for a patient with chest pain. A new drug for a patient with stiff heart syndrome.
That problem: The U.S. spends more money on healthcare administration than any other country. In 2019,spent on healthcare went to administrative issues like the ones bemoaned by Gelfand. It’s estimated around $265 billion of that was “wasteful” — unnecessary expenditures necessitated by the antiquated technology that undergirds the U.S. healthcare system. Gelfand can use a chatbot to electronically generate an appeal letter..
In an earnings call earlier this month, cofounder and CEO Jeff Tangney was asked how Doximity planned to monetize DocsGPT. “I’ll make a joke here,” he Jain, a former Googler and cofounder of the tech giant’s AI-focused fund Gradient Ventures, says the problem is that every doctor, insurer and health system records information in different formats. Unlike long-suffering health industry employees, AI can very quickly make sense of it. Infinitus has built its own models and doesn’t rely on OpenAI’s technology, but Jain says the underlying premise is the same: “What large language models do is, they say, ‘Throw all that data at us.
ChatGPT was only trained on data available until 2021, and isn’t regularly updated. The field of medicine is constantly changing, with new guidelines, drugs and devices coming on the market, which means outdated data would pose a problem. Shah says he doesn’t see the possibility for broad adoption of generative AI in healthcare until there are systems in place to regularly retrain the models on new information and detect when the answers are wrong.
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