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Can AI make health care more efficient?

People won’t be surprised to learn that AI could improve the accuracy of diagnosis, expedite the rates of drug discovery, or even replace some (or many) activities typically done by doctors. However, can AI save the health care system money? That is the question asked by a recent article in The Economist titled “Can artificial intelligence make health care more efficient? Technology has rarely been able to do so” An excerpt is below.

Economists think technology has been responsible for between 25% and 50% of growth in health expenditure in OECD countries over the past 50 years, growth which has seen the sector’s share of GDP grow relentlessly. In many of those countries it has achieved much. And yet, after decades of costly effort, stories still abound of incompatible it  systems, confidentiality breaches and paper records that need to be held on to in parallel to electronic health records. Is there any reason to think that AI can really sort this out?

There is. And it is offered, in part, by the sheer size of the problem. America spent $4.5 trillion on health care in 2022. That was considerably more than would be expected in comparable countries, and administrative costs accounted for 30% of the excess. Trillion-dollar opportunities can attract the attention of very large companies, such as America’s tech giants. And those companies think their large language models (LLMs) and other big self-supervised-learning systems offer new tools particularly well suited to the job. The fact that the biggest companies in AI see health care as a place to compete is a genuine cause for optimism.

The article cites Google’s MedPaLM2, a health-specific LLM being used to summarize information for patient handoffs between shifts as well as Amazon’s investment in Anthropic’s Claude LLM, which they also want to use for applications in health care.

You can read the full article here.