Since the release of the ChatGPT model, there has been a lot more talk about artificial intelligence. That’s also the case in the medical field. Real-world uses for the algorithms are hinted at by the fact that the ChatGPT AI tool has passed the U.S. medical licensure test, written a number of scientific articles, and is being used to appeal insurance rejections.
The healthcare business might greatly benefit from the use of artificial intelligence-based solutions, yet actual adoption of these products is limited.
According to the current paper, widespread use of AI might reduce healthcare costs by 5–10%, or around $200–360 billion per year. Projections are based on realistic use cases for artificial intelligence that can be realized with existing technology in the next five years without compromising on quality or accessibility.
Hospitals may save money by doing things like streamlining operating rooms or identifying adverse occurrences, both of which enhance clinical operations, quality, and safety. Similar advantages accrue to physician groups who use AI for purposes of care continuity, such as referral management.
Use cases that enhance claims administration, such as automating prior authorization, healthcare and provider relationship management, such as reducing hospital read missions, and provider directory management, will all save money for health insurance.
Within the next five years, private payers might save between $80 billion and $110 billion annually based on the AI-driven use cases. The potential cost reductions for physician organizations range from $3 billion to $60 billion.
The analysis forecasts that annual savings for hospitals may be anywhere from $60 billion to $120 billion.
Doctors’ use of AI for actual patient care is inconsistent, despite the growing interest and investment in the field of artificial intelligence (AI) medicine. Claims that AI may improve clinical outcomes are not backed by strong data, according to a research published in JAMA.
Despite this, the FDA has been moving quickly to approve medical AI technologies, having approved over 520 by the end of November. As more proof of AI’s usefulness in real-world situations becomes available in 2023, experts predict that year will mark a tipping point for its widespread deployment.