A.I. Outshines in Healthcare. At Paperwork.

A.I. Outshines in Healthcare. At Paperwork

A.I. May Someday Work Medical Miracles. For Now, It Helps Do Paperwork. – The New York Times (nytimes.com)

We can’t open the newspapers, science magazines or even turn on the radios these days without AI becoming part of the conversation. Huge strides have been made in the development of machine learning algorithms to generate what is commonly called artificial intelligence (AI).

AI offers considerable benefits particularly when applications generate substantial amounts of data with a high variability. Applications in drug development and chemistry could substantially increase discovery and implementation. Moreover, there has been widespread development and deployment of machine-learning algorithms in medicine, in the form of medical robots to improve patient treatment and recovery and as platforms that facilitate diagnoses and treatment recommendations. But there are concerns about bias and discrimination. Finding ways to develop machine learning without bias and developing AI models that can assess bias and health equity could help maximize the benefits for all.

AI cannot do everything. It cannot smell, it cannot work in a team (questionable) and it cannot reason like a human. But it can help us reach further. This leads me to an article that recently made the front page of the New York Times – “A.I. Outshines in Healthcare. At Paperwork.”

 We have all seen the great visions of super intelligent ChatGPT agents sitting alongside the healthcare professionals dispensing suggestions on how to improve care. But really the present is now and the problems that AI can solve are more mundane. A prime target for instance could be to ease the time-consuming process and burden of digital paperwork that we as physicians must produce, typing lengthy notes into electronic medical records, ensuring our coding is correct or even facilitating patient recalls.

AI has the potential to amplify human strengths, such as leadership and creativity, by providing relevant evidence-based information at the right time. Co-development leads to ‘relevant’ and ‘right time’ being defined in a way that meets the needs of healthcare professionals and of patients. AI can improve flexibility by creating chatbots which enable asynchronous one-to-many correspondences. With co-development, AI functionality and workflows embed the correct safeguards, have appropriate red flag functions, provide continuity, have acceptable clinical safety, avoids increasing anxiety, and have complementary processes supporting healthcare professionals. In an environment with insufficient numbers of healthcare professionals, AI can have a multiplying effect on available resources, such as automating identification of undiagnosed conditions or use digital systems to enable one-to-many remote monitoring. Through co-development we can achieve appropriate clinical oversight, safeguards, and management of risk.