Imagine booking an appointment with your doctor about an ache or pain, and describing your symptoms to her as she notes your concerns. After listening to you, she inputs your symptoms into her computer, which directs her to the latest research she might need to know about how to diagnose and treat your problem.
Next, she orders an MRI, reviewing the scans with the help of a computer to detect any problems that could be too small for a human to see. Finally, she reviews a treatment protocol recommended by program that has reviewed your medical records and family history, tailoring suggestions to your specific circumstances.
Sound like dreams of a distant future? It shouldn’t. These are all capabilities within the reach of today’s clinical decision support systems, computer programs designed to help healthcare professionals make decisions about diagnosis and treatment.
Clinical decision support systems are interactive systems that, with correct use, are better than the doctor alone in making decisions because of their enhanced capacity for information storage and processing. These system have been used for many years in hospitals but, with recent developments in the power of AI, they are on track to become the star of the team.
One of the more widely-known applications of a clinical decision support system is the use IBM’s Watson to help oncologists make the best clinical decisions for their patients. The tool helps doctors evaluate and compare treatment options for different types of cancers, and helps doctors choose the right treatment plan for an individual patient. Ultimately, the goal is to improve clinical outcomes and increase survival rates for cancer patients while still reducing treatment costs for providers.
While we are still in the early stages of complex AI clinical decision systems, applications of systems like IBM’s Watson point to a promising future that will benefit patients and providers alike.