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The concept of artificial intelligence (AI) is not new and was made a household term years ago, thanks to movies, TV episodes, and books; however, healthcare was perceived too complex to be in the picture. Perhaps the biggest technological factor that brought AI to light in the healthcare field may have been the invention of electronic medical records (EMR) that prompted a new field called health informatics and gave birth to the digitization of health data.
What does this digitization mean? In simple terms, it helps reduce the number of errors associated with clarity and interpretation of information in patient charts, and transform healthcare provider communications into the 21st century. It removes clutter, lowers the cost of care ultimately, and avoids certain types of medical errors. If we think of the EMR’s implications further, making patient information digital allows linking patient information into computer databases and opens doors for complex analytics using information about the patient, other patients with similar characteristics, and a wealth of biomedical knowledge acquired over the years and digitized into computer accessible knowledge base. These analytics help us with a range of new solutions, from churning out predictive outcomes (what is likely to happen to my patient?) to prescriptive solutions (how can I better help my patient based on information I possess?) to delivering the most effective and efficient care (what is the clinically best and financially cost effective treatment for my patient?), to shifting the emphasis of healthcare to prediction and prevention (how can individuals be well-informed of what to do in daily living to prevent certain diseases and maintain health?).
What artificial intelligence is truly capable of doing today is act like a human brain to supply physicians with myriads of care options, medications, and clinical trials available around the globe – then narrow it all down to a few top choices and allow human brain to consider what is best for the patient. Algorithms like neural networks and fuzzy logic are capable of traversing a sea of health information, trained to process and select applicable knowledge in ways similar to a human brain, and churning out solutions much faster than a human even when some of the data elements are missing. And with Big Data – information from individual sources stored in large computer warehouses for analysis – making it possible to access all sorts of knowledge and records, for the first time in history, information from multiple domains of medicine can be linked and used for new purposes. Examples include helping analyze genomic sequences, selecting the most optimal pathways for new drug development, analyzing real world performance of drugs post FDA trial phases in the market, creating cancer treatment plans, accurately matching patients to clinical trials, and detecting financial fraud through medical claims analysis. Humans could perform all of the above tasks, but it takes computers just hours to ingest information using such methods as natural language processing and create meaningful output, compared to months and sometimes years for humans.
Since we seemingly digitized healthcare, possess mountains of electronic patient data, and can produce complex analysis using statistical formulas and algorithms to generate the most effective care plan, the logical question is – when can I make an appointment with my know-it-all computer doctor? Well, let’s not rush to place too many “iRobots” on the hospital floor just yet: modern artificial intelligence solutions are still not as smart and flexible as a human brain, so your community doctor would remain your best expert when it comes to medical care for years to come. In the meantime, you might consider healthcare analytics as an exciting and promising career.
If you are passionate about this new combination of health and information technology, and are ready to change the world, many educational programs such as the Biomedical Informatics program at Nova Southeastern University (NSU) could help you make the transition. At NSU’s Biomedical Informatics Program, you can get started through its new courses in healthcare data analytics that include curriculum in artificial intelligence. These newest additions to an existing innovative medical informatics curriculum are aimed at helping more quantitatively oriented students discover new applications for their talents by developing much needed marketable skills, especially in health analytics.
