The Cost of Care: How AI is Revolutionizing Healthcare and Driving Down Prices
The cost of healthcare is once again at the center of a national debate. With premiums rising, the baby boomers aging, and diabetes, the most expensive disease in the world, affecting 10% of the US population, the rising cost of healthcare in America is an issue that affects all of us. In the past, the implementation of new and emerging technologies in healthcare has contributed to the climbing costs. In contrast, the application of AI into healthcare is promising to drive those costs down.
Healthcare is an enormously expensive industry and the costs are steadily climbing. According to World Book, in 2014 healthcare made up 17.1% of the GDP of the United States– up 4% from 1995, and continuing to grow. The application of artificial intelligence into healthcare is promising to greatly reduce these expanding expenses while improving healthcare quality and access. By 2026, it’s estimated $150 billion could be saved annually in the US healthcare economy by AI applications. It’s no wonder that healthcare is currently the number one investor in AI.
One of the areas in healthcare that will be most significantly impacted by the application of artificial intelligence is clinical documentation. AI applications in medical workflow management are estimated to accumulate $18 billion in annual savings for the healthcare industry by 2026, the third largest estimated savings from AI technology in healthcare after robotic surgery and virtual assistants. Modern healthcare AI is capable of learning and comprehending and can perform clinical healthcare functions in much the same way as a human, minus human error.
Physician error in clinical documentation is an understandable yet costly complication in healthcare, and AI is able to streamline the tedious clinical documentation process and automatically generate accurate and complete reports. Many AI healthcare programs are capable of fully augmenting human behavior and can perform tasks from risk analysis to patient diagnosis. Physician engagement in clinical documentation is a critical component to the quality and costs of healthcare, and AI applications are proving to increase physician engagement and improve clinical documentation quality.
With so much potential to improve not only healthcare costs, but also access and quality, the AI health market is currently experiencing a boom, and is expected to grow into a $6.6 billion dollar industry by 2021. This growth makes sense when you consider that the nation and the world are currently facing a shortage of doctors and healthcare personnel, and AI offers hospitals and physician practices a way to combat their rising operational and labor costs, while enabling them to better perform critical administrative functions quickly, accurately, and cost effectively.
Artificial Intelligence seems like the wave of the future, but the reality is, the future is here. In today’s medical environment of value-based care, appropriate reimbursements are incumbent upon accurate, high quality clinical documentation. As AI continues to grow and evolve, AI enabled clinical documentation improvement technology will continue to transform the healthcare industry, improving patient outcomes and optimizing revenue.
Clinical documentation is one of the more tedious tasks that doctors are faced with and is a heavily contributing factor in the rise of physician burnout. In the constantly evolving and data driven world of healthcare, AI is experiencing a boom. The application of AI technologies is revolutionizing the way clinical documentation can be generated in the context of patient treatment and AI is able to identify crucial information that can become lost in the clinical documentation process among the enormous amounts of information and data getting fed into EHR systems. This application is assisting physicians and healthcare workers in identifying missing or unclear data in electronic medical records streamlining the clinical documentation process and freeing up doctor’s time to focus on patients. 