So, what is AI in healthcare? AI in healthcare refers to a tool or set of tools that, with some level of autonomy, helps resolve business challenges, uncover business insights and automate repeated tasks to free people up to apply their skills to other more productive tasks. AI in healthcare enables humans to spend more time on strategic, value-added activities that computers still can’t handle, like maintaining a strong relationship with the other participants in your ACO or taking your client’s AP manager to lunch.
2. What is AI not (yet)? Understanding how to incorporate AI solutions in a healthcare environment requires developing a common understanding of AI capabilities and limitations and, perhaps most importantly, understanding what challenges can and cannot be addressed with AI solutions.
Artificial Intelligence is not magic. It’s not one size fits all. It won’t solve fundamental business issues and it won’t solve fundamental people or process challenges. It may self-improve and self-correct over time, but AI is built by humans and limited by humans.
One of the most recognizable issues with AI is the learning bias problem, in which human bias is transmitted to the system via the selection of data sets and the logic structure of the system’s algorithms. Over time, these omissions and influences can amplify, creating the possibility of serious negative outcomes.
As much as AI is enabled and built by humans, it is not always capable of providing a response sufficient for human understanding. AI presents what we call the “black box problem” in which the system is unable to provide a human-context explanation of why a decision was made – it is unable to “show the math”. This deficiency is less of an issue when the struggle is to understand why your AI tool is transposing call center data into your system. It’s a much bigger issue when it is determining what drugs should be administered in a NICU.
3. Common challenges that AI can address There are many areas where AI can provide real automation and efficiencies that significantly and positively affect healthcare organizations. Healthcare professionals spend an inordinate amount of time recording, managing and interpreting data from a variety of systems such as off-the-shelf systems, electronic health record systems or customer relationship management tools. The time spent on translating data is time away from patient care and other activities necessary to run a successful business. Considering all that’s required in every medical setting, AI can help solve challenges such as:
