Artificial intelligence (AI) is no longer simply the stuff of sci-fi books and movies. It’s real, and changing the way many industries do business. AI has the potential to help those who work in health care in many ways.
The Drawbacks to Predictive Modeling…and How AI Can Help
Much of patient treatment takes place outside of the clinic. Those with conditions such as diabetes and heart disease must take steps to remain healthy outside of the hospital—but reaching them is tricky. AI can help medical professionals by analyzing data and identifying patients who would benefit from preventative measures.
A startup company called ClosedLoop.ai aims to overcome many of the hurdles health care organizations face in regard to data through the power of AI by offering a solution that involves flexible analytics designed to enable hospitals to enter their own data into machine learning models and instantly get results. Doing so enables them to determine those patients who are most likely to miss appointments, develop complications, benefit from check-ups and more. Health insurers benefit, as well, by using the data to predict factors like patient readmissions and the progression of chronic diseases—information that is otherwise difficult to gather without the use of a crystal ball.
CloudLoop has also created a model that identifies the people most vulnerable for contracting COVID-19 in a particular region and prepare an area for surges in infection. The C-19 Index open source tool provides local resources to high-risk patients and is being used by health care systems to create risk scores. This is a great example of the ways in which AI is making inroads in the health care industry, a trend resulting in better overall patient health.
Predictive models have been around for some time, but machine learning and statistical techniques have been notoriously unreliable in the health care industry. There is no such thing as a one-size-fits-all approach; instead, platforms like CloudLoop use raw data from a specific health care system to easily create patient risk scores and, in the process, come up with a unique model for the organization.
The secret to widespread adoption of AI involves providing simple, actionable insights. By providing care managers with lists, risk scores, and rankings that are easy to access, helping those patients with the greatest need becomes straightforward.
With similar innovations, AI is poised to become increasingly popular in the health care industry even when the COVID-19 pandemic eases.