AI is often discussed in terms of being a game changer when it comes to a host of problems in healthcare. But it may actually be more accurate to consider it one multi-faceted component in an array of automation technologies emerging across the healthcare system.
Take a recent commentary at HIT Consultant by Jason Warrelmann is the Global Director of Healthcare and Life Sciences at UiPath, a Romanian developer of Robotic Process Automation (RPA) software.
As he sees things, the clinical possibilities for AI may get most of the buzz, but where doctors – and, by extension, the patients they want to care for – could really use help is on the administrative side of healthcare, as in tasks like data and managing patient records.
“RPA software allows users to configure ‘bots’ to take on repetitive tasks by emulating and integrating the actions of a human within digital systems to perform a business process,” he argues, “eliminating often repetitive tasks from a person’s workload. In healthcare, RPA could be used to help facilitate appointments, manage billing and find and copy records, saving providers time and resources.”
The problem is, he says, providers still aren’t interested in RPA to the extent they should be.
Indeed, “a recent study found that only 59 percent of healthcare professionals say RPA is an essential priority for them. While this number is more than half, it is almost ten percentage points lower than other industries. The same study found that employee resistance was the greatest barrier of RPA in healthcare.”
And the reason for that indifference, he argues, is that providers are still too susceptible to a few myths, which he aims to debunk. One of those is that RPA is nothing but a successor to early automation tools that didn’t work out, while another is that healthcare already has enough process automation tools.
But, from a strictly AI perspective, the interesting part of Warrelmann’s argument is how he portrays RPA as a necessary next step on the road to widespread use of AI in healthcare.
For example, take the challenge of providing adequate and accurate data which can be put to use “teaching” AI algorithms.
As Warrelmann sums it up, “(t)o ensure data integrity, providers must understand data flows and know the end goal of the process to be able to get from point A to point B. RPA forces businesses to look at their processes and helps make them more efficient. RPA works across systems and bridges the gap between legacy healthcare technology and the next wave of AI-informed solutions. Through RPA, old and new systems can work in sync to ensure that data is not lost and processes run optimally. Once in place, digital workers can quickly and accurately collect (and correct) data, ensuring that AI, once introduced, can reach its full potential.”
The bottom line for Warrelman is that healthcare providers are going to increasingly challenged with managing inventory, digitizing patient files and claims processing while trying to serve an increasing number of patients.
Thus, “RPA could play a major role in eliminating repetitive manual tasks, while also uniting disparate systems, giving healthcare professionals much-needed time back to focus on what they do best: care for patients.”