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Use cases of RPA in healthcare
Robotic process automation is beginning to appear in many industries, including healthcare. Here, an expert discusses RPA use cases in healthcare.
Experts say robotic process automation, which is software with artificial intelligence and machine learning capabilities...
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that essentially automate other software, can be used across many industries. However, it's mainly being used for rules-driven and repetitive back-office work at organizations, including healthcare organizations.
Ascension Health Alliance, the largest nonprofit health system in the United States and based in St. Louis, Mo., is using robotic process automation (RPA) for just that: back-office work. However, A.J. Hanna, executive director of the Ascension Ministry Service Center, which provides human resources, supply chain and finance services to Ascension Health, believes there are other use cases of RPA in healthcare, including revenue cycle management and IoT.
Why do you think RPA for healthcare is important, and do you think it's going to play a bigger role than it already is? What do you think are the top use cases of RPA in healthcare?
A.J. Hanna: I do think it has tremendous potential to expand within healthcare beyond just the normal back-office functions that we do, and ... the primary use case that I see is in [the] revenue cycle.
I worked for a third-party claims organization for about 15 years. As you know, there are code changes -- ICD-9 code changes, code definitional changes, billing code changes and the like -- and it could be easier to train a fleet of robots who are doing repetitive activities and similar activities than it may be [to train] a large human staff. And so I see there being tremendous potential not just for the ability to accommodate change, but because there are a lot of rules-based activities within the revenue cycle process, as well.
I also think that there's some place for the technology to begin to be able to do some comparative looks on medical records. There are technologies that are coming to the fore where there can be some analysis of the differences in the record states and provide some analysis of what those differences were. So I think you'll begin to see more technology applied in EMR [electronic medical records], and those are the two primary areas.
But in terms of RPA, I don't know that anyone has really scratched the surface yet on the clinical operations side of what this technology can do for us, and it's stuff that we're doing right now: Working with the clinical divisions to explore how we might be able to use the technology effectively in those environments, as well.
How widely is RPA being used in the healthcare industry?
Hanna: I do get a lot of requests from all kinds of organizations, but certainly healthcare organizations asking about our process ... how we went about it and how we chose a vendor, how we implemented. [So] it is a growing trend in industry in general.
Any health organizations that are using any kind of business process outsource services are certainly beginning to take a look at this. And then, in the clinical settings ... there are some use cases for IBM and Watson where they've worked with MD Anderson Cancer Center and some other organizations to do some detailed data mining. But I think what we'll begin to see is a movement from that not being the primary thing that health organizations are looking at -- they're going to be looking at other classes of technology, as well, to see how they can build in efficiencies and gain better insights into the work that they're doing.
Is healthcare IoT a good use case for RPA?
Hanna: Absolutely. If you know anything about Moore's law and the idea that our knowledge base and data grows and process and capacity grows exponentially over time, we're really in a shining example of what that means right now. Tools like ... RPA are creating new data insights in ways that we -- some of us -- certainly didn't have access to in the past because of the age of the systems that we're working on or whatever the case may be.
So there's actually new data streams being developed out of this automation effort, and I think that the organizations that are able to capture that data and use it in a meaningful way are going to have the most success.