As providers continue to be bogged down by clinical documentation and technology requirements in the revenue cycle process, 3M’s mission is focused on alleviating some of those burdens with the use of artificial intelligence.
Jared Sorenson, vice president of 3M’s revenue cycle solutions business, told Becker’s Hospital Review that despite there being hype around AI and the idea it will eliminate the human element in business, there are also very real uses of the technology in healthcare.
In care delivery specifically, AI is helping assist clinicians with efficiency and quality of clinical documentation, so they are able to spend more time interacting face to face with patients. Downstream in the revenue cycle, AI is driving prioritization for CDI and Quality reviews and improving accuracy, compliance, and productivity through computer-assisted coding.
“We want to reduce the burdensome technologies may have brought to clinicians and streamline workflows to create time to care for their patients,” Mr. Sorenson said.
Here, Mr. Sorenson discusses 3M’s mission to alleviate tech burdens in the revenue cycle and how AI will continue to evolve and optimize the process.
Editor’s note: Responses have been lightly edited for clarity and length.
Question: Before we launch into a discussion of AI, there are some real and serious issues facing the healthcare industry as a result of COVID-19. If you could share one thing with your health system clients right now, what would that be?
Jared Sorenson: That we have their back, and are committed to supporting our clients in every way we can. We recognize there are a lot of people on the front lines of this fight against COVID who are putting themselves at risk and trying to help those who are seriously ill. We are doing all we can to make sure that any regulatory changes, new codes, and other directions from CMS are included in our revenue cycle and physician-assistive solutions. We’re just making sure we can keep that as up to date as possible. For example, we are providing COVID-19 specific templates to use with our speech recognition solution and AI-powered COVID-related education with our computer-assisted physician documentation (CAPD). There’s a bit of a symbiotic relationship between healthcare and 3M in general – what 3M Health Information Systems, as a division, does to help on the health information management side with capturing accurate and consistent coding and documentation, along with what other divisions of 3M do to supply medical masks and other supplies. We want to help in any way we can.
Q: Moving to AI in the revenue cycle, there is a lot of noise around AI. What do you consider real and what is hype?
JS: What is real is that AI is happening, from healthcare tools and technology to the wider spaces like self-driving cars and consumer applications. In healthcare, there are very real models developing to identify clinical understanding. Creating a better picture of potential diagnoses and conditions through AI technologies helps drive efficiency in the revenue cycle so that we can boost the productivity of those who are evaluating cases for clinical documentation improvement, coding, or quality. All of that is real, and it is driving AI capabilities within the health system.
What is hype is maybe the perception that AI will solve all of our problems immediately, and that we’ll be able to automate at the touch of a button things that are handled today by people with clinical training and knowledge who are reviewing the case? The idea that AI is just going to remove that need and eliminate the human element is hype. There will always be an interactive relationship between what AI can do to process information and how that intelligence aids a human reviewer, or user who applies their critical knowledge to what AI is telling them, to then do their work more efficiently. Will we get to a stage where more automation is possible? Absolutely. But I think right now there is also a very important relationship between AI and the human element.
Q: What is 3M’s mission and what differentiates it from other companies?
JS: What makes us unique is that we are a partner not only to the provider community in health organizations and hospitals across the country, but we’re also very tightly aligned with the payer community. We work a lot with CMS, state Medicaid agencies, and commercial payers. So, in a sense, we have to walk a very balanced line on making sure that in the revenue cycle phase we are complete, compliant, and accurate. A provider should get paid every dollar they deserve, and a payer shouldn’t pay a penny more than appropriate. We have to walk that fine line of accuracy and be a trusted third party to our partners. We don’t pick sides in that regard.
In doing so, we have our business structured so that we have solutions for the revenue cycle based on the provider organizations. We also sell some of those solutions into the payer space and drive their initiatives more around value-based care. What has expanded that mission in the past year and a half is our acquisition of M*Modal to be part of our organization? This really drives a focus on the clinicians themselves. Our speech and AI-powered clinician-assistive solutions drive our mission of creating time to care by making bringing clinical intelligence in their workflow for more accurate documentation.
Q: In the revenue cycle, the C-Suites’ dream is fully autonomous clinical documentation capture, coding, and clean claims without denials—will this ever occur?
JS: This is a dream we share. For us to really be able to deliver automation, I see it starting in two ways. The first is pure automation—understanding clinical documentation and codes to realize a direct to bill model. There are segments in the revenue cycle where we are using this type of automation, such as radiology, using AI technologies to read the documentation and apply codes straight to a claim out the door. We would say there’s a larger slice of the services in healthcare that could qualify for this model today, so there is potential to expand. Simple, standard procedures should move in this direction with the goal to increase the range of services that we can automate. The other is, automating the priority factors for individuals who need to review a case so that they are reviewing cases more by exception rather for every single one. There is an AI that drives prioritized case review, which will continue to become more accurate and standard practice.
Q: Anything else to add?
JS: The last comment I would make about automation is to deliver true automation with a clean claim that is acknowledged and paid by the insurer—I don’t know that it will ever be achieved until there is a more cohesive or better sharing of information between the provider side of the house and the payer side of the house. Arguably today, when a case is put through the revenue cycle on the hospital side and it’s put out on a claim, the same processes of review and recoding the case often happens on the payer side. The vision is that true automation would bring those sides together, to where providers and payers are really looking off the same sheet of music, and they’re able to see and review the evidence delivered by AI that justifies a claim in the revenue cycle space. When we can reach that point—and AI will help us get there—then the process is less of a back and forth affair between payers and providers and it becomes a system of record for agreement between the two.