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Podcast: Technology improves clinical validation to help prevent denials

Our podcast today is about clinical validation and how technology can help address this increasingly important area of focus to aid in denial prevention.

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Tracy Morris:

Welcome to another edition of our Optum360 podcast series. I'm Tracy Morris, a marketing director at Optum360. Our podcast today is about clinical validation and how technology can help address this increasingly important area of focus. I'm joined today by colleagues, Anne Robertucci, product director, and subject matter expert in health information management and Mark Morsch, VP of technology and subject matter expert in artificial intelligence and natural language processing. Welcome, Annie and Mark.

Anne Robertucci:

Thanks Tracy. Happy to be here.

Mark Morsch:

Great to join you today Tracy.

Tracy Morris:

Annie, I'd like to start with you, with a two-part question. First, can you define clinical validation? And secondly, tell us why it's becoming an increasingly important area of focus for organizations?

Anne Robertucci:

Yes, Tracy. First off, clinical validation means that the diagnosis documented in a patient's record is substantiated by clinical criteria, generally accepted by the medical community. That clinical criteria can come from places like professional guidelines or evidence-based sources. Clinical validation has become an increasing area of importance for healthcare and more specifically, for clinicians, clinical documentation or what we'll call CDI auditing and health information management departments. Payers and auditors apply that clinical validation criteria to submitted claims to ensure that they're supported by widely accepted clinical criteria. Those lacking clinical substantiation may result in reduced payments or denied claims. In a recently published survey by [Actis 00:01:45], participants indicated as much as 46% of their organizations' denials fall into the clinical validation bucket.

Tracy Morris:

That's an incredible statistic showing the prevalence of clinical validation reviews or audits by payers in the industry today. Can you tell me how organizations are addressing clinical validation reviews?

Anne Robertucci:

Absolutely Tracy. CDI and coding programs across the industry have started to incorporate clinical validation reviews either at the point of care or at the time of coding in an attempt to reduce those denials post claim submission. Unfortunately, for many it's a manual process to identify the cases that fall into that at-risk bucket and require secondary review to determine if the provider documentation is supported by the clinical facts in the record. In the past, there was also a debate on who can identify and query a physician for clinical validation. While many CDI departments have responsibility for clinical validation queries, who can send a clinical validation query will vary by setting an organization. Many organizations support both CDI and coding professionals as authors of clinical validation queries. And one other interesting caveat is that some organizations struggle with querying the provider and coming across as questioning medical judgment. Tackling appropriate queering of a provider related to clinical validation is really a balancing act for CDI specialists and coders. One thing's for sure though, strong workflow and automation is necessary to help support the scope of work for both CDI and coding professionals.

Tracy Morris:

Thanks Annie. I'd like to bring in Mark now. Mark, we've heard a lot of buzz in the market about natural language processing or commonly referred to as NLP, a type of artificial intelligence or AI. How can technology like this help address clinical validation reviews?

Mark Morsch:

Well, you're right, Tracy. There's a tremendous buzz in the market about artificial intelligence and natural language processing in healthcare. These technologies have a big impact in areas such as the middle revenue cycle. And Optum was an early developer of solutions like computer assisted coding that utilize advanced NLP to assign codes, both diagnosis and procedure codes. These solutions started out in the physician market and as specialties such as radiology and emergency medicine and group support complex hospital coding as well as clinical documentation improvement. Optum clinical NLP, has the capability to both recognize the definitive documentation of coding as well as the clinical concepts, the defined conditions and procedures and using NLP to recognize the markers of disease, those clinical concepts it's possible to recognize when the clinical evidence supporting condition is documented.

Mark Morsch:

This type of artificial intelligence, which we call case finding, allows very precise identification of records with documentation weaknesses, helping CDI specialists, zero in on the most important opportunities. Our process of continuous development investment has yielded advanced applications and physician hospital coding, clinical documentation improvement as well as quality measures and utilization management. Clinical validation is a latest, innovative application of our clinical NLP to ensure and really build the integrity of medical record documentation.

Tracy Morris:

Without getting too technical Mark, can you describe to our audience how this works?

Mark Morsch:

Sure. Clinical validation is about finding the gaps in the patient's story. A good comparison is coding. You can think about NLP for coding as recognizing what was clearly stated by the physician in the documentation. With clinical validation, Optum NLP looks deeper into the supporting evidence, including laboratory results, vital signs, and key findings. Then understand what the physician didn't say. Clinical validation utilizes the case finding technology developed for CDI. Case finding identifies that clinical evidence inside the medical record, related to specific conditions and compares that evidence to definitive documentation.

Mark Morsch:

For example, in a patient record where the physician documented acute respiratory failure, the NLP will look for a range of clinical evidence, including pulse oximetry, respiratory rate, blood gas results, and symptoms such as shortness of breath and stridor and even treatment like supplemental oxygen. All of that evidence paints a picture, a clinical picture of the underlying disease. With case finding technology, validation can proactively recognize if the clinical picture is not fully consistent with the coded diagnosis. It's a great example of AI that captures clinical indicators and marries the thinking of coding and clinical reasoning. The centrality that encompasses this case finding is also fully transparent with clear traceability back to the supporting evidence in the medical record. That traceability to the underlying evidence really helps CDI specialists in justifying and explaining queries.

Tracy Morris:

Mark, NLP and AI technologies are advancing rapidly. How can healthcare leaders be confident that they will see a benefit?

Mark Morsch:

NLP and AI technologies are definitely advancing rapidly. And there's a level of hype around those technologies. We at Optum, are focused on applying these advances to deliver significant value to our clients. It means being critical at every step of our development to ensure that technology is truly delivering what experts like Annie and her team expect. We strive to deliver on results, not just on hype. To deliver a capability like clinical validation requires a deep understanding of the evidence within records, models that effectively capture and weight that evidence and reasoning that connects the evidence to a specific diagnoses or procedures. This all requires extensive data to learn from as well as expansive knowledge of medical specialty guidelines. We believe that the integration of CDI case finding along with NLP driven coding, all powered by the same underlying clinical NLP technology, is a differentiator for CDI and health information management teams.

Tracy Morris:

Thanks Mark. I'd like to loop Annie back in at this time. Annie as product director of Optum CAC and CDI technology, NLP powers or enables your solutions. Can you tell me how it's helping teams work smarter and better together?

Anne Robertucci:

Absolutely Tracy. NLP is a powerful instrument and has transformed the way we do business in a real time nature for both coding and CDI. It's critical to ensure the documentation at the point of care is accurate. And by getting it right up front, we create great efficiencies. For example, NLP drives the CDI specialist to review the right charts at the right time, through that automated case finding. In addition, with the power of NLP code suggestion, not only does it drive efficiency gains for the coder, but it also reduces the CDI specialist's time to conduct an initial review by suggesting the working DRG based on those same codes. Our platform also breaks down silos between key departments and ensures coding and CDI are aligned appropriately.

Anne Robertucci:

With our quality case finding, the technology drives collaboration with quality departments as well. So many things in healthcare are driven from complete and accurate documentation and coding. Through the accurate reporting of quality events, to collection of key social determinants of health for population health, as well as research initiatives. The benefits are really incredible once you connect the codified story to the key clinical facts within a record, from identifying gaps, missing diagnosis and potential quality events. And now with what Mark has done with clinical validation, all of these capabilities support the common goal for CDI and coding, of timely, complete, and accurate documentation, coding and reimbursement. And of course, working to get it right up front to help with those downstream denials.

Tracy Morris:

It sounds like clinical validation was a great expansion too, and natural fit for the technology and your overall CAC and CDI platform.

Anne Robertucci:

It was a great next step into continuing the evolution of our product modernization and meeting those expanding market needs Tracy. We see how CDI programs are changing and how we are constantly evolving our solutions to meet those needs. In February, a survey was conducted by Actis and participants were asked what their top priorities for CDI program expansion were. And a dramatic 61% cited clinical validation to support denial prevention was top of mind followed by expanding reviews to all payers and review of potential quality events. These are all areas we help solve with our technology with clinical validation, being the newest innovation.

Tracy Morris:

Annie, how have your clients received clinical validation?

Anne Robertucci:

Our clients are taking advantage of our clinical validation case finding today. They've reported that this capability has created efficiencies for singling out those cases at risk for denial, without having to search for them at the point of care. And without having to add additional staff. This allows both coding and CDI to ensure the documentation supports the codes on the claim.

Tracy Morris:

Great. Any final thoughts you'd like to leave our audience with?

Anne Robertucci:

Yes, Tracy. In today's world, it's critical to utilize resources wisely and ensure your CDI program is as efficient as possible by reviewing the right cases at the right time. It's also important that your program focuses on the integrity of the record and not just finding DRG drivers for optimization, reviewing all payers, incorporating review for potential quality events. And now clinical validation denial prevention is really key to managing a successful CDI program. Clinical validation is here to stay and it's going to remain a focus for payers as well as for healthcare organizations. Sophisticated clinically intelligent technology can transform processes to drive efficiencies and glean better results.

Tracy Morris:

And Mark, for you?

Mark Morsch:

Yeah, I'll just add that clinical validation is a great example of what is possible, when advanced NLP and AI is really able to successfully model a complex process and using NLP to catch that clinical evidence and link to related diagnosis and procedures can really augment the work of HIM and CDI specialist. It's exciting because the technology really extends the reach of those valuable resources and provides a lot of benefits.

Tracy Morris:

Thank you, Annie and Mark for sharing your expertise. That's all the time we have for today. I hope this has been informative for our listeners. Please be on the lookout for additional episodes of our podcast. Together, we can help make healthcare better for everyone.

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Clinical validation has become an increasing area of importance for organizations — and more specifically, for clinicians, clinical documentation improvement (or CDI), auditing and health information management departments. Payers and auditors apply clinical validation criteria to submitted claims to ensure they are supported by widely accepted clinical criteria. Those lacking clinical substantiation may result in denied claims or reduced payments. In a recently published survey by ACDIS, participants indicated as much as 46% of their organization’s denials fall in the clinical validation bucket.

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