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Articles

Mar 13: As time runs out, is ICD-10 ‘not useful’ for data analytics?

electronic health records
The healthcare industry has been debating the pros and cons of switching to ICD-10 since the very beginning of the new code set’s development.  Depending on who you ask, the transition is either a really great thing that will drastically improve care with its increased granularity, or a money-draining time suck that will destroy the delicate financial dance between providers and payers.  Although the opposition has gone mostly unheeded during the long march towards the federally mandated deadline of October 1, 2014, the debate doesn’t seem to be cooling down any time soon.
While the ICD-10 issue may be polarizing, there are some experts who think the argument is just too small.  The question isn’t whether or not ICD-10 is a good thing to do, because it’s definitely going to happen.  The real question is what we’re going to be able do with it – and what we’re not going to be able to do with it – once the new code set arrives.  At HIMSS14 last month, Dan Riskin, MD, CEO of Health Fidelity, took some time to explain to EHRintelligence why ICD-10 isn’t all it’s cracked up to be when it comes to the specificity and detail that has been its big selling point.
“We think ICD-10 is not useful for analytics,” Riskin said simply. “We recognize the effort to bring deeper data into claims, and yet we think claims data will never get to the point where it’s useful in value-based healthcare. There are too many problems with it.  We know that it’s inaccurate.  We also know that claims data is not robust.”
“Using three boiled-down concepts to represent an entire patient in a world where patients are older and more complex than they have ever been is never going to accomplish what’s desirable,” he continued.  “It’s fine to request more detail in claims.  But quite frankly, if you’re already going more granular with ICD-10, why not go to SNOMED, which is more granular still?  And if you are going to SNOMED, why not connect it with the medications on RXNorm and the labs on LOINC?  Why not connect all these things and have a really deep investigation of the patient?”
The answer, sadly, is that providers who can barely manage to switch on their EHRs, train their coders and physicians in ICD-10, and manage the concurrent demands of Stage 2 of meaningful use aren’t going to be able to shoulder the burden of integrating three or four coding standards in a world where vendors continue to struggle with the upgrades they need to push out for 2014.  Healthcare is an industry slow to change, but a more comprehensive landscape of data integration may be possible in the future.  Riskin thinks it needs to happen soon in order for providers to truly see the value not only of ICD-10, but also of the analytics infrastructures that many organizations are tentatively trying to build.
“For the smaller hospitals that have limited infrastructure, it’s fine that they may only be working with claims data.  But advanced hospitals should view ICD-10 as necessary for the revenue cycle, just not the end-all for analytics,” he said. “Claims data is a small portion of the meaningful representation of the patient.  I think using ICD-10 for analytics might work through 2014 and not much beyond that.  This idea of growing and scaling this manual fleet of people is probably nonsense.  It only gets us so far.”
What will get us the rest of the way?  Creating smart workflows that leverage smarter data, and having the human brainpower on hand to make sense of what the numbers are saying.  “That’s going to be increasingly desirable,” Riskin agreed.  “There are a very limited number of trained specialists in quality improvement and workflow.”
“Although, physicians are not notoriously good at this,” he admitted.  “Physicians were asked to manage finances in healthcare, and look at how well that went. Now we’re going to ask physicians to manage quality.  They have not traditionally done that. It’s been the domain of the nurses who have gotten deeply engaged in quality and have done that for no money for a very long period of time.  And they are experts.  They are so good.  The doctors being called into lead some of these groups?  I don’t know.”
“I think there will be a small number of highly trained doctors who are really engaged in the field, and they will be scarce and highly desirable,” he added.  “There will be a small number of doctors on the informatics side that actually know how to write code and architect software, and know how to implement it.  That’s a very small subset even of board-certified clinical informaticists. We need the nurses.”
Looking beyond the nuts and bolts of implementing the code set will become more common and more important as the deadline speeds by, leaving providers in an ICD-10 world for good.  The HIMSS conference is a useful indicator of the healthcare industry’s state of mind, and plenty of attendees in Orlando were thinking well past the anticipated chaos of October 2014.
“What I’ve seen over the last couple of years at HIMSS was a deep focus on revenue cycle management.  And now I’m seeing a transition from revenue cycle and ICD-10 towards analytics and value-based healthcare, which is really heartwarming for someone who worked hard so in policy to try see data captured not for data sake, but rather for the sake of actually helping people,” Riskin said.  “It’s nice to see that the focus is transitioning to value-based care, where I actually believe people will see a difference.”
“I think most people that planned to have an ICD-10 solution by end of year have probably already locked onto their approach,” he added.  “The landscape of companies addressing it is set.  I don’t think there are a lot of surprises this year in ICD-10.  On the other hand, the analytics is a wide open field.  The spending on it right now is minimal.  It is a tiny fraction of what’s spent on electronic health records, but the value that should be delivered from it will be high if we do it right.  So I think there is a hope, if not a certainty, that there will be a real market for analytics.” Source