Why We Should Applaud the End of the ICD-10 Grace Period

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Rhonda Butler, a clinical research manager with 3M Health Information Systems, originally contributed this blog.

Beginning Oct. 1, the grace period ends for Medicare part B ICD-10 diagnosis coding.

For those of you who heard the news but not the details, here is a quick history of the grace period: CMS made a deal with the AMA last year just before ICD-10 implementation, in an attempt to ease fears that physician practices would go belly up because their ICD-10 coded claims would be denied. CMS/AMA announced “flexibility in the claims auditing and quality reporting process.” The deal was limited to Medicare contractor “post payment” reviews of physician fee schedule claims and clinical quality data for required quality reporting programs. The announcement said that reviewers could not deny a claim or assess a quality reporting penalty “solely on specificity,” as long as the code was in the correct “code family”—in other words, it needed to be a valid code, accurate out to three characters, and if it was an unspecified code, okay.

As grace goes, it was not exactly amazing. Claims could be denied or a quality penalty assessed for reasons other than specificity. And, plenty of claims could still go to claim purgatory or straight to claim hell if they were sloppily coded: no state of grace for national or local coverage decisions (NCDs and LCDs), no grace for prepayment reviews and prior authorization requests.

At any rate, let’s all hope this less-than-amazing grace period will end quietly, so we can stop treating physician coders as sinners who need grace, and get on with it. What is “it?”

Though coders can get religious at times about what’s in “the Book”, coding is not a religion, it is a means to an end. We code medical records so we have coded data to use. We currently use coded data to calculate payment in many situations. We also use it to look for clinically meaningful patterns—patterns of use, patterns of cost, patterns of success, patterns of failure. Currently, coding is the easiest method we have for turning the volume and complexity of information about a person’s health state and interactions with the healthcare system into something that can be tracked and compared for cost and quality.

To some physician practices, codes are still the healthcare equivalent of SKUs and nothing more—we have to slap a code on a form, damnit, so we can get paid. But, yikes—the industry is all about population health, right? Population health can mean different things in different contexts, but in the realm of healthcare data it means one thing for sure: coded data from physician practices takes on new importance.

When people talk about a longitudinal patient record store as the holy grail of population health, one of the things they mean is, “We have decent coded data from inpatient and outpatient hospital encounters, but we don’t have a way to link those encounters together with physician office encounters, and furthermore we can’t trust the physician office coding as far as we can spit.” For example, 3M’s Clinical Risk Groups (CRGs) uses a stricter inclusion rule for codes from physician office records, which means that when physician office coding doesn’t meet that inclusion rule it gets ignored in calculating a CRG.

A longitudinal patient record is just a fancy way of saying we want to gather information about a person’s health over time, from a bunch of different sources. Physician practice coding is a blurry region in the data picture—it needs to get clearer. Most of us spend most of our lives outside of hospitals and surgery centers—hospital stays and same-day surgeries are the extraordinary health events in our lives. Our ordinary, everyday health encounters consist of visits to a doctor, physical therapist, nurse practitioner and many other providers.

For healthcare to continue to evolve, and to be able to work effectively toward its goals for reducing per capita cost while improving the health of the population and the patient experience, we need to be able to have more confidence in the coded data coming out of physician practices. Some in the physician community have already seen the bigger picture, and are working to create better coded data.

My hope is that the incentive to code more accurately will come of its own accord, without any more talk of grace or punishment, as more and more physicians see the direction that health care is moving, and realize it serves them well, both clinically and financially, to support the idea of creating good coded data.

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