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Stop the fear mongering over ICD-10: It's just another taxonomy

A recent Weekly Standard article shrilly announced that an  Oct. 1, 2014, update of ICD medical codes would augur “a nightmare for doctors.” This was not the only source predicting doom and gloom for the forthcoming code switch from ICD-9 to ICD-10 -- so I decided to investigate. 

It turns out many of these critics are falling victim to common misunderstandings about taxonomies and the characteristics and purposes of large, structured data sets. Here’s how.

ICD, or the International Classification of Diseases, is a taxonomy for diseases. As a  classification scheme it is no different than any other hierarchical or drill-down scheme where data items or nodes flow from parent to child (and where the child is more specialized than its parent). Examples abound, including the Dewey Decimal System for libraries, Amazon’s product catalog, Netflix movie categories and iTunes music genres. 

ICD-10 originated as an international standard with 12 top-level nodes that drill down to about four or five levels. Specifically, the ICD-10 codes consist of two parts:  ICD-10-CM for diagnosis coding and the ICD-10-PCS for inpatient procedure coding.  Basically, one taxonomy is for diseases and one is for procedures to treat diseases.

The headline of the Weekly Standard article is “Code Chaos,” which is a significant misnomer because a taxonomic structure is a well-proven, simple and effective information organization structure, Instead of chaos, it actually follows best practices for a code organization scheme.

There are  three main areas of confusion about the great ICD code switch:

Misunderstanding of magnitude. The chief issue that naysayers harp on is the increase in the number of codes. The Weekly Standard describes this difference as “vast,” from 17,000 codes in ICD-9 to 155,000 in ICD-10. 

The misunderstanding involves an incorrect assumption about complexity. An increase in the number of codes cannot be directly correlated to an increase in complexity, especially when the additions are made to a taxonomy or tree structure. Adding a new level to a tree always represents an exponential increase in the total number of nodes, but it may also mean that only one or two more new levels have been added to the tree.

When only the total number of new codes is emphasized, the implicit assumption is that some kind of linear search process is under way. But that is not true with taxonomies.  The drill down is much more efficient than that. In fact, this sub-dividing of a tree structure is why trees are so prevalent as tools in computer science; they neatly execute a “divide and conquer” strategy for organizing information. 

The total number of codes in ICD-10 should not be feared because they are divided into bite-sized groups within the taxonomy structure.  In fact, the taxonomy structure drastically reduces the organization and learning complexity even when the number of total codes grows exponentially.

Misunderstanding of outliers.  Many commenters poke fun at the level of detail in ICD-10 by citing a rare disease or procedure that is represented in ICD-10 that was not in ICD-9. Examples include an injury when water skiing or a bite from a venomous frog. 

While some of these codes may need to be refined or possibly removed, the critics misunderstand the utility of such fine-grained detail. The assumption is that since several outlier codes may never be used, one can conclude that a large percentage of codes at this level of granularity will not be used. 

Tom Coburn, the senator from Oklahoma who is also a doctor, is quoted as saying that 80 percent of the new codes won’t be used. I respectfully disagree. A more reasonable analysis is that the codes within each branch would follow a normal bell curve in terms of the rarity of their occurrence in the population.  Again, linear assumptions based on outliers are not accurate for a hierarchical structure.

Misunderstanding of purpose. While some critics understand the inherent benefits of specificity, many others incorrectly assert that ICD-10 is mere bureaucratic overreach, which belies a misunderstanding of the correlation between this type of information and successful big data analytics. 

Every business in the country is clamoring for improved business analytics and better decision making. The way you get that insight is by adding fidelity to your data management practices and data collection. High fidelity, granular data collection is the base of the pyramid, and predictive analytics is the top – you don’t get one without the other. 

As they said in the movie Fame, “Fame costs, and right here is where you start paying.” Well, I’ll rephrase that and say, “Analytics costs, and fidelity is how you start paying.”

ICD-10 is a major change that will require resources and training to implement, and its structure and codes will be refined as it evolves. But it is also just a set of taxonomies to categorize diseases and procedures and should not be overblown. 

Implementing ICD-10 is achievable by organizations of all sizes and will greatly improve the analysis of healthcare in the United States. Taxonomies are a proven metadata technique that is a best practice in information organization and discovery. In the case of ICD-10, the benefits really do outweigh the costs.

Michael C. Daconta ( or @mdaconta) is the Vice President of Advanced Technology at InCadence Strategic Solutions and the former Metadata Program Manager for the Homeland Security Department. His new book is entitled, The Great Cloud Migration: Your Roadmap to Cloud Computing, Big Data and Linked Data.

Posted by Michael C. Daconta on Mar 12, 2014 at 9:31 AM

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Reader Comments

Mon, Mar 24, 2014 Emma

While I, too, appreciated the description of ICD-10 as a a taxonomy, the writer misses the massive downstrea impacts of conversion. The point of patient contact, where the actual assignment of a code is done is the simplest aspect for ICD-10 transition. As the anonymous writer above pointed out, ICD codes are used in myriad other ways and well beyond reimbursement. ICD data are aggregated and use in research, statistics, longitudinal studies, biosurveillance, epidemiology, policy, and funding. Clinical decision support is based on the assigned diagnostic code. The impacts to secondary data users are massive and still largely unseen. ICD is the like the genetic code of health care. Imagine if we finally went to a new metric system in US where few, if any, of new measurements mapped precisely. One inch could be 15 cm or 2.8 cm depending on its use. Welcome to ICD-10. Then imagine if no one told you that starting on 10/1/14, the field where you received a report of inches of rain suddenly was in cm or mm...and you didn't t know which it was? Welcome to ICD-10. ICD codes are not proprietyar. They are a HIPAA standard codeset and posted for free at the website. THey codes are maintained and updated by CMS and CDC. They were adapted from and based on the World Health Organization ICD-10 codeset that was ratified in 1993. The US codes are far more precise because the US is one of the few countries that use them for reimbursement. The current ICD-9 codeset was ratified in 1973 - pre-EDI and was not designed for analytics and is woefully outdated. The more granular codes will simplify billing as they provide more detail to justify claims and will markedly reduce the amount of time provider spend submitting additional information to get their claims paid. It will also make it harder to upcode and commit other types of fraud. Modernization does not come cheap or easy. We need it...but that doesn't mean we're ready for it. Buckle up.

Fri, Mar 14, 2014 Dan United States

Anticipating the angst of October 1st, we've developed and recently released an app that may help alleviate the anxiety. You can check it out at Your feedback would be appreciated Thanks Dan

Thu, Mar 13, 2014

The assertion that there is no need for concern over the transition to ICD-10 because it is just another taxonomy completely misses the point. While there may be misconceptions over the nature of code complexity and the scale factor, those are not at the heart of the matter.

The fact is that diagnosis codes are at the heart of a large and complex set of processes from the coding of claims, their transmission, processing, adjudication, reimbursement, auditing, adjustment and analysis. That process involves tens of thousands of providers and hundreds of payers. There are thousands of interface points, decision points and systems that create, store, tranmit and process these codes and hundreds of thousands of human interventions on this process on a daily basis.

The people operating and running these systems and processes have a wealth of tacit knowledge around these codes. That knowledge helps them create the records quickly, it helps them resolve pended claims more easily, it helps them answer provider queries more readily, and it helps them perform a hundred more tasks without resorting to code books. With the transition to ICD-10 that tacit knowledge will be wiped out at a stroke. Formal knowledge will have to replace it and for some period of time (measured in years based on experience in other countries) the tacit knowledge will slowly have to be replenished through experience. That means that there may be imediate and measurable impacts to coding productivity in providers (impacting provider cash flow), time to claim submission, time to issue resolution, and call center reponse times, to name but a few potential impacts.

In addition, every legacy system (of which there are thousands) that references those ICD codes will have to have it's data assets mapped to ICD-10 codes. Because of the differences between ICD-9 and ICD-10 those initial mappings have a range of issues. Those issues impact a range of areas from; code grouping for provider reimbursement, to benefits adjudication and right through to data analytics (the supposed goal for this transition).

If this were the only thing the industry were coping with, the risks would be certainly be lower than they are today. However, all of this change needs to be done by a provider and payer community that is drowning under a vast ocean of work caused by government mandates that are forcing change in the minutia everything in healthcare from patient records to how payers handle claims from Native Alaskans over 300% of the FPL when using out-of-state providers.

I can assure the author that the taxonomic nature of ICD-10 as a code set is the least of the problems that providers and payers will have to deal with.

Thu, Mar 13, 2014 Virginia

The article did not discuss whether ICD-10 open source/open document or is is proprietary and owned by a professional organization that makes licensing $$$ off of its use? If it is proprietary is it only so for a limited lifespan or is it likely to be replaced by another proprietary system of codes when it becomes obsolete? Is ICD-10 owned by the same people that owned ICD-9? Is ICD-10 the system that Europe went to when it retired ICD-9 or did they go to a different system. If they went to a different system was that system open or proprietary and requiring of license fees. If it was a different system then ICD-10, what was the rationale for going with ICD-10 rather then the European system? Thank you, Scribe with a Stylus.

Thu, Mar 13, 2014 Jim Kretz

Good for you! A voice of reason regarding the switch to ICD-10. Nay sayers seem to forget that ICD-9, which was retired in Europe almost 20 years ago, has become quite a mess as new codes have been shoe horned into it violating much of its initial structure; e.g. cardiac codes appended in the opthamology section.

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