I want to thank Carl Natale for his recent blog on fighting fear with fear. Recently I thanked all the quiet heroes out there preparing for ICD-10, but I should have thanked the less quiet heroes too. I include Natale, Steve Sisko , AHIMA and AHA, colleagues at 3M and many others who are working by whatever means necessary to counter the forces that would stop or eternally delay the implementation of ICD-10 in the U.S.
I admire their willingness to use scary information to combat scary misinformation, even though it may not be how they would choose to make a living. But I do not count myself among those who are good at it.
A case in point is the number of ICD-10 codes, a favorite type of scary misinformation. Seven years ago we created the first complete list of ICD-10 codes in order to develop the mappings now known as the GEMs. Back then it never occurred to us that the total number of “codes” defined as such would be used to make ICD-10 the new poster child for government bureaucracy.
In hindsight, an offensive strategy would have been to package the numbers differently, like CPT with its base codes and modifiers. Methods of counting are ridiculously malleable—you can make something look like a little or a lot, no problem. No one computes the possible combinations of five-digit CPT code and three-digit modifier (this total would dwarf the number of ICD-10 codes) and then rails against the AMA for the intolerable coding burden to physicians. The total number of ICD-10 codes is to us a phenomenally boring factoid, and irrelevant as an indicator of the cost and complexity of implementing ICD-10. But the lesson here is that any bit of information, no matter how seemingly dull or benign, can be used as a weapon in the war of misinformation.
Since I consider myself unfit to fight an offensive war, what can I do to contribute? I am going to continue to help develop, maintain and explain ICD-10-PCS and the GEMs. I am going to continue to give people converting systems and policies to ICD-10 whatever technical help I can offer. In the unlikely event the country wants a rational, scientific debate on how to get health care costs under control, and wants good, detailed classification systems to measure it with, I’ll stop hiding away in my ivory tower and try my best to contribute on the front lines.
Rhonda Butler is a Senior Clinical Research Analyst with 3M Health Information Systems.