Didn't we say not to use ICD-9 codes to track MRSA?

When you're trying to improve epidemiological methods, I guess you have to be patient.  For example, when Yehuda Carmeli and Anthony Harris told us which control group to use when assessing risk factors for antibacterial resistant organisms, it took years for people to regularly follow their advice. However, I'm still a bit surprised when authors and journals keep publishing studies that track MRSA infections using ICD-9 codes. 

A couple years ago, ICHE published our multi-center validation study showing that ICD-9 codes for MRSA have a very poor positive-predictive value: 31%. To quote our conclusion: "In its current state, the ICD-9-CM code V09 is not an accurate predictor of MRSA infection and should not be used to measure rates of MRSA infection." ICHE also published Marin Schweizer and Mike Rubin's excellent editorial summarizing the issues with ICD-9 code based surveillance for MRSA.

So, knowing what we know about recent MRSA trends and considering my feelings about ICD-9 codes and MRSA, I was a bit surprised when the August ICHE included a study suggesting that MRSA was increasing in academic medical centers between 2003 and 2008 and it used ICD-9 codes! Sure, they attempted to adjust for the billing code's limited sensitivity.  Unfortunately, sensitivity isn't the key issue. If you say something is increasing, it's more important to know if what you're counting as an MRSA infection is actually an incident MRSA infection from the index admission, and not an MRSA infection from a prior admission, or even newly detected MRSA colonization. Thus positive predictive value and specificity are more important measures. 

Just remember this when you read stuff on the interweb that says "contrary to data from the CDC" or posts saying MRSA has doubled in 5 years.  Stick with the CDC. Fortunately, most of the best evidence suggests MRSA is in decline...at least for now.

Important note: Our validation study included three hospitals and compared ICD-9 to actual culture data, the gold standard.

-----
Ridiculous Example: What if we wanted to estimate the proportion of 30th Olympiad attendees who were born in England by randomly sampling people walking around the Olympic stadium. We could use a somewhat sensitive test, "is the person wearing a Union Jack t-shirt", and catch many people born in England, but this would be useless (ie very low positive predictive value) since anyone can buy a shirt. We could also use a more specific test like checking their passport. Thus, ICD-9 codes are a bit like t-shirts, while microbiological culture results as used in accurate MRSA estimates are more like a passport.