Does a claims diagnosis of autism mean a true case?
Requiring two autism codes in claims catches almost nine true cases out of ten.
01Research in Context
What this study did
The team asked a simple question. Do insurance claims that list autism really match a child’s chart?
They pulled claims that had at least two autism codes. Then they opened each child’s medical chart and checked if a clinician truly gave an autism diagnosis.
What they found
Eight out of every ten claims with two or more autism codes were right. The charts backed the diagnosis.
In plain words, the claims trick is good enough for big research studies.
How this fits with other research
Lemons et al. (2015) tried the same two-code rule in hospital records. They got almost the same hit rate. The rule works in both claims and EMRs.
Norris et al. (2010) warned that some paper checklists miss lots of kids. Their review says the SCQ works, but GARS fails often. The claims rule does not replace those tools; it just spots cases faster in huge data sets.
van den Broek et al. (2006) showed that toddler screens like M-CHAT miss higher-functioning kids. The claims study looked at all ages together, so it could still miss the same mild cases. Use both methods if you need the full picture.
Why it matters
If you run program evaluations or funding reports, you can trust the two-code rule to count autism cases. You do not need to read every chart. Just remember: the rule may skip mild or very young kids, so pair it with clinical tools when you plan services.
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02At a glance
03Original abstract
The purpose of this study was to validate autism spectrum disorder cases identified through claims-based case identification algorithms against a clinical review of medical charts. Charts were reviewed for 432 children who fell into one of the three following groups: (a) more than or equal to two claims with an autism spectrum disorder diagnosis code (n = 182), (b) one claim with an autism spectrum disorder diagnosis code (n = 190), and (c) those who had no claims for autism spectrum disorder but had claims for other developmental or neurological conditions (n = 60). The algorithm-based diagnoses were compared with documented autism spectrum disorders in the medical charts. The algorithm requiring more than or equal to two claims for autism spectrum disorder generated a positive predictive value of 87.4%, which suggests that such an algorithm is a valid means to identify true autism spectrum disorder cases in claims data.
Autism : the international journal of research and practice, 2014 · doi:10.1177/1362361312467709