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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

作者:James P, Burke;Anjali, Jain;Wenya, Yang;Jonathan P, Kelly;Marygrace, Kaiser;Laura, Becker;Lindsay, Lawer;Craig J, Newschaffer

来源:Autism : the international journal of research and practice 2014 年 18卷 3期

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作者:
James P, Burke;Anjali, Jain;Wenya, Yang;Jonathan P, Kelly;Marygrace, Kaiser;Laura, Becker;Lindsay, Lawer;Craig J, Newschaffer
来源:
Autism : the international journal of research and practice 2014 年 18卷 3期
标签:
Administrative data autism chart review validation study
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