• Jacob K Greenberg, Travis R Ladner, Margaret A Olsen, Chevis N Shannon, Jingxia Liu, Chester K Yarbrough, Jay F Piccirillo, John C Wellons, Matthew D Smyth, Tae Sung Park, and David D Limbrick.
• Departments of *Neurological Surgery and #Otolaryngology and Divisions of ‖Biostatistics, §Infectious Diseases, and ¶Public Health Sciences, Washington University School of Medicine in St. Louis, St. Louis, Missouri; ‡Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, Tennessee.
• Neurosurgery. 2015 Aug 1;77(2):269-73.

BackgroundThe use of administrative billing data may enable large-scale assessments of treatment outcomes for Chiari Malformation type I (CM-1). However, to utilize such data sets, validated International Classification of Diseases, Ninth Revision (ICD-9-CM) code algorithms for identifying CM-1 surgery are needed.ObjectiveTo validate 2 ICD-9-CM code algorithms identifying patients undergoing CM-1 decompression surgery.MethodsWe retrospectively analyzed the validity of 2 ICD-9-CM code algorithms for identifying adult CM-1 decompression surgery performed at 2 academic medical centers between 2001 and 2013. Algorithm 1 included any discharge diagnosis code of 348.4 (CM-1), as well as a procedure code of 01.24 (cranial decompression) or 03.09 (spinal decompression, or laminectomy). Algorithm 2 restricted this group to patients with a primary diagnosis of 348.4. The positive predictive value (PPV) and sensitivity of each algorithm were calculated.ResultsAmong 340 first-time admissions identified by Algorithm 1, the overall PPV for CM-1 decompression was 65%. Among the 214 admissions identified by Algorithm 2, the overall PPV was 99.5%. The PPV for Algorithm 1 was lower in the Vanderbilt (59%) cohort, males (40%), and patients treated between 2009 and 2013 (57%), whereas the PPV of Algorithm 2 remained high (≥99%) across subgroups. The sensitivity of Algorithms 1 (86%) and 2 (83%) were above 75% in all subgroups.ConclusionICD-9-CM code Algorithm 2 has excellent PPV and good sensitivity to identify adult CM-1 decompression surgery. These results lay the foundation for studying CM-1 treatment outcomes by using large administrative databases.

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