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Validation of an International Classification of Diseases, Ninth Revision Code Algorithm for Identifying Chiari
Jacob K Greenberg1, Travis R Ladner, Margaret A Olsen
1Departments 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.
Insights
Algorithm 2 using ICD-9-CM codes accurately identifies Chiari Malformation type I (CM-1) decompression surgery. This validated method enables large-scale outcome studies using administrative data.
Area of Science:
- Neurosurgery
- Health Informatics
- Medical Coding
Background:
- Administrative billing data offers potential for large-scale Chiari Malformation type I (CM-1) treatment outcome assessments.
- Validated International Classification of Diseases, Ninth Revision (ICD-9-CM) code algorithms are crucial for utilizing these datasets to identify CM-1 surgery.
Purpose of the Study:
- To validate two ICD-9-CM code algorithms for identifying adult patients who underwent CM-1 decompression surgery.
- To assess the accuracy and reliability of these algorithms for research purposes.
Main Methods:
- Retrospective analysis of adult CM-1 decompression surgeries at two academic medical centers (2001-2013).
- Algorithm 1: CM-1 diagnosis code (348.4) with cranial/spinal decompression procedure codes.
- Algorithm 2: CM-1 diagnosis code (348.4) as the primary diagnosis.
Main Results:
- Algorithm 2 demonstrated a high positive predictive value (PPV) of 99.5% for identifying CM-1 decompression surgery.
- Algorithm 1 had a lower overall PPV of 65%, with significant variations across subgroups.
- Both algorithms showed good sensitivity (Algorithm 1: 86%, Algorithm 2: 83%) across all patient subgroups.
Conclusions:
- ICD-9-CM code Algorithm 2 provides excellent PPV and good sensitivity for identifying adult CM-1 decompression surgery.
- This validated algorithm is foundational for future CM-1 treatment outcome research utilizing large administrative databases.
Background:
The 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.
Objective:
To validate 2 ICD-9-CM code algorithms identifying patients undergoing CM-1 decompression surgery.
Methods:
We 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.
Results:
Among 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.
Conclusion:
ICD-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.
