Purpose: To determine the predictive value of International Classification of Diseases, 9th Revision (ICD-9) codes for identifying infantile eye diagnoses.
Methods: Population-based retrospective cohort study of all residents of Olmsted County, Minnesota diagnosed at ≤1 year of age with an ocular disorder. The medical records of all infants diagnosed with any ocular disorder from January 1, 2005, through December 31, 2014, were identified. To assess ICD-9 code accuracy, the medical records of all diagnoses with ≥20 cases were individually reviewed and compared to their corresponding ICD-9 codes. Main outcome measures included positive predictive value (PPV), negative predictive value (NPV), sensitivity, and specificity of ICD-9 codes.
Results: In a cohort of 5,109 infants with ≥1 eye-related ICD-9 code, 10 ocular diagnoses met study criteria. The most frequent diagnoses were conjunctivitis (N = 1,695) and congenital nasolacrimal duct obstruction (N = 1,250), while the least common was physiologic anisocoria (N = 23). The PPVs ranged from 8.3% to 88.0%, NPVs from 96.3% to 100%, sensitivity from 3.0% to 98.7%, and specificity from 72.6% to 99.9%. ICD-9 codes were most accurate at identifying physiologic anisocoria (PPV: 88.0%) and least accurate at identifying preseptal cellulitis (PPV: 8.3%). In eye specialists versus non-eye specialists, there was a significant difference in PPV of ICD-9 codes for conjunctivitis (26.8% vs. 63.9%, p < .001), pseudostrabismus (85.9% vs. 25.0%, p < .001), and physiologic anisocoria (95.5% vs. 33.3%, p = .002).
Conclusion: The predictive value of ICD-9 codes for capturing infantile ocular diagnoses varied widely in this cohort. These findings emphasize the limitations of database research methodologies that solely utilize claims data to identify pediatric eye diseases.Abbreviations/Acronyms PPV: positive predictive value; NPV: negative predictive value; CNLDO: congenital nasolacrimal duct obstruction.
Keywords: ICD-9; Pediatric ophthalmology; claims data; international classification of diseases; negative predictive value; positive predictive value; sensitivity; specificity.