Recommendations for optimal ICD codes to study neurologic conditions

Abstract

Administrative health data are frequently used for large population-based studies. However, the validity of these data for identifying neurologic conditions is uncertain. This article systematically reviews the literature to assess the validity of administrative data for identifying patients with neurologic conditions. Two reviewers independently assessed for eligibility all abstracts and full-text articles identified through a systematic search of Medline and Embase. Study data were abstracted on a standardized abstraction form to identify ICD code-based case definitions and corresponding sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs). Thirty full-text articles met the eligibility criteria. These included 8 studies for Alzheimer disease/dementia (sensitivity: 8-86.5, specificity: 56.3-100, PPV: 60-97.9, NPV: 68.0-98.9), 2 for brain tumor (sensitivity: 54.0-100, specificity: 97.0-99.0, PPV: 91.0-98.0), 4 for epilepsy (sensitivity: 98.8, specificity: 69.6, PPV: 62.0-100, NPV: 89.5-99.1), 4 for motor neuron disease (sensitivity: 78.9-93.0, specificity: 99.0-99.9, PPV: 38.0-90.0, NPV: 99), 2 for multiple sclerosis (sensitivity: 85-92.4, specificity: 55.9-92.6, PPV: 74.5-92.7, NPV: 70.8-91.9), 4 for Parkinson disease/parkinsonism (sensitivity: 18.7-100, specificity: 0-99.9, PPV: 38.6-81.0, NPV: 46.0), 3 for spinal cord injury (sensitivity: 0.9-90.6, specificity: 31.9-100, PPV: 27.3-100), and 3 for traumatic brain injury (sensitivity: 45.9-78.0 specificity: 97.8, PPV: 23.7-98.0, NPV: 99.2). No studies met eligibility criteria for cerebral palsy, dystonia, Huntington disease, hydrocephalus, muscular dystrophy, spina bifida, or Tourette syndrome. To ensure the accurate interpretation of population-based studies with use of administrative health data, the accuracy of case definitions for neurologic conditions needs to be taken into consideration.