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Recommendations for optimal ICD codes to study neurologic conditions

2012; Lippincott Williams & Wilkins; Volume: 79; Issue: 10 Linguagem: Inglês

10.1212/wnl.0b013e3182684707

1526-632X

Christine Smith, Amy Metcalfe, Tamara Pringsheim, Jodie I. Roberts, Cynthia A Beck, Brenda R. Hemmelgarn, Jane McChesney, Hude Quan, Nathalie Jetté,

Machine Learning in Healthcare

Objective: Administrative health data are frequently used for large population-based studies. However, the validity of these data for identifying neurologic conditions is uncertain. Methods: 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). Results: 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. Conclusions: 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.