Misclassification bias is introduced into medical claims–based research because of reliance on diagnostic coding rather than full medical record review. We sought to characterize this bias for idiopathic intracranial hypertension (IIH) and evaluate strategies to reduce it.
A retrospective review of medical records was conducted using a clinical data warehouse containing medical records and administrative data from an academic medical center. Patients with 1 or more instances of International Classification of Diseases (ICD)-9 or -10 codes for IIH (348.2 or G93.2) between 1989 and 2017 and original results of neuroimaging (head CT or MRI), lumbar puncture, and optic nerve examination were included in the study. Diagnosis of IIH was classified as definite, probable, possible, or inaccurate based on review of medical records. The positive predictive value (PPV) for IIH ICD codes was calculated for all subjects, subjects with an IIH code after all testing was completed, subjects with high numbers of IIH ICD codes and codes spanning longer periods, subjects with IIH ICD codes associated with expert encounters (ophthalmology, neurology, or neurosurgery), and subjects with acetazolamide treatment.
Of 1,005 patients with ICD codes for IIH, 103 patients had complete testing results and were included in the study. PPV of ICD-9/-10 codes for IIH was 0.63. PPV in restricted samples was 0.82 (code by an ophthalmologist n = 57), 0.70 (acetazolamide treatment n = 87), and 0.72 (code after all testing, n = 78). High numbers of code instances and longer duration between the first and last code instance also increased the PPV.
An ICD-9 or -10 code for IIH had a PPV of 63% for probable or definite IIH in patients with necessary diagnostic testing performed at a single institution. Coding accuracy was improved in patients with an IIH ICD code assigned by an ophthalmologist. Use of coding algorithms considering treatment providers, number of codes, and treatment is a potential strategy to reduce misclassification bias in medical claims–based research on IIH. However, these are associated with a reduced sample size.