An imputation method for calculating and comparing autoimmune disease incidence using partial case review

Publication date: 4 December 2017
Source:Vaccine, Volume 35, Issue 48, Part B
Author(s): Jeff Slezak, Kristin Meyer, Lina S. Sy, Chun Chao, Harpreet Takhar, Brad Ackerson, T. Craig Cheetham, Steven Jacobsen
PurposeEstimate incidence of autoimmune conditions in a population who received HPV4 vaccine and a comparison unvaccinated population. Electronic health record (EHR) data may contain inaccurate or incomplete coding, while manual chart review of all cases may not be feasible. We propose a method to estimate incidence using EHR data and case review for a sample.MethodsSuspected incident cases were identified using ICD-9 codes, laboratory results and medications related to the condition. A random sample of charts was reviewed to confirm the diagnosis and determine disease onset date. Multiple imputation, using a Monte Carlo model including age and disease indicators was used to impute case status of non-reviewed cases. Incidence rate was calculated in each imputed dataset, with median and percentiles giving a distribution for the estimated incidence rate. Sensitivity analyses compared modeled results to results without imputation and results where imputation was applied to the subset of cases identified using specific ICD-9 codes.ResultsThe model accounted for differential case confirmation rates by age and method of case identification, identifying a potential safety signal that was missed relying on EHR data alone.ConclusionsThis method may be useful for computing incidence when full case review is not feasible.



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