J. P. Mullooly1, J. G. Donahue2, F. DeStefano3, J. Baggs3, E. Eriksen4 for the VSD Data Quality Working Group
1Center for Health Research, Kaiser Permanente Northwest, Portland, OR, USA 2Marshfield Clinic, Marshfield, WI, USA 3Centers for Disease Control and Prevention, Atlanta, GA, USA 4UCLA Center for Vaccine Research, Los Angeles Biomedical Research Institute, Torrance, CA, USA
bias, ICD-9-CM codes, positive predictive values, vaccine safety, power reductions
Objectives: To assess how well selected ICD-9-CM diagnosis codes predict adverse events; to model bias and power loss when vaccine safety analyses rely on unverified codes. Methods: We extracted chart verification data for ICD-9-CM diagnosis codes from six Vaccine Safety Datalink (VSD) publications and modeled biases and power losses using positive predictive value (PPV) estimates and ranges of code sensitivity. Results: Positive predictive values were high for type 1 diabetes (80%) in children, relative to WHO criteria, and intussusception (81%) in young children, relative to a standard published case definition. PPVs were moderate (65%) for inpatient and emergency department childhood seizures and low (21%) for outpatient childhood seizures, both relative to physician investigator judgment. Codes for incident central nervous system demyelinating disease in adults had high PPV for inpatient codes (80%) and low PPV for outpatient codes (42%) relative to physicians’ diagnoses. Modeled biases were modest, but large increases in frequencies of adverse events are required to achieve adequate power if unverified ICD-9-CM codes are used, especially when vaccine associations are weak. Conclusions: ICD-9-CM codes for type 1 diabetes in children, intussusception in young children, childhood seizures in inpatient and emergency care settings, and inpatient demyelinating disease in adults were sufficiently predictive for vaccine safety analyses to rely on unverified diagnosis codes. Adverse event misclassification should be accounted for in statistical power calculations.
J. Marienhagen, Ch. Eilles
Nuklearmedizin 2003 42 4: 129-134
C. Vogel, O. Gefeller
Methods Inf Med 2002 41 4: 342-348
In recent years, we have witnessed substantial progress in the use of clinical informatics systems...
A For-Discussion-Section in this issue features a pair of discussed review papers on boosting...
Invitation to Apply for the Student Editorial Board 2015/2016 - The Journal Methods of Information...
Information technology in health care has a clear potential to improve the quality and efficiency...
The submission deadline for the Focus Theme on "Big Data and Analytics in Healthcare"...