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Abstract
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.
GLOSSARY
- AD=
- Alzheimer disease;
- ICD=
- International Classification of Diseases;
- NPV=
- negative predictive value;
- PD=
- Parkinson disease;
- PPV=
- positive predictive value
Footnotes
Study funding: Supported by the Public Health Agency of Canada, Alberta Health and Wellness, Alberta Innovates Health Solutions, and the Canadian Institutes of Health Research.
The opinions expressed in this publication are those of the authors/researchers and do not necessarily reflect the official views of the Public Health Agency of Canada.
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Supplemental data at www.neurology.org
- Received January 23, 2012.
- Accepted April 19, 2012.
- Copyright © 2012 by AAN Enterprises, Inc.
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