Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Pharmacoepidemiology...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Pharmacoepidemiology and Drug Safety
Article . 2001 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
versions View all 2 versions
addClaim

Data validity issues in using claims data

Authors: B L, Strom;

Data validity issues in using claims data

Abstract

AbstractThis paper overviews the use of claims data in pharmacoepidemiology, examines problems related to claims data use, and focuses on the uncertain validity of diagnosis data. Two contrasting studies are provided of drug‐induced neutropenia and Stevens‐Johnson Syndrome; both studies were launched at the same time with similar designs. Neutropenia is a laboratory‐driven diagnosis, easy to make and confirm. The neutropenia study yielded many useful results, ranging from incidence rates to results with specific drug classes and individual drugs. However, the medical records revealed major unexpected issues from chronic and cyclic neutropenia. In contrast, Stevens‐Johnson Syndrome is harder to diagnose, and is represented poorly in the ICD‐9‐CM coding system. The result was a study productive of much less clinical information. These studies show the important implications of variable data validity to study interpretation. Uniquely problematic situations exist: the illness does not reliably come to medical attention; inpatient drug exposures; an outcome is poorly defined by the diagnostic coding system; descriptive studies; drug effects are delayed and patients lose eligibility; and there are important unknown confounders such as cigarette smoking, occupation, menarche, menopause, etc., about which information cannot be obtained without accessing the patient. Copyright © 2001 John Wiley & Sons, Ltd.

Related Organizations
Keywords

Insurance Claim Review, Neutropenia, Databases as Topic, Case-Control Studies, Pharmacoepidemiology, Stevens-Johnson Syndrome, Adverse Drug Reaction Reporting Systems, Humans, Medical Records

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    78
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 1%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
78
Top 10%
Top 1%
Top 10%
Upload OA version
Are you the author of this publication? Upload your Open Access version to Zenodo!
It’s fast and easy, just two clicks!