A systematic review of validated methods for identifying acute respiratory failure using administrative and claims data
Article first published online: 19 JAN 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Pharmacoepidemiology and Drug Safety
Supplement: The U.S. Food and Drug Administration's Mini-Sentinel Program
Volume 21, Issue Supplement S1, pages 261–264, January 2012
How to Cite
Jones, N., Schneider, G., Kachroo, S., Rotella, P., Avetisyan, R. and Reynolds, M. W. (2012), A systematic review of validated methods for identifying acute respiratory failure using administrative and claims data. Pharmacoepidem. Drug Safe., 21: 261–264. doi: 10.1002/pds.2326
- Issue published online: 19 JAN 2012
- Article first published online: 19 JAN 2012
- Food and Drug Administration (FDA) through Department of Health and Human Services (HHS). Grant Number: HHSF223200910006I
- acute respiratory failure;
- administrative and claims data;
- coding algorithm
The Food and Drug Administration's (FDA) Mini-Sentinel pilot program initially aims to conduct active surveillance to refine safety signals that emerge for marketed medical products. A key facet of this surveillance is to develop and understand the validity of algorithms for identifying health outcomes of interest (HOIs) from administrative and claims data. This paper summarizes the process and findings of the algorithm review of acute respiratory failure (ARF).
PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxis HOI. Level 1 abstract reviews and Level 2 full-text reviews were conducted to find articles using administrative and claims data to identify ARF, including validation estimates of the coding algorithms.
Our search revealed a deficiency of literature focusing on ARF algorithms and validation estimates. Only two studies provided codes for ARF, each using related yet different ICD-9 codes (i.e., ICD-9 codes 518.8, “other diseases of lung,” and 518.81, “acute respiratory failure”). Neither study provided validation estimates.
Research needs to be conducted on designing validation studies to test ARF algorithms and estimating their predictive power, sensitivity, and specificity. Copyright © 2012 John Wiley & Sons, Ltd.