A systematic review of validated methods for identifying acute respiratory failure using administrative and claims data

被引:13
作者
Jones, Natalie [1 ]
Schneider, Gary [1 ]
Kachroo, Sumesh [1 ]
Rotella, Philip [1 ]
Avetisyan, Ruzan [1 ]
Reynolds, Matthew W. [1 ]
机构
[1] United BioSource Corp, Epidemiol & Database Analyt, Lexington, MA 02420 USA
关键词
acute respiratory failure; administrative and claims data; Mini-Sentinel; coding algorithm; MORTALITY;
D O I
10.1002/pds.2326
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Purpose 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). Methods PubMed and Iowa Drug Information Service searches were conducted to identify citations applicable to the anaphylaxisHOI. 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. Results 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. Conclusions Research needs to be conducted on designing validation studies to test ARF algorithms and estimating their predictive power, sensitivity, and specificity. Copyright (C) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:261 / 264
页数:4
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