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The validity of administrative data to identify hip fractures is high-a systematic review.

Authors :
Hudson, Marie
Avina-Zubieta, Antonio
Lacaille, Diane
Bernatsky, Sasha
Lix, Lisa
Jean, Sonia
Source :
Journal of Clinical Epidemiology. 2013, Vol. 66 Issue 3, p278-285. 8p.
Publication Year :
2013

Abstract

Objective: To determine the validity of the diagnostic algorithms for osteoporosis and fractures in administrative data. Study Design and Setting: A systematic search was conducted to identify studies that reported the validity of a diagnostic algorithm for osteoporosis and/or fractures using administrative data. Results: Twelve studies were reviewed. The validity of the diagnosis of osteoporosis in administrative data was fair when at least 3 years of data from hospital and physician visit claims were used (area under the receiver operating characteristic [ROC] curve [AUC]50.70) or when pharmacy data were used (with or without the use of hospital and physician visit claims data, AUCO0.70). Nonetheless, the positive predictive values (PPVs) were low (!0.60). There was good evidence to support the use of hospital data to identify hip fractures (sensitivity: 69e97%; PPV: 63e96%) and the addition of physician claims diagnostic and procedural codes to hospitalization diagnostic codes improved these characteristics (sensitivity: 83e97%; PPV: 86e98%). Vertebral fractures were difficult to identify using administrative data. There was some evidence to support the use of administrative data to define other fractures that do not require hospitalization. Conclusions: Administrative data can be used to identify hip fractures. Existing diagnostic algorithms to identify osteoporosis and vertebral fractures in administrative data are suboptimal. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08954356
Volume :
66
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Clinical Epidemiology
Publication Type :
Academic Journal
Accession number :
85899344
Full Text :
https://doi.org/10.1016/j.jclinepi.2012.10.004