The validity of administrative data to identify hip fractures is high--a systematic review.
OBJECTIVE
To determine the validity of the diagnostic algorithms for osteoporosis and fractures in administrative data.


METHODS
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]=0.70) or when pharmacy data were used (with or without the use of hospital and physician visit claims data, AUC>0.70). 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: 69-97%; PPV: 63-96%) and the addition of physician claims diagnostic and procedural codes to hospitalization diagnostic codes improved these characteristics (sensitivity: 83-97%; PPV: 86-98%). 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.
Lady Davis Institute for Medical Research, Jewish General Hospital, Room A-725, 3755 Cote Ste Catherine Road, Montreal, Quebec H3T 1E2, Canada. marie.hudson@mcgill.ca
Marie
M
Hudson
Antonio
A
Avina-Zubieta
Diane
D
Lacaille
Sasha
S
Bernatsky
Lisa
L
Lix
Sonia
S
Jean
D000465:Algorithms; D006620:Hip Fractures / Q000175:diagnosis* / Q000209:etiology; D006801:Humans; D007344:Insurance Claim Reporting / Q000706:statistics & numerical data*; D008499:Medical Records; D010024:Osteoporosis / Q000175:diagnosis / Q000209:etiology; D015203:Reproducibility of Results; D012307:Risk Factors