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]=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.
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]=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.
Authors: Nam-Kyong Choi; Daniel H Solomon; Theodore N Tsacogianis; Joan E Landon; Hong Ji Song; Seoyoung C Kim Journal: J Bone Miner Res Date: 2017-02-07 Impact factor: 6.741
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