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A systematic review of validated methods for identifying systemic lupus erythematosus (SLE) using administrative or claims data

期刊

VACCINE
卷 31, 期 -, 页码 K62-K73

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ELSEVIER SCI LTD
DOI: 10.1016/j.vaccine.2013.06.104

关键词

Systemic lupus erythematosus (SLE); Administrative database; ICD-9; Positive predictive value (PPV); Incidence calculation; Algorithm validation

资金

  1. Food and Drug Administration (FDA) through Department of Health and Human Services (HHS) [HHSF223200910006I]

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Purpose: To examine the validity of billing, procedural, or diagnosis code, or pharmacy claim-based algorithms used to identify patients with systemic lupus erythematosus (SLE) in administrative and claims databases. Methods: We searched the MEDLINE database from 1991 to September 2012 using controlled vocabulary and key terms related to SLE. We also searched the reference lists of included studies. Two investigators independently assessed the full text of studies against pre-determined inclusion criteria. The two reviewers independently extracted data regarding participant and algorithm characteristics and assessed a study's methodologic rigor using a pre-defined approach. Results: Twelve studies included validation statistics for the identification of SLE in administrative and claims databases. Seven of these studies used the ICD-9 code of 710.0 in selected populations of patients seen by a rheumatologist or patients who had experienced the complication of SLE-associated nephritis, other kidney disease, or pregnancy. The other studies looked at limited data in general populations. The algorithm in the selected populations had a positive predictive value (PPV) in the range of 70-90% and of the limited data in general populations it was in the range of 50-60%. Conclusions: Few studies use rigorous methods to validate an algorithm for the identification of SLE in general populations. Algorithms including ICD-9 code of 710.0 in physician billing and hospitalization records have a PPV of approximately 60%. A requirement that the code is obtained from a record based on treatment by a rheumatologist increases the PPV of the algorithm but limits the generalizability in the general population. (C) 2013 Published by Elsevier Ltd.

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