Literature DB >> 21063669

Characterisation of children's asthma status by ICD-9 code and criteria-based medical record review.

Young Juhn1, Amiinah Kung, Robert Voigt, Shirley Johnson.   

Abstract

OBJECTIVE: To characterise the relationship between ICD code-based (i.e. physician diagnosis-based) and criteria-based asthma ascertainment.
METHODS: We compared identification of children with asthma between criteria-based medical record review for asthma ascertainment and an ICD-9 code-based approach. We determined the agreement rate and validity index of ICD code-based asthma ascertainment using asthma status by medical record review as a gold standard.
RESULTS: Of the 115 study subjects, the agreement between medical record review and ICD-9 coding was 81.6% with a kappa value of 0.28 (P<0.0001). Sensitivity, specificity, positive and negative predictive values for ICD-9 code were 24.0%, 97.8%, 75.0%, and 82.0%, respectively, using criteria for asthma by medical record review as gold standard.
CONCLUSIONS: ICD code-based asthma ascertainment appears to under-identify children with asthma compared to criteria-based medical record review. ICD codes may be useful for etiologic research but may not be suitable for surveillance of asthma epidemiology.

Entities:  

Mesh:

Year:  2011        PMID: 21063669      PMCID: PMC6602167          DOI: 10.4104/pcrj.2010.00076

Source DB:  PubMed          Journal:  Prim Care Respir J        ISSN: 1471-4418


  17 in total

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3.  Methodological challenges in using routinely collected health data to investigate long-term effects of medication use during pregnancy.

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5.  Risk of Asthma in Late Preterm Infants: A Propensity Score Approach.

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Authors:  Daniela V Luquetti; Babette S Saltzman; Daniela Vivaldi; Luiz A Pimenta; Anne V Hing; Cynthia H Cassell; Jacqueline R Starr; Carrie L Heike
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9.  Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data.

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10.  Patient-level temporal aggregation for text-based asthma status ascertainment.

Authors:  Stephen T Wu; Young J Juhn; Sunghwan Sohn; Hongfang Liu
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