A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets.

Seol, Hee Yun; Wi, Chung-Il; Ryu, Euijung; King, Katherine S; Divekar, Rohit D; Juhn, Young J

Seol, Hee Yun; Wi, Chung-Il; Ryu, Euijung; King, Katherine S; Divekar, Rohit D; Juhn, Young J.

Afiliação

Seol HY; Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Wi CI; Department of Internal Medicine, Pusan National University Yangsan Hospital, Yangsan, Korea.
Ryu E; Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, Minnesota, USA.
King KS; Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
Divekar RD; Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
Juhn YJ; Division of Allergic Disease, Mayo Clinic, Rochester, Minnesota, USA.

J Asthma ; 58(8): 1077-1086, 2021 08.

Article em En | MEDLINE | ID: mdl-32315558

Assuntos

Algoritmos; Asma/diagnóstico; Adolescente; Adulto; Criança; Estudos Transversais; Conjuntos de Dados como Assunto; Feminino; Humanos; Masculino; Estudos Retrospectivos; Adulto Jovem

Palavras-chave

pediatrics; Epidemiology; diagnostics

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Asma / Algoritmos Tipo de estudo: Diagnostic_studies / Guideline / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Child / Female / Humans / Male Idioma: En Revista: J Asthma Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

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