Development and evaluation of a computable phenotype to identify pediatric patients with leukemia and lymphoma treated with chemotherapy using electronic health record data
Autor: | Jennifer J. Wilkes, Taylor Aglio, Charles A. Phillips, Christopher B. Forrest, Jenna Sopfe, Michael J. McNeil, L. Charles Bailey, Hanieh Razzaghi, Mikaela Salvesen‐Quinn |
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Rok vydání: | 2019 |
Předmět: |
Male
medicine.medical_specialty Adolescent Lymphoma medicine.medical_treatment Article 03 medical and health sciences 0302 clinical medicine Internal medicine Epidemiology medicine Electronic Health Records Humans Registries Medical diagnosis Chemotherapy Leukemia business.industry Medical record Hematology medicine.disease Confidence interval Oncology Child Preschool 030220 oncology & carcinogenesis Pediatrics Perinatology and Child Health Female Observational study business Algorithms 030215 immunology |
Zdroj: | Pediatr Blood Cancer |
ISSN: | 1545-5017 1545-5009 |
Popis: | Background Widespread implementation of electronic health records (EHR) has created new opportunities for pediatric oncology observational research. Little attention has been given to using EHR data to identify patients with pediatric hematologic malignancies. Methods This study used EHR-derived data in a pediatric clinical data research network, PEDSnet, to develop and evaluate a computable phenotype algorithm to identify pediatric patients with leukemia and lymphoma who received treatment with chemotherapy. To guide early development, multiple computable phenotype-defined cohorts were compared to one institution's tumor registry. The most promising algorithm was chosen for formal evaluation and consisted of at least two leukemia/lymphoma diagnoses (Systematized Nomenclature of Medicine codes) within a 90-day period, two chemotherapy exposures, and three hematology-oncology provider encounters. During evaluation, the computable phenotype was executed against EHR data from 2011 to 2016 at three large institutions. Classification accuracy was assessed by masked medical record review with phenotype-identified patients compared to a control group with at least three hematology-oncology encounters. Results The computable phenotype had sensitivity of 100% (confidence interval [CI] 99%, 100%), specificity of 99% (CI 99%, 100%), positive predictive value (PPV) and negative predictive value (NPV) of 100%, and C-statistic of 1 at the development institution. The computable phenotype performance was similar at the two test institutions with sensitivity of 100% (CI 99%, 100%), specificity of 99% (CI 99%, 100%), PPV of 96%, NPV of 100%, and C-statistic of 0.99. Conclusion The EHR-based computable phenotype is an accurate cohort identification tool for pediatric patients with leukemia and lymphoma who have been treated with chemotherapy and is ready for use in clinical studies. |
Databáze: | OpenAIRE |
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