Utility of medical record diagnostic codes to ascertain attention-deficit/hyperactivity disorder and learning disabilities in populations of children

BMC Pediatrics

Yu Shi¹  David O. Warner¹  Danqing Hu¹  Randall P. Flick²  Andrew C. Hanson³  Phillip J. Schulte³  Sheri Crow⁴  Michael J. Zaccariello⁵ 

[1]Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 1st St SW, 55905, Rochester, MN, USA

[2]Department of Anesthesiology and Perioperative Medicine, Mayo Clinic, 200 1st St SW, 55905, Rochester, MN, USA

[3]Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, USA

[4]Department of Health Sciences Research, Mayo Clinic, Rochester, USA

[5]Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, USA

[6]Department of Psychiatry and Psychology, Mayo Clinic, Rochester, USA

关键词: Attention-deficit/hyperactivity disorder;    Learning disability;    Diagnostic code;    Machine learning;    Validation;   

DOI  :  10.1186/s12887-020-02411-3

来源: Springer

【 摘 要 】

BackgroundTo develop and evaluate machine learning algorithms to ascertain attention-deficit/hyperactivity (ADHD) and learning disability (LD) using diagnostic codes in the medical record.MethodDiagnoses of ADHD and LD were confirmed in cohorts of children in Olmsted County of Minnesota based on validated research criteria. Models to predict ADHD and LD were developed using ICD-9 codes in a derivation cohort of 1057 children before evaluated in a validation cohort of 536 children.ResultsThe ENET-MIN model using selected ICD-9 codes at prior probability of 0.25 has a sensitivity of 0.76, PPV of 0.85, specificity of 0.98, and NPV of 0.97 in the validation cohort. However, it does not offer significant advantage over a model using a single ICD-9 code of 314.X, which shows sensitivity of 0.81, PPV of 0.83, specificity of 0.98, and NPV of 0.97. None of the models developed for LD performed well in the validation cohort.ConclusionsIt is feasible to utilize diagnostic codes to ascertain cases of ADHD in a population of children. Machine learning approaches do not have advantage compared with simply using a single family of diagnostic codes for ADHD. The use of medical record diagnostic codes is not feasible to ascertain LD.

【 授权许可】

CC BY