Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Pharmacoepidemiol Drug Saf. 2021 Dec;30(12):1635-1642. doi: 10.1002/pds.5369. Epub 2021 Oct 15.
To validate healthcare claim-based algorithms for neurodevelopmental disorders (NDD) in children using medical records as the reference.
Using a clinical data warehouse of patients receiving outpatient or inpatient care at two hospitals in Boston, we identified children (≤14 years between 2010 and 2014) with at least one of the following NDDs according to claims-based algorithms: autism spectrum disorder/pervasive developmental disorder (ASD), attention deficit disorder/other hyperkinetic syndromes of childhood (ADHD), learning disability, speech/language disorder, developmental coordination disorder (DCD), intellectual disability, and behavioral disorder. Fifty cases per outcome were randomly sampled and their medical records were independently reviewed by two physicians to adjudicate the outcome presence. Positive predictive values (PPVs) and 95% confidence intervals (CIs) were calculated.
PPVs were 94% (95% CI, 83%-99%) for ASD, 88% (76%-95%) for ADHD, 98% (89%-100%) for learning disability, 98% (89%-100%) for speech/language disorder, 82% (69%-91%) for intellectual disability, and 92% (81%-98%) for behavioral disorder. A total of 19 of the 50 algorithm-based cases of DCD were confirmed as severe coordination disorders with functional impairment, with a PPV of 38% (25%-53%). Among the 31 false-positive cases of DCD were 7 children with coordination deficits that did not persist throughout childhood, 7 with visual-motor integration deficits, 12 with coordination issues due to an underlying medical condition and 5 with ADHD and at least one other severe NDD.
PPVs were generally high (range: 82%-98%), suggesting that claims-based algorithms can be used to study NDDs. For DCD, additional criteria are needed to improve the classification of true cases.
使用医疗记录作为参考，验证基于医疗保健索赔的儿童神经发育障碍（NDD）算法。
我们使用两家波士顿医院的门诊和住院患者的临床数据仓库，根据基于索赔的算法，确定了在 2010 年至 2014 年间至少患有以下一种 NDD 的儿童（≤14 岁）：自闭症谱系障碍/广泛性发育障碍（ASD）、注意力缺陷多动障碍/儿童多动综合征（ADHD）、学习障碍、言语/语言障碍、发育协调障碍（DCD）、智力障碍和行为障碍。每个结局随机抽取 50 例病例，并由两名医生独立审查病历以判断结局的存在。计算阳性预测值（PPV）和 95%置信区间（CI）。
ASD 的 PPV 为 94%（95%CI，83%-99%），ADHD 为 88%（76%-95%），学习障碍为 98%（89%-100%），言语/语言障碍为 98%（89%-100%），智力障碍为 82%（69%-91%），行为障碍为 92%（81%-98%）。50 例基于算法的 DCD 病例中，共有 19 例被确认为严重协调障碍伴功能障碍，PPV 为 38%（25%-53%）。在 31 例假阳性 DCD 病例中，有 7 例儿童的协调缺陷并未持续整个儿童期，7 例有视觉运动整合缺陷，12 例因潜在医疗状况导致协调问题，5 例患有 ADHD 和至少一种其他严重 NDD。
PPV 通常较高（范围：82%-98%），表明基于索赔的算法可用于研究 NDD。对于 DCD，需要额外的标准来提高真实病例的分类。
