Validation of Neurologic Impairment Diagnosis Codes as Signifying Documented Functional Impairment in Hospitalized Children.

Academic pediatrics(2021)

引用 2|浏览10
暂无评分
摘要
OBJECTIVE:To assess the performance of previously published high-intensity neurologic impairment (NI) diagnosis codes in identification of hospitalized children with clinical NI. METHODS:Retrospective study of 500 randomly selected discharges in 2019 from a freestanding children's hospital. All charts were reviewed for 1) NI discharge diagnosis codes and 2) documentation of clinical NI (a neurologic diagnosis and indication of functional impairment like medical technology). Test statistics of clinical NI were calculated for discharges with and without an NI diagnosis code. A sensitivity analysis varied the threshold for "substantial functional impairment." Secondary analyses evaluated misclassified discharges and a more stringent definition for NI. RESULTS:Diagnosis codes identified clinically documented NI with 88.1% (95% confidence interval [CI]: 84.7, 91) specificity, and 79.4% (95% CI: 67.3, 88.5) sensitivity; negative predictive value (NPV) was 96.7% (95% CI: 94.8, 98.0), and positive predictive value (PPV) was 49% (95% CI: 42, 56.1). Including children with milder functional impairment (lower threshold) resulted in NPV of 95.7% and PPV of 77.5%. Restricting to children with more severe functional impairment (higher threshold) resulted in NPV of 98.2% and PPV of 44.1%. Misclassification was primarily due to inclusion of children without functional impairments. A more stringent NI definition including diagnosis codes for NI and feeding tubes had a specificity of 98.4% (95% CI: 96.7-99.3) and sensitivity of 28.6% (19.4-41.3). CONCLUSIONS:All scenarios evaluated demonstrated high NPV and low-to-moderate PPV of the diagnostic code list. To maximize clinical utility, NI diagnosis codes should be used with strategies to mitigate the risk of misclassification.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要