日本行政数据库中记录的呼吸系统疾病诊断的有效性。
Validity of diagnoses of respiratory diseases recorded in a Japanese administrative database.
机构信息
Department of Respiratory Medicine, Japanese Red Cross Medical Center, Tokyo, Japan.
Department of Respiratory Medicine, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
出版信息
Respir Investig. 2023 May;61(3):314-320. doi: 10.1016/j.resinv.2023.01.009. Epub 2023 Mar 1.
BACKGROUND
Validating the information recorded in administrative databases is essential. However, no study has comprehensively validated the accuracy of Japanese Diagnosis Procedure Combination (DPC) data on various respiratory diseases. Therefore, this study aimed to evaluate the validity of diagnoses of respiratory diseases in the DPC database.
METHODS
We conducted chart reviews of 400 patients hospitalized in the departments of respiratory medicine in two acute-care hospitals in Tokyo, between April 1, 2019 and March 31, 2021, and used them as reference standards. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of DPC data on 25 respiratory diseases were determined.
RESULTS
Sensitivity ranged from 22.2% (aspiration pneumonia) to 100% (chronic eosinophilic pneumonia and malignant pleural mesothelioma) and was <50% for eight diseases, while specificity was >90% for all diseases. PPV ranged from 40.0% (aspiration pneumonia) to 100% (coronavirus disease 2019, bronchiectasis, chronic eosinophilic pneumonia, pulmonary hypertension, squamous cell carcinoma, small cell carcinoma, lung cancer of other histological types, and malignant pleural mesothelioma) and was >80% for 16 diseases. Except for chronic obstructive pulmonary disease (82.9%) and interstitial pneumonia (other than idiopathic pulmonary fibrosis) (85.4%), NPV was >90% for all diseases. These validity indices were similar in both hospitals.
CONCLUSIONS
The validity of diagnoses of respiratory diseases in the DPC database was high in general, thereby providing an important basis for future studies.
背景
验证行政数据库中记录的信息至关重要。然而，尚无研究全面验证日本诊断程序组合（DPC）数据在各种呼吸系统疾病中的准确性。因此，本研究旨在评估 DPC 数据库中呼吸系统疾病诊断的准确性。
方法
我们对 2019 年 4 月 1 日至 2021 年 3 月 31 日期间在东京两家急症医院呼吸内科住院的 400 名患者进行了病历回顾，并将其作为参考标准。确定了 25 种呼吸系统疾病的 DPC 数据的灵敏度、特异性、阳性预测值（PPV）和阴性预测值（NPV）。
结果
灵敏度范围为 22.2%（吸入性肺炎）至 100%（慢性嗜酸性粒细胞性肺炎和恶性胸膜间皮瘤），8 种疾病的灵敏度<50%，而特异性均>90%。PPV 范围为 40.0%（吸入性肺炎）至 100%（2019 年冠状病毒病、支气管扩张、慢性嗜酸性粒细胞性肺炎、肺动脉高压、鳞状细胞癌、小细胞癌、其他组织学类型的肺癌和恶性胸膜间皮瘤），16 种疾病的 PPV>80%。除慢性阻塞性肺疾病（82.9%）和间质性肺炎（非特发性肺纤维化）（85.4%）外，所有疾病的 NPV 均>90%。这两个医院的这些有效性指标相似。
结论
总体而言，DPC 数据库中呼吸系统疾病诊断的准确性较高，为未来的研究提供了重要依据。
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