Department of Internal Medicine, Endocrine Research Institute, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.
Department of Internal Medicine, Yonsei Wonju College of Medicine, Wonju, Korea.
J Korean Med Sci. 2022 Aug 15;37(32):e249. doi: 10.3346/jkms.2022.37.e249.
We analyzed the International Classification of Diseases, 10th edition (ICD-10) diagnostic codes, procedure codes, and radiographic image codes for vertebral fracture (VF) used in the database of Health Insurance Review and Assessment Service (HIRA) of Korea to establish a validated operational definition for identifying patients with osteoporotic VF in claims data.
We developed three operational definitions for detecting VFs using 9 diagnostic codes, 5 procedure codes and 4 imaging codes. Medical records and radiographs of 2,819 patients, who had primary and subordinated codes of VF between January 2016 and December 2016 at two institutions, were reviewed to detect true vertebral fractures. We evaluated the sensitivity and positive predictive value (PPV) of the operational definition in detecting true osteoporotic VF and obtained the receiver operating characteristic (ROC) curve.
Among the 2,819 patients who had primary or secondary diagnosis codes for VF, 995 patients satisfied at least one of the criteria for the operational definition of osteoporotic VF. Of these patients, 594 were judged as having true fractures based on medical records and radiographic examinations. The sensitivity and PPV were 62.5 (95% confidence interval [CI], 59.4-65.6) and 59.7(95% CI, 56.6-62.8) respectively. In the receiver operating characteristic analysis, area under the curve (AUC) was 0.706 (95% CI, 0.688-0.724).
Our findings demonstrate the validity of our operational definitions to identify VFs more accurately using claims data. This algorithm to identify VF is likely to be useful in future studies for diagnosing osteoporotic VF.
我们分析了韩国健康保险审查与评估服务（HIRA）数据库中使用的国际疾病分类第 10 版（ICD-10）诊断代码、程序代码和影像学代码，以建立一种经验证的、用于从索赔数据中识别骨质疏松性椎体骨折（VF）患者的操作性定义。
我们使用 9 个诊断代码、5 个程序代码和 4 个影像学代码开发了三种用于检测 VF 的操作性定义。对两家机构在 2016 年 1 月至 2016 年 12 月期间有原发性和次要 VF 编码的 2819 例患者的病历和 X 线片进行了回顾，以检测真正的椎体骨折。我们评估了操作性定义检测真正的骨质疏松性 VF 的敏感性和阳性预测值（PPV），并获得了受试者工作特征（ROC）曲线。
在 2819 例有原发性或继发性 VF 诊断代码的患者中，有 995 例符合骨质疏松性 VF 操作性定义标准中的至少一条。在这些患者中，根据病历和影像学检查，有 594 例被判断为存在真正的骨折。敏感性和 PPV 分别为 62.5%（95%置信区间[CI]，59.4-65.6）和 59.7%（95% CI，56.6-62.8）。在 ROC 分析中，曲线下面积（AUC）为 0.706（95%CI，0.688-0.724）。
我们的研究结果表明，我们的操作性定义能够更准确地识别索赔数据中的 VF，具有有效性。这种用于识别 VF 的算法可能对未来诊断骨质疏松性 VF 的研究有用。
