- 著者
-
Aki Kuwauchi
Satomi Yoshida
Chikashi Takeda
Yugo Yamashita
Takeshi Kimura
Masato Takeuchi
Koji Kawakami
- 出版者
- Japan Epidemiological Association
- 雑誌
- Journal of Epidemiology (ISSN:09175040)
- 巻号頁・発行日
- pp.JE20220360, (Released:2023-04-22)
- 参考文献数
- 27
BackgroundAcute pulmonary embolism (PE) is a life-threatening in-hospital complication. Recently, several studies have reported the clinical characteristics of PE among Japanese patients using the diagnostic procedure combination (DPC)/per diem payment system database. However, the validity of PE identification algorithms for Japanese administrative data is not yet clear. The purpose of this study was to evaluate the validity of using DPC data to identify acute PE inpatients.MethodsThe reference standard was symptomatic/asymptomatic PE patients included in the COntemporary ManageMent AND outcomes in patients with Venous ThromboEmbolism (COMMAND VTE) registry, which is a cohort study of acute symptomatic venous thromboembolism (VTE) patients in Japan. The validation cohort included all patients discharged from the 6 hospitals included in both the registry and DPC database. The identification algorithms comprised diagnosis, anticoagulation therapy, thrombolysis therapy, and inferior vena cava filter placement. Each algorithm’s sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were estimated.ResultsA total of 43.4% of the validation cohort was female, with a mean age of 67.3 years. The diagnosis-based algorithm showed a sensitivity of 90.2% (222/246, 95% CI; 85.8–93.6), a specificity of 99.8% (228,485/229,027, 95% CI; 99.7–99.8), a PPV of 29.1% (222/764, 95% CI; 25.9–32.4) and an NPV of 99.9% (228,485/229,509, 95% CI; 99.9–99.9) for identifying symptomatic/asymptomatic PE. Additionally, 94.6% (159/168, 95% CI; 90.1–97.5) of symptomatic PE patients were identified by the diagnosis-based algorithm.ConclusionsThe diagnosis-based algorithm may be a relatively sensitive method for identifying acute PE inpatients in the Japanese DPC database.