Why the study?
The validity of acute pulmonary embolism identification algorithms using Japanese administrative data was not yet clear.
Do identification algorithms using Japanese administrative data validly identify acute pulmonary embolism inpatients compared to a clinical registry?
Do identification algorithms using Japanese administrative data validly identify acute pulmonary embolism inpatients compared to a clinical registry?
A diagnosis-based algorithm using the Japanese DPC administrative database is highly sensitive and specific for identifying acute pulmonary embolism inpatients, though its positive predictive value is low.
Supports PE case identification in Japanese claims data for research; leaves open refinement to address low PPV before broader application.
BACKGROUND: Acute 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. METHODS: The 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 six 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. RESULTS: A 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% confidence interval [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 using the diagnosis-based algorithm. CONCLUSION: The diagnosis-based algorithm may be a relatively sensitive method for identifying acute PE inpatients in the Japanese DPC database.
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Kuwauchi et al. (2023) studied this question.
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