Validation of DPC data for identifying stroke cases in a large-scale cohort study

2020 Fiscal Year Final Research Report

• Project/Area Number: 17K09126
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Epidemiology and preventive medicine
• Research Institution: Iwate Medical University
• Principal Investigator: Tanno Kozo 岩手医科大学, 医学部, 特任教授 (20327026)
• Project Period (FY): 2017-04-01 – 2021-03-31
• Keywords: 循環器・高血圧 / コホート研究 / 脳血管疾患 / レセプト情報

Outline of Final Research Achievements

To validate stroke determination by DPC data, data from a prospective cohort study were used in this study. 2,025 study participants who were admitted to a hospital in the study area between 2009 and 2014 were included. Sensitivity, positive predictive value (PPV), and kappa coefficient were calculated for stroke cases extracted from DPC data (DPC extracted cases) using cases registered in the Iwate Stroke Registry (stroke registry cases) as the gold standard. The sensitivity, PPV, and kappa coefficient were 0.789, 0.967, and 0.849, respectively. The incidence rate of stroke was 12.0 in the stroke registry cases and 9.8 in the DPC extracted cases. This study suggests that DPC data can be used to identify strokes in cohort studies although it may underestimate absolute risks such as incidence rates.

Free Research Field

疫学・公衆衛生学

Academic Significance and Societal Importance of the Research Achievements

国外では傷病名の妥当性を評価した上で、医療データはコホート研究のアウトカムとして利用されている。本研究は地域ベースの前向きコホート研究において医療データ（今回はDPCデータ）をアウトカムとして用いた国内で初めての研究と考えられる。本研究ではDPCデータ等のリアルワールドデータが大規模前向きコホート研究のアウトカムとして利用できる可能性を示した。リアルワールドデータを利活用することで大規模コホートにおいても一定の様式で追跡情報を収集することが可能になることが期待される。