Impacts and regional disparities of COVID-19 using large-scale databases

2022 Fiscal Year Final Research Report

• Project/Area Number: 21K21136
• Research Category: Grant-in-Aid for Research Activity Start-up
• Allocation Type: Multi-year Fund
• Review Section: 0908:Society medicine, nursing, and related fields
• Research Institution: Kyoto University
• Principal Investigator: Shin Jung-ho 京都大学, 医学研究科, 特定講師 (00911934)
• Project Period (FY): 2021-08-30 – 2023-03-31
• Keywords: COVID-19 / 新型コロナウイルス感染症 / DPC / NDB / 大規模データベース / リアルワールドデータ / Withコロナ

Outline of Final Research Achievements

We analyzed the short-term and medium-term impact of COVID-19 on the healthcare system using nationwide multicenter DPC data and the National Database of Health Insurance Claims and Specific Health Checkups of Japan (NDB) of the Ministry of Health, Labor and Welfare. Furthermore, we also analyzed the impact of COVID-19 on the healthcare system of each secondary medical area, and examined the correlation between the population density of the secondary medical area and changes in healthcare provision during each wave of the COVID-19 spread, as well as differences in trends during each wave of infection. Our results suggested large-scale data such as DPC and NDB were effective in monitoring, evaluation, and analysis for providing stable medical services according to regional characteristics.

Free Research Field

公衆衛生学

Academic Significance and Societal Importance of the Research Achievements

「Withコロナ」時代に、地域の特性に合わせて安定した医療サービスの提供を行うための精度、政策の立案のためには、現状をタイムリーにモニタリング、評価、分析する必要がある。本研究でDPC、NDBなどの大規模データは、定期的に収集されるリアルワールドデータであり、不確実性の高いCOVID-19の医療システムへの影響について、迅速に分析できることを示した。しかし、NDBは利用までの手続きに数か月以上の時間を要し、今後、さらなる活用のためにはデータ利用までの期間を短縮する必要性が示唆された。