COVID-19 Patients Analysis Utilizing JAPAN and US Claims Databases
Author(s)
Kim SW1, Ishii T2, Takeno S2, Kado Y2, Tamai Y2, Akiyama T2, Yu E2, Demiya S2
1IQVIA Solutions Japan, Minato, 13, Japan, 2IQVIA Solutions Japan, Minato-ku, Tokyo, Japan
OBJECTIVES : COVID-19 has been spread globally and its profound impact has been threatening in all patients and healthcare providers throughout all nations for more than one year. Until now small studies have been reported; however, big data analysis using real-world data has not been published yet. Therefore, this study investigated COVID-19 patients’ demographic characteristics, comorbidities and treatment in Japan, and comparison with the US. METHODS This retrospective study used the IQVIA Claims database which integrated the payer claims data of the health insurance union for Japanese workers, and the IQVIA PharMetrics® Plus database which is the largest claims database of fully adjudicated medical and pharmacy claims data of national and sub-national health plans and self-insured employer groups in the US. COVID-19 patients were identified between January and June in Japan and between January and March 2020 in the US. Analysis was performed using IQVIA Evidence 360 (E360), a Software-as-a-Service Platform containing global real-world datasets. RESULTS From 349 and 1,105 patients having diagnosis of COVID-19, Genders were 58.5% and 57.6% in male in Japan and the US, respectively. Moreover, the mode age groups were 30-34 (11.2%) and 55-64 (38.2%), respectively. The major comorbidities were diabetes (33.2%), hypertension (17.8%) and hyperlipidemia (12.9%) in Japan, and hypertension (64.9%), hyperlipidemia (48.5%) and diabetes (36.9%) in the US. Main treatments used in Japan were antipyretic-analgesics, antibiotics and steroid. In the US, antibiotics, steroid, opioid painkillers were used. CONCLUSIONS Japanese and US COVID-19 patients showed similar demographics. However, differences in comorbidities and treatments exists. Other differences are currently being investigated more precisely with accumulated real-world data.
Conference/Value in Health Info
2021-05, ISPOR 2021, Montreal, Canada
Value in Health, Volume 24, Issue 5, S1 (May 2021)
Code
PIN46
Topic
Clinical Outcomes, Epidemiology & Public Health, Real World Data & Information Systems
Topic Subcategory
Clinical Outcomes Assessment, Disease Classification & Coding, Health & Insurance Records Systems
Disease
Infectious Disease (non-vaccine)