Table 4.
Gastrointestinal bleeding and/or proton pump inhibitors | |||||
Country/Region | Database | Area of research | Sample size | Design, statistical methods and 3V | Application |
Taiwan, China | Taiwan National Health Insurance Database (NHID) | PUD | 403567 | Nationwide retrospective cohort study | Effect of H. pylori therapy and PPIs on PUD |
Wu et al[58], 2009 | |||||
Volume, Velocity and Variety | |||||
PUD | 32235 | Nationwide retrospective cohort study | Risk of rebleeding from PUD in ESRD patients | ||
Wu et al[95], 2011 | |||||
Volume, Velocity and Variety | |||||
PPIs | 6552 | Nationwide retrospective cohort study | Effect of clopidogrel and PPIs on ACS | ||
Volume, Velocity and Variety | |||||
Wu et al[59], 2010 | |||||
South Korea | Korean Health Insurance Review and Assessment Service (HIRA) | PPIs | 59233 | Nationwide retrospective cohort study | Effect of PPIs on thrombotic risk |
Kim et al[96], 2019 | |||||
Volume, Velocity and Variety | |||||
Hong Kong, China | Clinical Data Analysis and Reporting System (CDARS) | Dabigatran | 5041 | Territory-wide retrospective cohort study | Risk factors for dabigatran-associated gastrointestinal bleeding |
Chan et al[62], 2015 | |||||
Volume, Velocity and Variety |
This list is not exhaustive, but serves to provide a few distinct examples of how Big Data analysis can generate high-quality research outputs in the field of gastroenterology and hepatology. 3V: Volume/velocity/variety; PUD: Peptic ulcer disease; H. pylori: Helicobacter pylori; PPIs: Proton pump inhibitors; ESRD: End-stage renal disease; ACS: Acute coronary syndrome.