春雨直播app

Pharmacoepidemiology is a field of public health that aims to improve people's health through the development and practice of methodologies for studying the use, safety, and efficacy of pharmaceuticals. Experimental research methods that artificially assign the administration or non-administration of a drug to be evaluated into two groups to compare efficacy and safety are called interventional studies, and are primarily used to prove the efficacy of pharmaceuticals. In interventional studies, results with less bias are obtained by managing patient visits, collecting new data, and aligning the characteristics between comparison groups. Data obtained under such experimental environments are "unrealistic" compared to general medical practice and have disadvantages such as a lack of generalizability; because the effects of the drug are easily demonstrated, they are referred to as "champion data." On the other hand, pharmacoepidemiology primarily uses observational research as its method, aiming for a more "realistic" evaluation using medical data generated under routine clinical practice rather than an experimental environment.

The arrival of the information society has enabled the research use of massive databases consisting of vast electronic medical record information and health insurance claims information; these are called "real-world data" as an antithesis to interventional studies. While these have traditionally been one of the information sources handled in observational research and can reduce the resources and costs for collecting new data from a vast number of patients, they also have drawbacks: necessary information for research may not be obtainable because only laboratory values already measured in clinical practice exist, and bias is always present in comparisons because the characteristics of patients who use a certain drug differ from those who do not. In hospital medical record information, the occurrence of medical events can only be fully captured during hospitalization, and follow-up during other periods is incomplete. In claims information, the lack of clinical information unrelated to insurance billing may cause inconveniences.

However, by not simply leaving these basic flaws of "real-world data" as limitations, but instead addressing them based on epidemiological theory, it is possible to link them to scientifically valid research results. Research using Danish "real-world data" proved the safety of antipyretic analgesic use in COVID-19 patients and had a major impact on global health authorities. I am also constantly conscious of data limitations and methods for dealing with bias, but I continue my research while finding the feeling of "taming a bucking bronco" to be quite interesting.