Potential of Artificial Intelligence in Evidence-Based Practice in Nursing

人工智能在循证护理实践中的潜力

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Abstract

The arrival of new drug into the market requires many years of previous research along with the need of continuous evaluation throughout the lifetime of the drug. This warrants pharmacoepidemiological research which may be defined as the study of the use and the effects of drugs in large populations. Nowadays, this type of research seems more feasible thanks to the massive expansion of the information sources and data (e.g: clinical patient registries, electronic medical records). However, there is a risk of information overload, fragmented evidence and given the enthusiasm aroused by the "Big Data", it must be emphasized that its nature is mainly observational, and therefore subject to bias and confusion. The application of epidemiological methods in this scenario seems essential for any analysis. In short, the management and use of these data sources to generate useful information expansion is the next challenge for the application of research methods in modern pharmacoepidemiology.

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