
Clinical research informatics is a sub-domain of biomedical informatics that involves the use of informatics in the discovery and application of new knowledge relating to health and diseases and better treatment strategies. It includes the management of processing information in respect to human system integration with machine and data. In other words, all biomedical informatics involved with clinical research is called clinical research informatics. Clinical research informatics (CRI) has recently emerged as an important domain of transition and also in supporting clinical trials, which are often a complex and highly resource intensive process. With its evolution, in the last few years, the various organizations like the government, academic, and private sectors have showed their interest in the scientific and financial aspect in the conduct and outcomes of clinical research trials. Clinical researchers have been facing significant challenges in conducting the clinical research trials, as it involves a complex workflow process, like gathering information management requirements, data storage, accessibility, reliability, and ethical issues. The easy access to adequate and efficacious high-quality, reliable data information is important to solve the hurdles faced in clinical trials; therefore, an expeditious transformation of biomedical informatics tools and technologies is the need of the hour. Hence, clinical research informatics should specifically designed advanced tools and methods to address the clinical research information management requirements and it should be technologically upgraded with time. Uniform standard and robust guidelines should be prepared to protect patient privacy and confidentiality of data, with an advanced network security safeguard system.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
