Clinical Data Management (CDM) holds the entire life cycle of clinical data from its collection to exchange for statistical analysis in support of performing regulatory activities. It primarily focuses on data integrity and dataflow. Clinical Data Science (CDS) has expanded the scope of CDM by ensuring the data is reliable and credible. Risk-based data strategies are essential to consider as the most important component in the automation of clinical data management. Other solutions include identifying sites for clinical trials, targeting the right audience, recruiting the right patients, collecting reported outcomes, obtaining digital consent, remotely screening patients, and conducting decentralized trials.
Sponsors have incredibly increased the use of healthcare apps and digital health technologies to collect other real-world data (RWD) and reported outcomes. Over 200 new health apps are added every day to app stores. Phase IV is most likely of all clinical trial phases to witness experiments with digital health. However, this is unfortunate since it can improve the efficacy of clinical research trials in various ways.
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