abstract

Effective information management is fundamental to pharmacovigilance, which is the study and practice of identifying, evaluating, comprehending, and preventing adverse effects and other drug-related issues. Pharmacovigilance relies on reliable information systems that allow for the gathering of adverse event reports from many stakeholders, including healthcare providers, patients, and others. The ever-changing landscape of data sources, with a focus on how EHRs, wearable tech, and real-world evidence may be combined to provide a more comprehensive picture for analysis. By automating signal identification and predictive modelling, innovative technologies like machine learning and artificial intelligence are revolutionizing pharmacovigilance. Using such techniques to filter through massive datasets, finding any safety issues and helping regulators make decisions. In addition, the abstract explores the significance of regulatory bodies, pharmaceutical corporations, and healthcare providers exchanging structured information. Proactively responding to emerging risks and developing successful risk management strategies are both made possible by the timely and transparent transmission of safety information. A never-ending process of data management strategy review in order to keep up with the ever-changing demands of healthcare and pharmaceutical innovation. The abstract essentially shows how pharmacovigilance and information management work hand in hand, and how important it is to use varied and high-quality data effectively to improve medication safety standards and protect public health.