In today’s fast-paced pharmaceutical and healthcare landscape, real-time data is crucial for effective decision-making. Organizations are transitioning towards utilizing governed real-time insights to transform raw data into actionable intelligence, fostering agility and compliance. Notably, AI and machine learning are unlocking predictive insights from real-world evidence, which allow organizations to proactively address patient needs and market changes. Additionally, hyper-personalization in healthcare professional engagement is replacing traditional approaches.
Despite significant advancements, challenges such as fragmented data assets and latency in data delivery persist. Solutions like master data management and micro-batching are essential to ensure reliable and timely insights. Furthermore, the secure handling of sensitive HCP and patient data is vital to avoid compliance risks. Techniques that enhance the explainability of advanced models are also necessary to gain trust from stakeholders across various roles. As organizations mature in their use of data, technologies like digital twins and natural language processing are set to redefine the landscape, enabling smarter, evidence-based decisions across the field, leading to stronger public confidence.
👉 Pročitaj original: CIO Magazine
