Webinar on Next Generation Scenario Planning Models For Healthcare in partnership with the SCIP

Watch this insightful "Next Generation Scenario Planning Models for Healthcare" webinar, presented in partnership with the Strategic Consortium of Intelligence Professionals (SCIP). Featured speakers include Oliver Guirdham, CEO of The Business Research Company, who brings over two decades of experience leading successful projects for industry giants, and Ravi Kiran, Director of Healthcare & Lifesciences Market Research, with over a decade of expertise in biotechnology and impactful insights. Discover advanced forecasting models and gain valuable insights into the future of healthcare.
The webinar explored various forecasting models pertinent to the healthcare industry, focusing on three primary methodologies. Firstly, epidemiology-driven prediction leverages disease incidence and prevalence data to forecast healthcare needs and outcomes. Secondly, prescription-driven prediction relies on prescription trends and patterns to anticipate future drug demand and usage. Lastly, sales-driven prediction utilizes historical sales data and market trends to project future sales volumes and revenue streams in the healthcare sector. Each of these methodologies provides unique insights and aids in strategic planning and resource allocation.
In addition to these methodologies, the webinar also highlighted the diverse tools used in major models, including statistical methods, AI-ML based techniques, hybrid models, and qualitative approaches. Statistical methods offer robust and traditional means of analysis, while AI and machine learning techniques bring advanced capabilities in handling large datasets and uncovering complex patterns. Hybrid models combine the strengths of different approaches to enhance prediction accuracy. Qualitative models, on the other hand, incorporate expert opinions and subjective insights, adding a valuable dimension to forecasting in the healthcare industry. Together, these tools and models enable comprehensive and effective forecasting, facilitating better decision-making and resource management.
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