Introducing CRISP-PIP: A Cross-Industry Standard Process Framework to Empower Translation of Big Data into Actionable Population Insight Products for Healthcare

Healthcare is generating vast amounts of data, offering opportunities to improve care quality, efficiency, and outcomes. Big Data Analytics enables the transformation of complex data into actionable tools - Population Insight Products (PIPs) - such as dashboards or predictive models. These tools can support evidence-based, participatory decision-making. Yet, Big Data Analytics adoption in healthcare is hindered by technical, organisational, legal, and user-related challenges. Existing frameworks like CRISP-MED-DM offer a process for data mining in healthcare but lack integration of open science principles and stakeholder collaboration. To bridge this gap, we developed CRISP-PIP - a participatory framework aligned with FAIR (Findable,<br/>Accessible, Interoperable, and Reusable) data principles to guide the structured development and implementation of PIPs.