Data-driven decision-making in medical education and healthcare

Data-driven decision-making in medical education and healthcare

This book is divided into three main sections:

1. The big picture (general background and methodologies)
2. Medical and healthcare education in selected case studies
3. Health information and statistics in selected case studies

Each chapter, except the big picture, has the same format describing a particular project result as a case study, which is always based on a well-proven interdisciplinary methodology (specifically CRISP-DM – Cross-Industry Process for Data Mining – the structured approach to planning and running data mining projects.

• As a methodology, it includes descriptions of individual project phases, the tasks involved with each stage, and the relationships between them.
• As a process model, it provides an overview of the complete data mining life cycle.