Clinical Data Mining and EHR Analysis with MIMIC-III

Modern healthcare generates massive amounts of data, yet unlocking its potential requires specialized skills in managing Electronic Health Records (EHR). This text-based course guides you through the fundamentals of clinical data mining using the industry-standard MIMIC-III database. By the end of this course, you will transition from understanding basic clinical database structures to confidently querying complex schemas, mapping research questions to data, and extracting critical patient outcomes. You will learn to: Understand the fundamental structure and terminology of Electronic Health Record (EHR) databases; Query clinical databases using SQL to extract patient cohorts and demographic details; Navigate the MIMIC-III relational schema to locate diagnostic, laboratory, and prescription tables; Apply International Classification of Diseases (ICD) coding to map specific clinical outcomes and diagnoses; Analyze patient timelines and clinical events using structured data-mining techniques; Address ethical considerations, data privacy, and de-identification standards in healthcare research. The curriculum begins with foundational concepts of health informatics and relational database designs before progressing to hands-on SQL queries and practical data extraction scenarios. You will read through clear explanations, study structured code snippets, and complete written exercises to reinforce your learning. Designed for beginners, this course requires no prior experience in healthcare informatics or database administration, making it ideal for aspiring data analysts, clinical researchers, and software developers entering the health-tech space. Start your journey into clinical data science today.