Chapter 2 Introduction
2.1 How clinical data differs from other data types
Clinical data comes from a wide variety of sources and as such, requires careful consideration when designing, collecting, and analyzing this data. Unlike domains such as Finance or other areas in the sciences which predominantly use structured data, clinical data is often heterogeneous, integrating quantitative measurements, categorical data, subjective narratives from patient notes, and objective observations from doctor notes and even possible image analysis. Free text adds a layer of complexity with unstructured information, reflecting subjective patient experiences or qualitative insights from healthcare professionals. Furthermore, the contrast between patient and doctor notes reflects the dual perspectives of symptoms and formal diagnoses. In essence, clinical data’s unique blend of structured and unstructured components, along with its multidisciplinary nature, necessitates specialized methodologies for comprehensive analysis and interpretation in the realm of healthcare.