Decoding Health Data

A Practical Guide From Genomics to EHRs to Insurance Claims

Daniel Feller, PhD

A practical guide to the data types, standards, and formats behind modern health AI — written for mid-career tech professionals and data scientists entering healthcare, and for healthcare data professionals who want to broaden their knowledge across data streams.

Part I: Getting Started

• Who Should Read This Book
• How to Read This Book
• How Healthcare Is Delivered
• A Primer on Healthcare Vocabularies

Part II: Administrative Data

• Medical Claims
• Pharmacy Claims

Part III: Clinical Data

• Electronic Health Records
• Medical Imaging
• Clinical Trial Data
• Molecular Sequencing

Part IV: Patient-Generated Data

• Vital Signs Monitoring
• Adherence Monitoring Technology
• Activity & Lifestyle
• Patient-Reported Outcomes
• Complex & Unstructured Data
• The Patient-Generated Data of the Future

Working with Health Data

• Methods to De-Identify Health Data
• Putting It All Together: Multimodal Data Streams

© Daniel Feller. Licensed under CC BY-NC 4.0. Free for educational and non-commercial use with attribution. Cite as: Feller, D. Decoding Health Data. danieljfeller.github.io/book. For commercial licensing, contact danieljfeller@gmail.com.