I wrote this book because I found existing materials too academic and wanted to provide a no-nonsense, practical guide with just the bare minimum of information to get readers fluent in the language of all the distinct health data streams. Regardless of whether you are a data scientist who pushes two commits per day to Github, an executive who wants to speak the language of a new domain, or an entrepreneur looking for their next app idea, this book can help you.

This book is perfect for mid-career tech professionals who want to transition into healthcare from another industry. If this is you, then you’re in the right place and I’m glad you are here. Welcoming technologists with a finance, retail, or manufacturing background into healthcare delivery and technology organizations is critical, given that 28% of health systems say that having too few staff with data science skills is preventing them from becoming more data driven.

This book is also for data analysts and data scientists in healthcare who want to expand their knowledge. I have worked with PhDs who spent their entire careers writing software genomic sequencing data and have no understanding of the clinical data within Electronic Health Record systems (EHRs). I have also worked with career state employees who could list off every detail of a standard medical claims extract but could not tell you a single fact about pharmacy claims. If you work within any healthcare domain, you know that this is the rule rather than the exception. However, if we are to modernize medicine we must foster a more expansive view of health data so that we can do things such as understand the real-world clinical impact of gene therapies or fully represent a patient’s interactions with the health system.