This handbook aims to bridge the gap between healthcare domain knowledge and techincal analytics skills -- something I wish I had when starting my journey in this field.
I welcome your contributions, feedback, and suggestions as we continue to build this resource together. Whether you're a seasoned healthcare analytics professional or just starting your journey, there's a place for you in this community!
I like the Data Roles Continuum created by Zack Wilson. For comprehensive data engineering resources, his Data Engineer Handbook is excellent.
It's interesting to note that while many healthcare analytics professionals are titled "data analyts" or "data scientists", they frequently perform tasks fall under "data engineering." This is why many end up functioning as "analytics engineers" in practice.
Across all fields, professionals typically need three essential capabilities: business knowledge, soft skills, and hard skills.
- Chapter 1: Healthcare System Fundamentals
- Chapter 2: Healthcare Data Landscape
- Chapter 3: Healthcare Analytics Use Cases
- Chapter 4: Healthcare Data Architecture
- Chapter 5: Data Modeling for Healthcare
- Chapter 6: SQL for Healthcare Analytics
- Chapter 7: Visualization for Healthcare Data
- Chapter 8: Advanced Analytics in Healthcare
- Chapter 9: Collaboration with Healthcare Stakeholders
- Chapter 10: Healthcare Analytics Project Management
- Chapter 11: Translating Business Questions to Analytics
- Chapter 12: Ethical Consideration in Healthcare Analytics
- Blogs
- Books
- Courses
- Guiding Principles
- Journals
- Newsletters
- Open Data
- Projects
- Repos
- Summer Internship
- Websites
- An Introduction to Claims Data
- Google Health Health AI Developer Foundations
- Thoughs on Healthcare Markets and Technology
- Analytics and AI for Healthcare: Book Series
- Digital Health: A Primer
- Dimensions of Intelligent Analytics for Smart Digital Health Solutions
- Translational Application of Artificial Intelligence in Healthcare: - A Textbook
- Data Driven Science for Clinically Actionable Knowledge in Diseases
- Data Analysis in Medicine and Health using R
- Explainable AI in Healthcare: Unboxing Machine Learning for Biomedicine
- Clinical Intelligence: The Big Data Analytics Revolution in Healthcare: A Framework for Clinical and Business Intelligence
- Clinical Research Methods for Surgeons
- Geek Doctor: Life as Healthcare CIO
- Health Economics and Policy
- Healthcare Analytics Made Simple: Techniques in healthcare computing using machine learning and Python
- Healthcare Big Data Draft in Chinese
- Healthcare Data Analytics
- Healthcare Data Analytics: Primary Methods and Related Insights
- Interpreting the Medical Literature
- Multivariable Analysis: A Practical Guide for Clinicians and Public Health Researchers
- Practical Biostatistics for Medical and Health Sciences
- Reproducible Medical Research with R
- SAS Data Analytic Development: Dimensons of Software Quality
- SAS Programming with Medicare Administrative Data
- Study Design and Statistical Analysis: A Practical Guide for Clinicians
- The CMIO Survival Guide: A Handbook for Chief Medical Information Officers and Those Who Hire Them
- The Project Manager's Guide to Health Information Technology Implementation
- The Truth about Health Care: Why Reform is Not Working in America
- Veridical Data Science
- AI in Health Care
- Cleaning Medical Data in R
- Machine Learning for Healthcare
- Health Policy 101
- HealthR
- Regression Modeling Strategies Short Course
- Health Innovation
- Healthcare Brew
- Learn Analytics Engineering
- Medical Futurist
- The Analytics Engineering Roundup
-
Centers for Disease Control and Prevention (CDC) Open Technology
-
Centers for Medicare & Medicaid Services (CMS) Public Data Sets
- The TUVA project
- The Tuva Project is a large collection of tools organized into many GitHub repos that transform raw healthcare data into quality-tested data that is ready for analysis and machine learning. At the center of the project is the Tuva data model, a standard data model designed for healthcare analytics. These docs describe how to install, use, and contribute to the Tuva Project.
- CDC
- CMS
- Healthcare-Analytics
- Hospital admission data was analyzed to accurately predict the patient’s Length of Stay at the time of admit so that the hospitals can optimize resources and function better.
Here's the mostly comprehensive list of data engineering creators:
Name | YouTube |
X/Twitter |
TikTok |
||
---|---|---|---|---|---|
Chad You | Chad You | Chad You | |||
Andrea Hobby | Andrea Hobby | ||||
Madison Schott | Madison Schott | ||||
Tristan Handy | Tristan Handy | ||||
Benjamin Rogojan | Seattle Data Guy | Benjamin Rogojan | SeattleDataGuy | ||
Zack Wilson | Data with Zach | Zach Wilson | Zach Morris Wilson |