HEALTH DATA ANALYTICS

Free Online Courses

• RITX: Advanced Level (8 weeks 8-10 hours per week)

• Module One: Introduction to Healthcare

• Components of Healthcare
• Challenges & Opportunities
• Systems Approach
• Healthcare Trends
• Module Two: Introduction to Health Informatics
• Overview of Health IT
• Health IT Systems & Components
• EHR Adoption
• Interoperability & HIT Standards
• Public Health IT & Consumer Engagement
• Module Three: Introduction to Data Analytics
• Data Terms & Concepts
• Getting Data Ready for Analysis
• Data Governance, Privacy, and Security
• Analysis With Artificial Intelligence
• Making Data Usable to Others
• Module Four: Introduction to Visualizations
• Value of Visualization
• Visualization Best Practices

• Free ($249 Verified Certificate)

• DoaneX: Intermediate Level (3 weeks 5-10 hours per week)
• Define Population Health, Health Informatics and Public Health
• Describe the difference and connection between Population Health and Informatics
• Compare how population health is being managed through Health Informatics
• Apply the concepts of informatics to understand how healthcare is changing the health of the population
• Discuss emerging trends in health informatics
• Recognize informatics solutions for public health challenges
• Free ($149 Verified Certificate)

Podcasts and Videos

• "Healthcare is seeing a huge influx of data from many different sources. With so much data comes the extraordinary potential of predictive analytics that can help with prevention, wellness management, fraud detection and more. This podcast offers a great opportunity to learn more about the power of predictive analytics."
• Host: Shahid Shah
• Guest: Anand Mahurkar

• "Analytics is a key enabler for life sciences and healthcare organizations to create better outcomes for patients, customers and other stakeholders in healthcare. The IBM Institute for Business Value recently released a new study titled “Analytics across the ecosystem - A prescription for optimizing healthcare outcomes.” This study discovered that almost two-thirds of organizations across the healthcare ecosystem have analytics strategies in place, but how many of those are being effective?"
• Host: Heather Fraser

Paid Online Courses

• Georgia Tech: Introductory Level
• Health Informatics: A Current & Historic Perspective (5 weeks 10-11 hours per week)
• The major challenges facing healthcare delivery systems around the world
• The key issue of chronic disease and the critical role informatics can play in managing it
• The potential of electronic health records (EHRs)
• The challenges to the design and usability EHRs
• The twin challenges of EHR adoption and data sharing
• The critical role of patient engagement
• The technologies and tools historically used to achieve that engagement
• Contemporary approaches to patient engagement
• Health Informatics: Data & Interoperability Standards (5 weeks 10-11 hours per week)
• Working familiarity with the major health care data standards
• Awareness of the web-based tools for accessing the data standards
• HL7 as the global health care interoperability standards organization
• HL7 interoperability standards history
• The HL7 interoperability standards that preceded FHIR
• The FHIR interoperability standard
• The SMART on FHIR EHR connected app platform
• Familiarity with web-based tools for learning and utilizing FHIR and SMART on FHIR
• Health Informatics: The Cutting Edge (5 weeks 10-11 hours per week)
• Working familiarity with the major health care data standards
• Awareness of the web-based tools for accessing the data standards
• HL7 as the global health care interoperability standards organization
• HL7 interoperability standards history
• The HL7 interoperability standards that preceded FHIR
• The FHIR interoperability standard
• The SMART on FHIR EHR connected app platform
• Familiarity with web based tools for learning and utilizing FHIR and SMART on FHIR
• Cost $267.30 (discounted from $297)

• Harvard University: Expert Level
• Statistics & R (4 weeks 2-4 hours per week)
• Random variables
• Distributions
• Inference: p-values and confidence intervals
• Exploratory Data Analysis
• Non-parametric statistics
• Introduction to Linear Models & Matrix Algebra (4 weeks 2-4 hours per week)
• Matrix algebra notation
• Matrix algebra operations
• Application of matrix algebra to data analysis
• Linear models
• Brief introduction to the QR decomposition
• Statistical Inference & Modeling for High-Throughput Experiments (4 weeks 2-4 hours per week)
• Organizing high throughput data
• Multiple comparison problem
• Family Wide Error Rates
• False Discovery Rate
• Error Rate Control procedures
• Bonferroni Correction
• q-values
• Statistical Modeling
• Hierarchical Models and the basics of Bayesian Statistics
• Exploratory Data Analysis for High throughput data
• High Dimensional Data Analysis (4 weeks 2-4 hours per week)
• Mathematical Distance
• Dimension Reduction
• Singular Value Decomposition and Principal Component Analysis
• Multiple Dimensional Scaling Plots
• Factor Analysis
• Dealing with Batch Effects
• Clustering
• Heatmaps
• Basic Machine Learning Concepts
• Cost: $626.40 (discounted from $696)

SUMMARY

• In our initial hour of research, we have scoped the availability of information in the public domain. We have also developed a format to present the information consistent with the instructions.
• Please note, only the course/podcast title has been hyperlinked to avoid confusion with multiple links to the same website. All of the information is available on the hyperlinked web page.
• We suggest the following research path.