Healthcare — Lean six Sigma Green Belt
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Earn Your Green Belt Online from the University of Michigan
Learn how to effectively solve problems by integrating Lean and Six Sigma within the DMAIC approach.
This course will set you up with a structure to systematically frame problems, collect data productively, and implement sustainable solutions. After completing the program—including an improvement project at your organization—you'll earn a University of Michigan Lean Six Sigma Green Belt certification.
Using examples and case studies, this course focuses on applications primarily drawn from healthcare organizations, including office processes and healthcare operations. Project results include improved patient satisfaction scores, reduction of patient wait time, increased equipment utilization, fewer billing errors, and more.
Demonstrate your ability to conduct thorough problem-solving analysis toward achieving measurable results with a University of Michigan Lean Six Sigma Green Belt certification.
Understand variability through the graphical representation of data
Describe a process visually through process mapping techniques
Apply DMAIC problem solving process toward process improvement at the Green Belt level
Interpret test results and draw conclusions based on data
Develop recommendations and control plans to improve processes
Complete a process improvement project outside of class that demonstrates the application of the full DMAIC methodology
The following modules are required, and you will also receive access to optional supplemental material.
- Continuous Improvement Overview – Integrating Lean and Six Sigma, Classic Forms of Waste, Kaizen, Lean-Six Sigma in Healthcare
- DMAIC Problem Solving Process
- DEFINE: Requirements Flow Down, Linking Customers to Business Performance Metrics (VOC/VOB), Project Charters
- Process Maps: SIPOC, Swimlane, Process Mapping Diagram
- MEASURE: Exploring Data Patterns & Distributions (Run Charts, Histograms, Box Plots), Outliers (Supplement: Course Software Tutorial)
- Descriptive Statistics (Sampling, Mean, Median, Variation)
- Measuring Current State Capability (Yield, PPM Defective, DPMO)
- Rolled Yield Analysis (Types of Yield, Rolled Yield, Normalized Yield)
- Process Stability - Overview of Statistical Process Control (Variable and Attribute Control Charts)
- Measurement Systems Analysis (MSA)
- Value Stream Mapping – Part 1 (Current State Map, Value Add Timeline)
- Value Stream Mapping – Part 2 (Value Stream Productivity Analysis, Effective Process Time, Lean Levers: Pitch Interval, Volume/Mix Leveling, and Future State Maps)
- ANALYZE: Qualitative Analysis (Affinity, P-Diagram, Cause-Effect Diagram, 5 Whys)
- Stratification Analysis (Grouping Variables, Multiple Box Plots)
- Check Sheets and Pareto Analysis
- Two Group Hypothesis Tests (F-tests, t-tests, 2 proportion tests)
- Two-Variable Analysis: Scatter Plot/Linear Regression/Correlation
- Standardized Work Analysis (Time Observation, Capacity Planning Sheets, Detail Job Instructions, Leadership Standardized Work)
- IMPROVE: 5S Process, Standardized Work, Training, Error Proofing, Visual Aids, Process Monitoring
- Flow Improvements (Push vs. Pull Systems, Little's Law, Batch Size Reduction, Layout Improvement)
- Failure Mode and Effects (FMEA) Analysis
- CONTROL: Methods of Control
- Project Selection and Scoping
- Applying the Six Sigma Methodology and Course Summary
Time Commitment and Work Pace
Estimated: 60 self-paced hours
- 40 hours (approximately) for lecture recordings and exercises
- 10-30 hours for project work