What would make this 45 minutes worthwhile of your time?
What initiatives in your facility prompted you to attend this conference?
What tools are you hoping to return with?
Do you want to be entertained? Educated? Both?
A Measurement 2 308,537 3 66,807 4 6,210 5 233 6 3.4 Sigma Levels Parts per Million Defective
Practical Meaning 99% Good 99.99966% Good Postal System 20,000 Lost Articles of Mail / Hr Airline System Two Short/Long Landings / Day Medical Profession 200,000 Wrong Drug Prescriptions / Yr 7 Lost Articles / Hr 1 Short / Long every 5 Years 68 Wrong Drug Prescriptions
The Hidden Process Yield Shrinkage (waste) Redo Hidden Process NOT OK Yield At Measurement Operation Inputs Measure Final ‘Yield’ = OK Final Yield ignores the hidden process. Final yield performance is a function of post measurement. Process Variation Causes A " Hidden Process " Increased Cost – Lost Capacity >95% Customer Quality 65% is not 95% ... why not? Process 1 2 3 90% Yield 90% Yield 85% Yield = FPY/RTY 81 % 69 % 95% Yield 4 65 % >95% ‘Yield’ Final Measurement
Rolled Throughput in Healthcare Shrinkage (waste) Redo Hidden Process NOT OK Yield At Measurement X-Ray Patient presents for x-ray Results Final ‘Yield’ = OK Final Yield ignores the hidden process. Final yield performance is a function of post measurement. Process Variation Causes A " Hidden Process " Increased Cost – Lost Capacity >95% Customer Quality 65% is not 95% ... why not? Process 1 2 3 90% X-Ray 90% Correct Test 85% Results = FPY/RTY 81 % 69 % 95% Returned 4 65 % >95% ‘Yield’ Final Measurement
Variation Causes Defects Poor Support of Robust Product Functionality Process Capability No standard process for staff members InadequateStaffing Needs Variation in Medical Supplies No Metrics Way off Target Out of Spec. LSL USL
Time Performance Breakthroughs in Process Performance GOOD BAD 3 Sigma (CpK = 1) 6 Sigma (Cpk = 2)
Changing the Decision Making Processes Decision Making Growth Path Types of Problems You Will Normally Solve 1. Intuition, gut feel, I think ….. 2. We have Raw Data and look at it 3. We make graphs / charts of the data 4. We use advanced statistical tools to evaluate the data Simple Complex How Many Times Have Your Heard This ? “I Think The Problem Is…”
Overall Approach Practical Problem Statistical Problem Statistical Solution Practical Solution
The Funneling Effect Optimized Process 30+ Inputs 8 - 10 4 - 8 3 - 6 Found Critical X’s Controlling Critical X’s 10 - 15 All X’s 1st “Hit List” Screened List MEASURE ANALYZE IMPROVE CONTROL
AM PM MON TUE THU FRI WED TRAINING CURRENT STATE MAP CONCEPT & DETAIL DESIGN “ TAKE ACTION” IMPLEMENT IMPROVEMENTS REFINE Stabilize / Measure IMPROVEMENTS REFINE CHANGES PREPARE PRESENTATION PRESENTATION & CELEBRATION “ TAKE ACTION” DESIRED STATE GAP ANALYSIS
What is Lean? Lean is the identification and elimination of “Waste” with in a process Waste is define as anything that adds cost but Does not add value to the process.
TYPES OF WASTE PEOPLE TYPES OF WASTE Processing Motion Waiting Fixing Defects Making Too Much Moving Things Inventory
ACE Events Focus on Non Value-Added Activity To Reduce Lead Time
Reducing value-added (VA) activities usually results in only minor gains
Reducing Non Value-added (NVA, aka Waste) usually results in major lead time reductions without adding resources or capital
Typical company VA NVA Original lead time Traditional cost reductions VA NVA Minor improvement VA NVA Major improvement Don’ t make capital investments on improving VAs until the NVAs achieve equilibrium with the VAs ACE waste reduction
Reducing Length of Stay Team’s Actions Potential Time Savings Total Potential Savings of 1’18” 2 min Taking specimen to lab 30 min Wait to be tasked 30 min Wait to be seen by MD 2 min Triage paper to Reg/MD 5 min Pt waiting to be triaged 2 min RN/tech to take vital signs 2 min RN/tech start blue form 5 min Central Location for Stretchers and Wheelchairs
Only 27% Patients reported being “Very Satisfied”.
Where do unsatisfactory delays occur?
81 % stated before being taken to a treatment room.
56 % stated before being treated by a physician.
Facility had been concerned over customer satisfaction ratings with wait times in the ED. It was thought that people from the community were heading to area hospitals in Austin and San Antonio to receive care (with shorter waiting times)
Data Collection Cycle Time from Triage to Bed Using Six Sigma tools, we began collecting data on variables in the process. We found that the average waiting time for a patient to be placed in a bed was over 42 minutes!
Data Collection ALOS We also found that the Average Length of Stay for our ED patients was 2.5 hours.
Using Lean Tools to Drive Results Lean Tools, such as 5S, allowed us to organize the medical supply closets in the ED. Labels were created, excess inventory returned and par levels adjusted to provide a savings of over $32,000.00 .
Result 1: Triage to ER Bed Old Process New Process Average of 19 Minutes Average of 43 Minutes Over 50% reduction in overall cycle time!
Result 2: Average Length of Stay Old Process New Process Variation of 29 Minutes Variation of 87 Minutes Over 60% reduction in overall variation!
Result 3: Left Without Being Seen (LWBS) Reduction from 2% to 0.84%! 60% Reduction in LWBS