1. LEAN LABORATORY PRACTICES
DR AYE AYE KHINE
CHEMICAL PATHOLOGY
NHLS TYGERBERG
STELLENBOSCH UNIBERSITY
Lab Management workshop 3-6 June 2019

2. Lean is a process Any change that improves efficiency and patient care
Remove waste
Standardize
Monitor the results (audit)
Improve efficiency
Harmonize
Any change that improves efficiency and patient care
(practice the same)
Value added services
no unnecessary steps, no repeats
get better result with same resources
Compatible and comparable

4. Exercise Value added lean practices
Give examples
Non value added practices (not lean)
Who is our customer? What does our customer need?

5. Waste Required waste or purposeful waste – give example QC/EQA
Calibration
Health and safety

6. Identifying waste in complete testing process
Pre pre-A
Pre-A A
Post A
Post post- A

7. Lean process leads to quality Improvement
Higher Quality
Improved efficiency
Reduced TAT
Resource Optimisation
Space utilization- streamline workflow

8. How? Workflow analysis Benchmark before you implement
Study your processes: Do a survey or audit for a day or week
Follow a rack of samples through your lab (choose urgent and routine racks)
Benchmark before you implement
Run a pilot for a week
Understand the impact of the change on the rest of the service
Do this before spending money on technology!

9. Lean process in workflow
Replaces processes with more reliable ones
Facilitates to make work easier to perform
Detects errors when it occurs
Eliminates possibility of error (Predicts errors)

10. From workflow analysis to Data
surveys, interviews and audits
Discussions with staff can focus on what impacts their day-to-day tasks
Charts show real issues
Impact of issues on service
Use data to
Influence decision makers
To get attention of staff involved

11. Spaghetti Maps

12. Post Lean

14. Lean Analysis Reveals Opportunities
The daily specimen collection run at the hospital began at 6 a.m. The majority of the volume occurred during this hour. This created a bottleneck (Figure 1) that affected all parts of the process.

15. Value Stream Map of Specimen Collection

16. Other Areas to be lean to improve workflow
LIMS
QCQA
INVENTORY HR
Safety and risk

17. Basic Lean Rules 1
Do not make changes until you understand the current situation and analyse data
Make changes based on data, not emotion!
Communicate 360*
Include staff in the plan- listen to your staff
Facilitate new ideas
Work with the suppliers
Pilot first and evaluate the change

18. A Lean Workplace... looks organised and clean
Samples flow without bottle necks
Results meet TAT
Fewer staff needed for the same output
Others moved to special bench or sent for workplace skill development
Very few rejections
No stock outs or expiries
Spend less than budgeted 
Revenue exceeds expenditure 
Staff happy: bonuses and job satisfaction
Management happy

19. Lean process and six sigma

20. Copy Right- only for training purposes and not permitted for publications

21. Introduction
Just like the “Lean”, Six Sigma is another tool for business process improvement.
It was introduced by engineer Bill Smith while working at Motorola in Jack Welch made it central to his business strategy at General Electric in Today, it is used in many industrial sectors
Sigma in Statistics it is used to measure the variability of a process or a result/product
is a dynamic process with the goal being six sigma status
TQM can be applied to SS as it makes quality management a more quantitative science

23. SS calculation needs TAE
Total allowable error of many analytes are well published (BV, CLIA, RCPA)
To asses the SS of a process the following equation is used:
Six Sigma = 𝑻𝒐𝒕𝒂𝒍 𝒂𝒍𝒍𝒐𝒘𝒂𝒃𝒍𝒆 𝒆𝒓𝒓𝒐𝒓 – 𝒃𝒊𝒂𝒔 𝑪𝑽
Which TAE to use?
CLIA too loose, BV too tight
Do we have any bias?

24. SS calculation- challenges
Example of Cholesterol
CLIA defined allowable error= 10%
NCEP specification for imprecision- 3% and for bias- 3% (TAE = 7,95 = 8%)
Lab’s bias is 2% and CV is 4%
SS = 10 –2 4 = 2 SS = ( 8– 2)/4 = 1,5
Bias 4% and CV 2%
SS = 10 –4 2 = 3
Lab’s bias is 2% and CV is 2%
SS = (10 –2)/2 = 4 SS = (8 –2)/2 = 3

25. CAP: Q-probe and Q-track to estimate SS
Laboratories subscribe to CAP can register for these programs
Participate in surveys
Analyzed in stats software
A summary data from across participating laboratories
The defects/errors observed were converted to DPMO for sigma assignment
CAP Q-Track another software that looks at longitudinal data collected from serial time points from participating laboratories
Areas of survey- qualitative questionnaire response converted to % (Likert scale)
Error rates (request form, test names, missing information, errors in logging, delays in logging, missing tubes, leaked tubes, wrong tubes, centrifuge errors, instrument breakdown, IQC errors, reagent errors, dilution errors, reporting errors, discordant critical results, pending tests % etc.)

29. Conclusion
SS can be seen as an important tool for assessing method or process performance, method validation, and in prioritizing resources for analytes that are at risk based on SS