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SIX SIGMA METRICS
J AISHWARYA
M.Sc. 3RD YEAR MEDICAL BIOCHEMISTRY
History
■ “Six Sigma” coined- Motorola engineer named Bill Smith.
(Incidentally, “Six Sigma” is a federally registered trademark of
Motorola).
■ In the early and mid-1980s with Chairman Bob Galvin at the helm,
Motorola engineers decided that the traditional quality levels —
measuring defects in thousands of opportunities – didn’t provide
enough granularity. Instead, they wanted to measure the defects per
million opportunities.
■ documented more than $16 Billion in savings as a result of our Six
Sigma efforts
Measures of Central Tendency
■ Central tendency is the tendency of data to be around this
mean.
■ Mean is the arithmetic average of a process data set.
■ Standard Deviation (also known as Sigma or σ) determines
the spread around this mean/central tendency
Standard deviations
■ The more number of standard deviations between process average
and acceptable process limits fits, the less likely that the process
performs beyond the acceptable process limits, and it causes a
defect.
■ This is the reason why a 6σ (Six Sigma) process performs better
than 1σ, 2σ, 3σ, 4σ, 5σ processes.
•
Six Sigma stands for 6 standard deviations (6σ)
between average and acceptable limits
• LSL and USL stand for “Lower Specification Limit” and
“Upper Specification Limit” respectively.
• Specification Limits are derived from the customer
they specify the minimum and maximum acceptable
Example
■ For instance in a car manufacturing system
the desired average length (Mean length)
of car door can be 1.37185 meter. In order
to smoothly assemble the door into the car,
LSL can be 1.37179 meter, and USL can
be 1.37191 meter. To reach a 6σ quality
level in such a process, the standard
deviation of car door length must be at
most 0.00001 meter around the mean
length
SIX SIGMA
■ “Six Sigma is a quality program that, when all is said and done,
improves your customer’s experience, lowers your costs, and builds
better leaders”.
■ Six Sigma at many organizations simply means - measure of quality
that strives for near perfection
■ Generic or customized name for the organization like “Operational
Excellence,” “Zero Defects,” or “Customer Perfection.”
■ Six Sigma is a disciplined, data-driven approach and methodology for
eliminating defects (driving toward six standard deviations between the
mean and the nearest specification limit) in any process – from
manufacturing to transactional and from product to service.
Definition – statistical (industrial aspect)
■ The statistical representation of Six Sigma describes quantitatively
how a process is performing.
■ To achieve Six Sigma — statistically — a process must not produce
more than 3.4 defects per million opportunities.
■ A Six Sigma defect is defined as anything outside of customer
specifications.
OBJECTIVES OF SIX SIGMA
■ to reduce process output variation so that on a long
term basis, this will result in no more than (or 3.4 defects
per million opportunities – DPMO).
■ Sigma is also the capability of the process to produce
defect free work. Higher the capability, lower the
defects
■ Better sigma metrics compared to 1σ, 2 σ, 3 σ, 4 σ.etc
Processes in various Sigma Levels
Sigma Level vs DPMO Defects per Million Opportunities
Can we have any process which has 6σ
level of performance?
■
The answer is yes
■ Pharmaceutical Companies, Airline Manufacturing
Organizations, Automobile Manufacturers, among others are
bound to work at a sigma level which is either 6σ or more
than that. If they are not able to perform at this efficiency,
the organization cannot exist. Think about it, you are in the
air, 5000 feet above the ground, flying in a Boeing 777
Aircraft and suddenly a nut-bolt in the wing of the plane
loosens (probably due to manufacturing defect) making it
difficult for the pilot to steer the flight! This is the only
reason why defects are not welcome and organizations try to
achieve higher Sigma levels.
The Potential for Six Sigma in Lab Quality
Management
■ Six Sigma methodology to use - help laboratories in
establishing better quality management systems.
Specifically, Six Sigma can help clinical lab managers better
evaluate the analytical quality of lab results as well as
the equipment and products used to produce them.
■ Employing the Six Sigma metric – 3.4 errors per million
opportunities – can help labs better determine if “bias,
imprecision, or both” have contributed to lower
Sigma metrics for equipment currently used in a lab
Six Sigma can be used to help answer one of the
most commonly asked questions in laboratory
quality control. How often should I run QC?
■ Six Sigma model allows laboratories to evaluate the effectiveness of their
current QC processes.
■ common use is to help implement a risk-based approach to QC, where an
optimum QC frequency and multi-rule procedure can be based on the sigma
score of the test in question.
■ The performance of tests or methods with a high sigma score of six or more
may be evaluated with one QC run (of each level) and a single 1:3s warning
rule. On the other hand, tests or methods with a lower sigma score should be
evaluated more frequently with multiple levels of QC and a multi-rule strategy
designed to increase identification of errors and reduce false rejections.
Table shows how multi-rules and QC
frequency can be applied according to
Sigma Metrics:
Underutilized Methodology – In Clinical Laboratory
■ Six Sigma metric that tests variance and errors in a process
■ Mostly underutilized due to lack of knowledge or lack of information
or both
Six Sigma Has Made Its Way Into Lab Work Before
■ Countries like Utah, Oklahoma and Illinois – adapted this metric
system for better process efficiency.
Application of SixSigma in Clinical Lab
• Reduce errors in the pre-analytical, analytical, and
post-analytical phases of testing
• Improve safety
• Reduce turnaround times (TATs)
• Improve accuracy of analytical tests
• Optimize quality control (QC) rule
How to implement Six Sigma
■ Critical to involve all levels of staff in the process to produce better
results
■ Lean six sigma methodologies improve clinical laboratory efficiency
and reduce turnaround times.
Keys to Six Sigma success in the lab include:
• A leader who is knowledgeable in Six Sigma concepts
• Proper communication with lab staff throughout the process
• Proper training for lab staff
• Change management strategies
• A shift in workplace culture
The five stages of implementing Six Sigma
■ Define who the customer is and what their needs and
expectations are. In the case of clinical labs,
patients or the health care professionals who rely on
■ Measure the process you’re looking to improve. First
you need to create a plan to collect data, then collect
figure out what errors/defects are occurring and the
measure them against.
■ Analyze your collected data to identify the key causes of
errors in the lab and areas that could be improved.
■ Improve the lab process you’re focusing on through
solutions/plans your team has come up with. This could
automating a process to reduce human errors and prevent
injuries.
■ Control the new and improved process to ensure the changes
stick. Make sure staff aren’t going back to the old methods of
things. Develop, document, and implement a monitoring plan
the new process is maintained. This might mean ongoing
staff to refresh them in the new methods.
CALCULATING SIX SIGMA -
IMPLEMENTING IN CLINICAL
LAB
Measure the Quality on the Sigma
Scale
■ The first one: counting the errors or defects.
■ This methodology is useful in evaluation of all errors in
total
testing process, except analytical phase.
Sigma Calculator
■ The second: using the following equation.
■ Sigma = (TEa – bias) / CV
Where:
■ TEa: total error allowable (quality goal).
■ bias and CV (coefficient of variation) are the indicator of
systematic and random errors respectively.
Measure the Quality on the Sigma
Scale
SIGNIFICANCE
CASE STUDIES
1- North Shore University Hospital, New
York
■ Define: Total Turnaround Time (TAT) taking too long
■ Measure: Target TAT set to 120 min. and upper
specification limit set to 150min., defect defined as a TAT
over 150 min., collected information on 195 patients
■ Analyze: Use data to identify underlying problem
- the underling problem was employees lacked
proficiency with the hospitals bed tracking system
(BTS)
■ Improve: Improved communication within the staff by:
documenting communication and Retraining employees
on BTS.
■ Control: Monitoring the process (TAT continued to be
monitored on a monthly basis)
Results
■ – Went from a slightly over one sigma process to a
3.1 sigma process
■ – The average TAT went from 226 minutes to 69
minutes
Conclusion
■ Six Sigma is not only a means to quantify
analytical performance, but is also a management
method that can improve the organization in an
orderly way,
■ with the target being to reach optimal quality
characterized by a level of 3.4 DPMO
Conclusion
■ The errors that we are interest are primarily analytical
errors, which represent only the tip of the iceberg.
However, the reality is quite different.
■ When we see the whole iceberg and control it all, then it
will be possible to reach Six Sigma level and even
higher quality in clinical laboratories.
If we don’t measure, we
don’t know, and if we don’t
know , we can’t manage
Six sigma metrics

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Six sigma metrics

  • 1. SIX SIGMA METRICS J AISHWARYA M.Sc. 3RD YEAR MEDICAL BIOCHEMISTRY
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  • 3. History ■ “Six Sigma” coined- Motorola engineer named Bill Smith. (Incidentally, “Six Sigma” is a federally registered trademark of Motorola). ■ In the early and mid-1980s with Chairman Bob Galvin at the helm, Motorola engineers decided that the traditional quality levels — measuring defects in thousands of opportunities – didn’t provide enough granularity. Instead, they wanted to measure the defects per million opportunities. ■ documented more than $16 Billion in savings as a result of our Six Sigma efforts
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  • 5. Measures of Central Tendency ■ Central tendency is the tendency of data to be around this mean. ■ Mean is the arithmetic average of a process data set. ■ Standard Deviation (also known as Sigma or σ) determines the spread around this mean/central tendency
  • 6. Standard deviations ■ The more number of standard deviations between process average and acceptable process limits fits, the less likely that the process performs beyond the acceptable process limits, and it causes a defect. ■ This is the reason why a 6σ (Six Sigma) process performs better than 1σ, 2σ, 3σ, 4σ, 5σ processes.
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  • 8. • Six Sigma stands for 6 standard deviations (6σ) between average and acceptable limits • LSL and USL stand for “Lower Specification Limit” and “Upper Specification Limit” respectively. • Specification Limits are derived from the customer they specify the minimum and maximum acceptable
  • 9. Example ■ For instance in a car manufacturing system the desired average length (Mean length) of car door can be 1.37185 meter. In order to smoothly assemble the door into the car, LSL can be 1.37179 meter, and USL can be 1.37191 meter. To reach a 6σ quality level in such a process, the standard deviation of car door length must be at most 0.00001 meter around the mean length
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  • 11. SIX SIGMA ■ “Six Sigma is a quality program that, when all is said and done, improves your customer’s experience, lowers your costs, and builds better leaders”. ■ Six Sigma at many organizations simply means - measure of quality that strives for near perfection ■ Generic or customized name for the organization like “Operational Excellence,” “Zero Defects,” or “Customer Perfection.” ■ Six Sigma is a disciplined, data-driven approach and methodology for eliminating defects (driving toward six standard deviations between the mean and the nearest specification limit) in any process – from manufacturing to transactional and from product to service.
  • 12. Definition – statistical (industrial aspect) ■ The statistical representation of Six Sigma describes quantitatively how a process is performing. ■ To achieve Six Sigma — statistically — a process must not produce more than 3.4 defects per million opportunities. ■ A Six Sigma defect is defined as anything outside of customer specifications.
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  • 14. OBJECTIVES OF SIX SIGMA ■ to reduce process output variation so that on a long term basis, this will result in no more than (or 3.4 defects per million opportunities – DPMO). ■ Sigma is also the capability of the process to produce defect free work. Higher the capability, lower the defects ■ Better sigma metrics compared to 1σ, 2 σ, 3 σ, 4 σ.etc
  • 15. Processes in various Sigma Levels
  • 16. Sigma Level vs DPMO Defects per Million Opportunities
  • 17. Can we have any process which has 6σ level of performance? ■ The answer is yes ■ Pharmaceutical Companies, Airline Manufacturing Organizations, Automobile Manufacturers, among others are bound to work at a sigma level which is either 6σ or more than that. If they are not able to perform at this efficiency, the organization cannot exist. Think about it, you are in the air, 5000 feet above the ground, flying in a Boeing 777 Aircraft and suddenly a nut-bolt in the wing of the plane loosens (probably due to manufacturing defect) making it difficult for the pilot to steer the flight! This is the only reason why defects are not welcome and organizations try to achieve higher Sigma levels.
  • 18. The Potential for Six Sigma in Lab Quality Management
  • 19. ■ Six Sigma methodology to use - help laboratories in establishing better quality management systems. Specifically, Six Sigma can help clinical lab managers better evaluate the analytical quality of lab results as well as the equipment and products used to produce them. ■ Employing the Six Sigma metric – 3.4 errors per million opportunities – can help labs better determine if “bias, imprecision, or both” have contributed to lower Sigma metrics for equipment currently used in a lab
  • 20. Six Sigma can be used to help answer one of the most commonly asked questions in laboratory quality control. How often should I run QC? ■ Six Sigma model allows laboratories to evaluate the effectiveness of their current QC processes. ■ common use is to help implement a risk-based approach to QC, where an optimum QC frequency and multi-rule procedure can be based on the sigma score of the test in question. ■ The performance of tests or methods with a high sigma score of six or more may be evaluated with one QC run (of each level) and a single 1:3s warning rule. On the other hand, tests or methods with a lower sigma score should be evaluated more frequently with multiple levels of QC and a multi-rule strategy designed to increase identification of errors and reduce false rejections.
  • 21. Table shows how multi-rules and QC frequency can be applied according to Sigma Metrics:
  • 22. Underutilized Methodology – In Clinical Laboratory ■ Six Sigma metric that tests variance and errors in a process ■ Mostly underutilized due to lack of knowledge or lack of information or both Six Sigma Has Made Its Way Into Lab Work Before ■ Countries like Utah, Oklahoma and Illinois – adapted this metric system for better process efficiency.
  • 23. Application of SixSigma in Clinical Lab • Reduce errors in the pre-analytical, analytical, and post-analytical phases of testing • Improve safety • Reduce turnaround times (TATs) • Improve accuracy of analytical tests • Optimize quality control (QC) rule
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  • 25. How to implement Six Sigma ■ Critical to involve all levels of staff in the process to produce better results ■ Lean six sigma methodologies improve clinical laboratory efficiency and reduce turnaround times. Keys to Six Sigma success in the lab include: • A leader who is knowledgeable in Six Sigma concepts • Proper communication with lab staff throughout the process • Proper training for lab staff • Change management strategies • A shift in workplace culture
  • 26. The five stages of implementing Six Sigma
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  • 28. ■ Define who the customer is and what their needs and expectations are. In the case of clinical labs, patients or the health care professionals who rely on ■ Measure the process you’re looking to improve. First you need to create a plan to collect data, then collect figure out what errors/defects are occurring and the measure them against.
  • 29. ■ Analyze your collected data to identify the key causes of errors in the lab and areas that could be improved. ■ Improve the lab process you’re focusing on through solutions/plans your team has come up with. This could automating a process to reduce human errors and prevent injuries. ■ Control the new and improved process to ensure the changes stick. Make sure staff aren’t going back to the old methods of things. Develop, document, and implement a monitoring plan the new process is maintained. This might mean ongoing staff to refresh them in the new methods.
  • 30. CALCULATING SIX SIGMA - IMPLEMENTING IN CLINICAL LAB
  • 31. Measure the Quality on the Sigma Scale ■ The first one: counting the errors or defects. ■ This methodology is useful in evaluation of all errors in total testing process, except analytical phase. Sigma Calculator
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  • 33. ■ The second: using the following equation. ■ Sigma = (TEa – bias) / CV Where: ■ TEa: total error allowable (quality goal). ■ bias and CV (coefficient of variation) are the indicator of systematic and random errors respectively. Measure the Quality on the Sigma Scale
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  • 38. 1- North Shore University Hospital, New York ■ Define: Total Turnaround Time (TAT) taking too long ■ Measure: Target TAT set to 120 min. and upper specification limit set to 150min., defect defined as a TAT over 150 min., collected information on 195 patients ■ Analyze: Use data to identify underlying problem - the underling problem was employees lacked proficiency with the hospitals bed tracking system (BTS)
  • 39. ■ Improve: Improved communication within the staff by: documenting communication and Retraining employees on BTS. ■ Control: Monitoring the process (TAT continued to be monitored on a monthly basis) Results ■ – Went from a slightly over one sigma process to a 3.1 sigma process ■ – The average TAT went from 226 minutes to 69 minutes
  • 40. Conclusion ■ Six Sigma is not only a means to quantify analytical performance, but is also a management method that can improve the organization in an orderly way, ■ with the target being to reach optimal quality characterized by a level of 3.4 DPMO
  • 41. Conclusion ■ The errors that we are interest are primarily analytical errors, which represent only the tip of the iceberg. However, the reality is quite different. ■ When we see the whole iceberg and control it all, then it will be possible to reach Six Sigma level and even higher quality in clinical laboratories.
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  • 43. If we don’t measure, we don’t know, and if we don’t know , we can’t manage