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  • 1. Six Sigma7 Management Sigma7 A Tool for Implementing ISO 15189:2003 Marlies Ledford-Kraemer, MBA, BS, MT(ASCP)SH Revised: mmvi 1
  • 2. Topics for Discussion Wh at IS O is Q 15 ual P ro 18 ity ces 9:2 ? Six ses 00 Si g 3S Lea ma tan nS 7M dar Im ix S ana d pac i gem t o gma ent fQ ual ity Ma na g em ent 2
  • 3. What is Quality? 3
  • 4. Definitions of Quality Cynical approach – An external business constraint – A “given” just like the air we breathe, therefore if everybody has quality, it does not give us a competitive advantage – The only level of quality that we need is the level that prevents us from being sued Progressive view – The extent to which health services … increase the likelihood of desired outcomes and are consistent with current professional knowledge.” (Institute of Medicine-1990) – “Predictable degree of uniformity and dependability, at low cost and suited to the market” • Dr W Edwards Deming (American statistician who revitalized the Japanese economy in the 1950s) – How closely a product or service meets the expectations set forth by the “customer” 4
  • 5. Scope of Quality Issues Three types of quality problems decrease likelihood of desired outcomes – Overuse • Providing services even though “risk” exceeds benefit – Giving antibiotics to a person with the common cold – PT/APTT as part of pre-operative screen – Underuse • Failure to provide effective care that would improve outcomes – Taking an inadequate patient history that leads to incomplete bleeding or thrombotic work-up – Misuse • Providing appropriate care without requisite skill thereby increasing risk of complications – Protein C / Protein S testing on patients receiving warfarin 5
  • 6. ISO 15189:2003 Medical Laboratories – Particular Requirements for Quality & Competence 6
  • 7. What is ISO? Name is taken from Greek ίσος meaning equal ISO is world's largest developer of standards Network of national institutes of standards representing 150 countries – Secretariat for USA is American National Standards Institute (ANSI) who in turn delegates responsibility to CLSI (Clinical Laboratory Standards Institute-formerly NCCLS) Preparation of standards is done through ISO Technical Committees (TC) – ISO/TC 212, Clinical Laboratory Testing and in vitro Diagnostic Test Systems, developed ISO 15189 • First proposed in 1999 and published in 2003 7
  • 8. Are ISO 15189 & 9000 Related? ISO 9000 is a generic management system standard – ISO 9001:2001 is concerned with "quality management“ (QM) • QM is what an organization does to enhance customer satisfaction by meeting both customer & applicable regulatory requirements while continually improving its performance in pursuit of these objectives – “Generic” implies its use for any product or service – “Management system” refers to what the organization does to manage its processes or activities – If an organization wishes to establish a quality management system, then salient features of such a system are found in relevant standards of ISO 9000 ISO 15189 is based upon ISO 9000 – ISO 15189 standard denotes particular requirements for quality and competence uniquely related to medical (clinical) laboratories 8
  • 9. ISO 15189 and CLSI Guidelines CLSI guidelines related to quality management parallel efforts of ISO 15189 – HS1-A2 A Quality Management System Model for Health Care; Approved Guideline-Second Edition – GP26-A3 Application of a Quality Management System Model for Laboratory Services; Approved Guideline-Third Edition – GP22-A2 Continuous Quality Improvement: Integrating Five Key Quality System Components; Approved Guideline-Second Edition Slides 12-18 show relationship between ISO 15189 elements and the 12 CLSI Quality System Essentials (QSE) 9
  • 10. Impact of IS0 15189 An institution’s management system that has been independently audited by a third party agency and confirmed to be in conformity with ISO 9001:2000 is certified by the third party agency (not ISO) Laboratories in the US are accredited through CAP, JCAHO, or COLA Potential adoption by US accrediting agencies and others worldwide would establish ISO 15189 as the standard for guiding and harmonizing the accreditation process of clinical laboratories – Standard has been endorsed by the International Laboratory Accreditation Cooperation as an acceptable alternative for accreditation of medical laboratories – From a regulatory perspective, laboratories would be accredited by agencies that use ISO 15189 as a guideline • Laboratories could still obtain ISO 9000 certification • Management & technical requirements of ISO 15189 would be complemented by the complete management system provided by ISO 9001:2000 10
  • 11. ISO 15189 Document 1 Scope 2 Normative references 3 Terms and definitions 4 Management requirements 5 Technical requirements Annex A (normative) – Correlation with ISO 9001:2000 and ISO/IEC 17025:1999 (General Requirements for the Competence of Calibration and Testing Laboratories) Annex B (informative) – Recommendations for protection of laboratory information system (LIS) Annex C (informative) – Ethics in laboratory medicine 11
  • 12. Management Requirements-1 4.1 Organization and management Laboratory should • Be legally identifiable • Meet needs of patient and clinical personnel • Meet ISO requirements • Identify personnel conflicts of interest • Be responsible for design, implementation, maintenance, and improvement of quality management system Aligns with CLSI QSE: Organization 12
  • 13. Management Requirements-2 4.2 Quality management system Laboratory should have • Policies & procedures that are documented, communicated, understood, and implemented • Internal quality control and participate in external quality assessment schemes • A quality policy statement • A quality policy manual • A program that regularly monitors & demonstrates proper calibration of instruments, reagents, and analytical systems Aligns with CLSI QSE: Organization 13
  • 14. Management Requirements-3 4.3 Document control Laboratories should • Control all documents that form a laboratory's quality documentation • Have procedures to ensure that quality management documents are reviewed by authorized personnel, identified as current, amended & so noted, and removed if obsolete • Maintain documents on any appropriate medium (that may or may not be paper) Aligns with CLSI QSE: Documents and Records 14
  • 15. Management Requirements-4 4.4 Review of contracts – Laboratories which enter into contracts with clients to whom they provide medical laboratory services should • Establish & maintain procedures for review of contracts • Ensure that laboratory has capability to meet contractual requirements • Document contract reviews, changes, or discussions • Include, in contract, work referred to other laboratories • Inform clients if deviations from the contract occur • Communicate contract amendments to all parties 4.6 External services and supplies – Laboratory should • Document procedures for selection & use of external services such as equipment & consumables • Verify that equipment & consumable supplies comply with standard specifications • Maintain an inventory control system • Evaluate suppliers of critical reagents & document evaluations and approvals Aligns with CLSI QSE: Purchasing and Inventory 15
  • 16. Management Requirements-5 4.15 Management review Laboratory management should • Review laboratory's quality management system to ensure continuing effectiveness & introduce necessary improvements • Record findings from reviews, forward those on to staff, and implement new actions in a timely fashion Aligns with CLSI QSE: Organization 16
  • 17. Management Requirements-6 Remaining elements are covered by CLIA and laboratory accrediting programs with deemed status such as CAP – 4.5 Examination by referral laboratories QSE: Purchasing and Inventory – 4.7 Advisory services QSE: Service and Satisfaction – 4.8 Resolution of complaints QSE: Occurrence – 4.9 Identification & control of nonconformities Management – 4.10 Corrective action – 4.11 Preventive action QSE: Assessments – 4.12 Continual improvement QSE: Process Improvement – 4.13 Quality and technical records QSE: Documents and Records – 4.14 Internal audits QSE: Assessments 17
  • 18. Technical Requirements Element CLSI QSE 5.1 Personnel Personnel 5.2 Accommodation & environmental conditions Facilities and Safety 5.3 Laboratory equipment Equipment 5.4 Pre-examination procedures (pre-analytical testing phase) 5.5 Examination procedures (analytical testing phase) 5.6 Assuring quality of examination procedures Process Control (quality control) 5.7 Post-examination procedures (post-analytical testing phase) 5.8 Reporting of results 18
  • 19. How to Use ISO 15189 ISO 15189 is a guideline (a “what to do”) that provides laboratories with specific managerial and technical requirements Implementation of ISO 15189 requires specific tools or roadmaps – CLSI standards and guidelines • GP22-A2, GP26-A3, and HS1-A2 – Lean enterprise (or Lean Thinking) • Eliminating muda (waste) – Six Sigma with myriad of process improvement tools • SIPOC (Suppliers, Inputs, Process, Outputs, Customer): Define • FMEA (Failure Modes and Effects Analysis): Measure • Flow diagrams: Analyze 19
  • 20. A Comparison Stages of Quality (CLSI HS1-A2:2004) Hierarchical Level Activities Performed Total management approach centered Six Sigma Management Tool Total Quality Management around customer satisfaction Activity to identify, measure, & control Quality Cost Management cost of quality ISO 9001 Systematic process-oriented approach ISO 15189 Quality Management System New to meet quality objectives Organized activities to provide Quality Assurance confidence that organization meets CLIA/CAP requirements for quality Operational process control Quality Control techniques to meet requirements for quality & regulatory compliance 20
  • 21. Processes 21
  • 22. How is Quality Measured? First step in quality consciousness is to recognize that a defect exists Assess processes – Measure variation using control charts – Determine process capability Assess outcomes – Should relate to a process that can be modified to improve an outcome • Example: Phlebotomy (pre-analytical process) – Improper technique leads to PF4 release, causing in vitro heparin neutralization that falsely shortens the APTT used to monitor heparin therapy (outcome) 22
  • 23. What is a Process? Transformation of inputs (X) into outputs (Y) – Example: Patient specimen is an “input” that is transformed by the laboratory into a Prothrombin Time (“output”) A process can be: Defined Examples Brushing one’s teeth, preparing breakfast Measured Admitting a patient, administering Analyzed chemotherapy, serving meals to patient Phlebotomy (pre-analytical phase of testing) Improved Performing a PT (analytical phase) Controlled Reporting PT test result (post-analytical) 23
  • 24. Defining & Documenting a Process Every process must have an owner – Owner is Courier who delivers specimen tubes to laboratory Objective of a process must be clearly stated – For the Courier, the objective is to deliver tubes to laboratory Each process must have a beginning & end point (boundary) in order to identify where one process ends and another begins – Process for Courier begins when phlebotomist gives him labeled specimen tubes and process ends when Courier gives (signs in) tubes to laboratory technologist Data collected from a process must be valid – Everyone involved in the process (courier delivery of specimens) must be in agreement as to how process data is to be collected so that data is useful and can lead to action 24
  • 25. Data Collected from a Process Attribute data – Classification of items into categories – Example • Proportion of requisition slips not “clocked-in” when received by laboratory • Number of typographical errors (post-analytical) inputted into LIS during January for all coagulation laboratory testing Variables data – Measurement of a characteristic – Example • Turn-around time for STAT coagulation tests (PT, APTT, Thrombin Time, and D-dimer) 25
  • 26. Attribute Data Attribute data aids in preventing defects and moving to a zero percent defective rate – Defect is an imperfection of some type that does not necessarily render the product or service as unusable whereas defective implies that the item is non-conforming and needs to be re-worked. Data does not provide specific information as to cause of the defect Control charts plot attribute data based on conforming or non-conforming to some specification 26
  • 27. Attribute Control Chart Requisition Slips "Clocked-in" 0.1 Special Cause 2 of 50 Variation Fraction Non-Conforming 0.08 defective 0.06 1 of 50 defective 0.04 0.02 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 zero defective Day (50 Requisitions per Day) 27
  • 28. Variables Data Variables data control 99.73% of all data falls charts allow for reduction of within +/- 3 Standard unit-to-unit variation by Deviation (sigma units or F) quantifying information of an average value (mean or µ) obtained from attribute data – Of those slips identified as Normal Gaussian Distribution “defective” (not “clocked in”), how many came between the hours of 0:00 to 8:00, 8:00-16:00, 16:00- 24:00? -3σ −2σ −1σ µ 1σ 2σ 3σ Brings process or product 68.26% closer and closer to 95.46% 99.73% intended specifications Carl Frederick Gauss 28
  • 29. Variables Data Control Chart R Bar Chart: TAT in Hours for Four Lab Tests Within Each Subgroup 26 24 Ave TAT = 5 hours (PT = 3 + APTT = 3 A ve ra g e T A T in h o u rs 22 20 + TT = 4 + DD = 10 hours) 18 16 14 12 10 8 6 4 2 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 All points due to Common Subgroups Cause Variation 29
  • 30. Process Variation Sources to which variation can be attributed: human, equipment, methods, materials, or environment Process variation is due to either common causes or special causes – Control charts are statistical tools that aid in distinguishing between these two types of variation Goal is to control and reduce variation, stabilize a process, and improve the process – Process improvement continuously modifies currently used methods so as to reduce the difference between “customer” needs and process performance 30
  • 31. Common Cause Variation Inherent in a process – Always present and affects all components of a process Laboratory perspective – Systematic error or bias • Incorrect value (120% v 100%) for reference plasma entered into coagulation analyzer for FVIII assay calibration curve – Relates to accuracy Management perspective – Managers are responsible for a system and hence are responsible for common causes of variation • Coagulation analyzer has not undergone quarterly preventive maintenance because Supervisor failed to renew contract 31
  • 32. Special Cause Variation Special causes come from outside the system Laboratory perspective – Random error • Reagent arm on coagulation analyzer does not dispense correct amount for one sample due to obstruction in probe – Relates to precision Management perspective – Variation should be identified and studied • May be shown to be detrimental and therefore must be removed – Samples accessioned incorrectly by a new technologist on first day of job • May be shown to be beneficial and therefore implemented – Western blots for VWF multimers are far superior when performed by one technologist versus other co-workers 32
  • 33. Process Stabilization & Improvement Control charts allow for process stabilization wherein a process exhibits only common cause variation and by that has a known capability Only a stabilized process can be continually improved upon – Stabilized attribute chart shows zero percent defective (Example: achieve conformance in that all requisition slips contain an ICD9 code) – Variables data chart may still show deviation from a “standard” and allow for continuous reduction in variation from this center • For example, conformance with noting ICD9 codes on all requisition slips does not imply that correct ICD9 codes were used 33
  • 34. Deming PDSA Cycle Model for process standardization A P (Act) (Plan) ing end v er- en t Ne ve m o S D pr Im (Study) (Do) Quality 34
  • 35. Commonly Used “Cycle" Is this your P P laboratory’s (Plan) (Plan) ing d en process er- Nev S improvement D D M ES model? (Do) (Do) Quality “p,p,do,do cycle” 35
  • 36. Six Sigma Management Relationship Between Voice of the Customer and Voice of the Process 36
  • 37. What is Six Sigma®? Process improvement initiative – A registered trademark of the Motorola Corporation who initiated this management strategy in the 1980s – Designed to set tolerance limits for manufacturing, service, and administrative processes such that fewer than 3.4 defects occur per million opportunities (<3.4 DPMO) “Relentless and rigorous pursuit of the reduction in variation of critical processes in order to achieve continuous and breakthrough improvements that impact the bottom line and/or top line of the organization and increase customer satisfaction” (Dr Edward Popovich) From a non-technical perspective it represents a corporate culture, philosophy, or business/management strategy 37
  • 38. Six Sigma® Focus Meet needs of the customer (external such as a patient or internal such as another department) Align Voice of the Customer with Voice of the Process – Customer wants high quality goods and services at a reasonable price – Reducing variability in processes improves performance • Process variation decreases quality and adds cost Top down management – Approach must be supported at all levels of an organization 38
  • 39. Six Sigma® ls About Processes! On Target & Less Variation Off Target Variation xx x x xx x x x x xx x x xxx xx x x x x x x Goal is to reduce spread in variation and to center process Goal is to reduce spread in variation and to center process In turn, customer receives a high quality product/service In turn, customer receives a high quality product/service with a high degree of certainty with a high degree of certainty 39
  • 40. Six Sigma® Technically Speaking Measures the degree to which any process deviates from its goal – A metric Applies statistical tools to identify, quantify, and eliminate/control variation – Typical value of an output is measured by the mean – Variability of an output (process) is measured by the standard deviation • As the standard deviation of a process decreases, the “sigma level” of a process increases – With Six Sigma7 performance, 6 process standard deviations fit between process mean and specification limits Allows for benchmarking 40
  • 41. “Goal Post View” of Process Capability LSL USL Lower Specification Limit Upper Specification Limit “Loss” or “Loss” or Defects Nominal Defects Nominal area is based upon perceived needs & wants of customers 41
  • 42. Process Distribution Voice of the Voice of the Voice of the Voice of the Customer Process Process Customer -6σ -5σ -4σ -3σ -2σ -1σ µ 1σ 2σ 3σ 4σ 5σ 6σ 3F 99.73% of processes are nominal 6F 99.9999998% of processes are nominal (fall within specification limits) 42
  • 43. What’s the Point? LSL USL Define process capability µ LSL USL Optimize process capability µ LSL USL Improve process capability and do so continually µ LSL* USL* 43
  • 44. Focusing on X (Not Y) Inputs (X) Process Outputs (Y) Feedback Loop Six Sigma tools focus on understanding and improving the upstream X’s versus monitoring the downstream Y variables By understanding how variation in X’s impact variation in Y’s, the need for inspection & rework is dramatically reduced/eliminated Y = ff (X1,, X2,, X3,…Xn) Y = (X1 X2 X3,…Xn) 44
  • 45. DMAIC Approach to Process Improvement Define Define Opportunity Opportunity Measure Measure Performance Performance Analyze Analyze Opportunity Opportunity Improve Improve Performance Performance Control Control Performance Performance Opportunity: chance for a defect to occur 45
  • 46. DMAIC Approach to Project Management Define Define goals & scope of project goals & scope of project X’s & Y’s and determine baseline Measure Measure X’s & Y’s and determine baseline process capability process capability relationships between X’s & Y’s and determine relationships between X’s & Y’s and determine Analyze Analyze which X’s are critical in order to detect & which X’s are critical in order to detect & eliminate noise (variation) eliminate noise (variation) process by manipulating key X’s to process by manipulating key X’s to Improve Improve achieve desired changes in Y variable achieve desired changes in Y variable of interest of interest new & improved process new & improved process Control Control in order to sustain the in order to sustain the gain gain 46
  • 47. What is Measured? Calculate Defects per Million Opportunities (DPMO) Metrics Total # defects x 1,000,000 DPMO = (# of Opportunities for Error) x (# of units) Sigma calculators are available on-line to determine sigma levels Unit: any item that is produced or service rendered Defect: an imperfection of some type that fails to meet a customer’s requirement Opportunity: chance for a defect to occur 47
  • 48. Six Sigma® Allows for 1.5σ shift 1.5σ offset was described by Harry & Schroeder as the “fudge factor” that accommodates unexpected errors or movement over time and allows for a robustness in the product that is impervious to unavoidable sources of variation Short-term capability of a process is 6σ but long-term capability is only 4.5σ – Voice of the Process should be no more than half of tolerance allowed for Voice of the Customer Advantage is that small shifts in the process mean are tolerated without increasing the defect rate significantly (6σ = 3.4 DPMO v 4.5σ = 6.8 DPMO) 48
  • 49. Short v Long Term Process Capability Three Sigma Process Six Sigma Process Centered Centered LSL USL LSL USL 1.5 Sigma Shift 1.5 Sigma Shift LSL USL LSL USL 49
  • 50. What Do the Numbers Mean? DPMO DPMO Sigma AUC Tail Centered with Shift 1.0 317,400 691,462 68.26% 31.74% 2.0 45,600 308,537 95.44% 4.56% 2.5 12,419 158,686 3.0 2,700 66,807 99.73% 0.27% 3.5 465 22,750 4.0 63 6,210 99.379% 0.621% 4.5 6.8 1,350 5.0 0.57 233 99.9767% 0.0233% 5.5 0.038 32 6.0 0.002 3.4 99.99966% 0.00034% AUC: area under the curve DPMO: defects per million opportunities 50
  • 51. A Product Involves Many Processes A product or service is composed of many processes Example: a product such as a Prothrombin Time may require 20 processes (phlebotomy, transport of specimen, specimen processing, test performance, reporting of results, and so forth) – Industry standard is ~4σ or 6,210 DPMO • (1.0-0.00621)20 x 100 = 88.286% likelihood of delivering a defect free product (correct PT) – If industry standard were 6σ or 3.4 DPMO • (1.0-0.0000034)20 x 100 = 99.99932% likelihood of delivering a defect free product 51
  • 52. Lean Six Sigma 52
  • 53. Lean Philosophy Toyota manufacturing system (1988) – Taiichi Ohno, a Toyota executive, identified seven types of muda (waste) that absorb resources but create no value • Defects (mistakes that require rework) • Overproduction (producing items that no one wants) • Inventories (goods awaiting further processing or consumption) • Unnecessary processing (performing steps that are not needed) • Unnecessary movement of people • Unnecessary transport of goods from one place to another without any purpose • Waiting by employees in a downstream activity because an upstream activity has not delivered on time Womack & James (1996) added an eighth muda: design of goods or services that do not meet users’ needs 53
  • 54. Lean Thinking Effectiveness of any process is reflected by a product’s value – Value is defined by the CUSTOMER and not the producer Types of process steps – Value-added • Steps directly contributing to a product characteristic that is desired and valued by the customer • Activities should be retained and are opportunities for improvement thereby enhancing value and reducing costs – Non-value-added • Work, which according to the customer, does not add value to the product • Considered as WASTE and must be minimized/eliminated – Business-value-added • Includes administrative, regulator, and business functions • Also considered as non-value-added steps by the customer • Processes can not be eliminated but can be improved 54
  • 55. Combining Lean and Six Sigma7 Lean Six Sigma improves processes and allows for quality improvement to occur at a quicker pace – Lean approaches processes from a “waste management” point of view hence, steps that create waste are initially eliminated – Six Sigma7 tools can subsequently be applied to only those steps/processes that provide value to the customer • Time is not wasted by applying tools to processes that are not value- added (with the exception of business-value-added process steps) Lead time and process cycle efficiency are key components of Lean Six Sigma – Lead time: how long it takes to deliver a product or service once it has been requested by a customer – Process cycle efficiency: proportion of time spent on value-added work compared to total process time 55
  • 56. What is the Impact of Quality Management? 56
  • 57. Six Sigma® in Practice 99% Good (3.8 F) 99.99966% Good (6 F) 16,000 lost articles of mail per hour 5.4 articles lost per hour 22,000 checks deducted from the 7.5 checks deducted from the wrong bank account each hour wrong bank account each hour 500 incorrect surgical operations per 1.7 incorrect operations per week week 2 unsafe plane landings per day at 1 unsafe plane landing every O’Hare International Airport in Chicago four years 50 newborn babies dropped at birth 1 newborn baby dropped at by doctors each day birth by doctors every 2 months Eckes G. Six Sigma Revolution. New York: John Wiley & Sons, Inc, 2003, p 37. 57
  • 58. Industry Examples of Six Sigma® Domestic airline fatalities – 0.43 DPMO (better than 6σ) Airline baggage handling & restaurant billing – 4,000 DPMO or 4.15σ Firestone production of tires for Ford Explorer – ~5σ (remember the public outcry?) 1% hospitalized patients injured through negligence – ~10,000 DPMO or 3.8σ Inappropriate prescribing of antibiotics by doctors – 210,000 DPMO or 2.3σ 58
  • 59. Laboratory Capabilities in 2000 Quality Indicator DPMO Sigma Pre-analytical Missing information on Pap requisitions 100,259 2.8 Correction of errors on ordered tests 3,123 4.3 Patients without ID bands 5,625 4.1 Specimen redraws 19,053 3.6 Therapeutic drug monitoring timing 207,140 2.4 Analytical Laboratory testing error 726 4.7 Laboratory proficiency testing 9,000 3.9 Post-analytical Laboratory reporting errors 533 4.8 Nevalainen D, et al. Arch Pathol Lab Med 2000:124;516-9 59
  • 60. Health Care v Other Businesses Most healthcare services show process capabilities between 2.7σ – 4.7σ – Notable exception is deaths caused by anesthesia during surgery (5.4 DPMO or ~5.9σ) If other industries deteriorated to our antibiotic practices at 2.3σ – 9 million errors per day would occur in the credit card industry – 36 million checks per day would be deposited in the wrong accounts – Deaths from airline crashes would increase by nearly 500,000 fold 60
  • 61. Benefits of Six Sigma® Improves process flows Reduces total defects Improves efficiency Improves effectiveness (checklists to prevent missing critical steps) Results in higher levels of customer & employee satisfaction Increases value of product/service Decreases costs & increases revenue Decreases costs & increases revenue 61
  • 62. Improving processes is just not another thing to do but makes us do things right Using ISO 15189 as a guide, laboratorians should look beyond quality control and quality assurance of individual procedures by extending their QC/QA culture to process improvement throughout the workflow – Use Six Sigma7 management as a tool to improve quality Be proactive and embrace quality initiatives in order to raise laboratory outcomes to those that we as consumers demand of other industries – We have the capacity to deliver the finest health care but must do so with regularity As providers of healthcare services we can not continue to defend our level of mediocrity 62
  • 63. References Castellani WJ. ISO 15189-taking laboratory accreditation to the next level. CLMA/ASCP LabThink 2005. Chassin MR. Is health care ready for Six Sigma quality? The Milbank Quarterly 1998;76(4):565-91. Becher EC, Chassin MR. Improving quality, minimizing error: making it happen. Health Affairs 2001;20(3):63-81. Clinical and Laboratory Standards Institute (CLSI). Application of a quality management system model for laboratory services; Approved Guideline GP26-A3, 2004. CLSI. A quality management system model for health care; Approved Guideline HS1-A2, 2004. CLSI. Continuous quality improvement: integrating five key quality system components; Approved Guideline GP22-A2, 2004. Gitlow HS, Oppenheim A, Oppenheim R. Quality Management: Tools and Methods for Improvement, 2nd ed. Boston: Irwin McGraw-Hill, 1995. Gitlow HS, Levine DM. Six Sigma for Green Belts and Champions. Upper Saddle River: Pearson Prentice Hall, 2005. International Organization for Standardization (ISO). Medical laboratories – Particular requirements for quality and competence; International Standard 15189, 2003. ISO. Medical laboratories - Guidance on laboratory implementation of ISO 15189:2003; Technical Report 22869, 2005. Jacobson JM, Johnson ME. Lean and Six Sigma: not for amateurs. Lab Medicine 2006;37(2):78-83 (Part 1) and Lab Medicine 2006;37(3):140-5 (Part 2). Ledford-Kraemer MR. The Clotting Times. 2005;5(1):6-9. http://www.clot- Ledford-Kraemer MR. The Clotting Times. 2005;5(2):5-7. http://www.clot- Nevalainen D, et al. Evaluating laboratory performance on quality indicators with the Six Sigma scale. Arch Pathol Lab Med 2000;124:516-19. South SF. Achieving breakthrough improvements with the application of Lean Six Sigma tools and principles within process excellence. Lab Medicine 2005;36(4):240-2. WomackJP, Jones DT. Lean Thinking, 2nd ed. New York: Free Press, 2003. 63
  • 64. Internet Resources (excellent web site for Quality Control, Quality Assurance, and Six Sigma) (Six Sigma tutorial) (iSixSigma) – (iSixSigma Healthcare) (General Electric) (Motorola University) (Six 64