what’s new in statistical quality control guidance: clsi’s ...preparation for final draft...
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What’s New in Statistical Quality Control Guidance: CLSI’s C24 Updates August 2, 2016
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• Statistical Quality Control for Quantitative Measurement Procedures: Principles and Definitions Curtis A. Parvin, PhD Nils B. Person, PhD, FACB Nikola Baumann, PhD Lili Duan, PhD A. Paul Durham Valerio M. Genta, MD Jeremie Gras, MD Greg Miller, PhD Megan E. Sawchuk, MT(ASCP)
CLSI C24 - 4th Edition
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Document Status
CLSI C24 - 4th Edition
Project Phase Activities Dates Proposed Draft Voting Delegates and Committee
members vote on Proposed Draft
Dec 1, 2015 – Feb 1, 2016
Comment Resolution Committee resolves comments and updates draft
February, 2016 – April, 2016
Preparation for Final Draft Voting
Editing, Final approval from chairholder
May, 2016 – August, 2016
Final Draft Vote Consensus Council Approves Publication
Aug 26 – Sep 15, 2016
Preparation for Publication
Editors prepare publication format
September, 2016
Publish September, 2016
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What’s New?
• Notable changes and additions – Alignment with principles introduced in CLSI EP23:
Laboratory Quality Control Based on Risk Management – Additional performance measures related to patient risk – Expanded guidance on setting target values and SDs – Greater focus on QC frequency and QC schedules – More emphasis on recovering from an out-of-control
condition
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
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Managing Patient Risk
Probability of Harm Negligible Minor Serious Critical Catastrophic
Frequent unacceptable unacceptable unacceptable unacceptable unacceptable
Probable acceptable unacceptable unacceptable unacceptable unacceptable
Occasional acceptable acceptable acceptable unacceptable unacceptable
Remote acceptable acceptable acceptable acceptable unacceptable
Improbable acceptable acceptable acceptable acceptable acceptable
Severity of Harm
CLSI EP23, Table 3. Risk Acceptability Matrix
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Laboratory QC
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Probability of detecting a testing process failure
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Probability (number) of incorrect patient results reported before the testing
process failure is detected
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Probability (number) of incorrect patient results identified and corrected before
misdiagnosis or hazardous action
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Focus on the measurement procedure
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Patient Risk
Sequence of Events Creating Risk of Harm for a Patient (Example)
Initiating cause
Testing process failure
Incorrect result
generated
Incorrect result
reported Misdiagnosis
Hazardous medical action
Patient harmed
P1 P2 P3 P4 P5 P6
Hazardous Situation
CLSI EP23, Figure 6
Focus on risk of harm to patients
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Patient Risk Based QC Performance Measures
• Number of erroneous patient results generated before detecting an out-of-control condition
• Depends on • Magnitude of out-of-control condition • QC Strategy
– # of QCs evaluated – QC rule(s) – Frequency of QC evaluations (QC schedule)
• Allowable total error for the analyte
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Patient Risk Based QC Performance Measures
• Number of erroneous “final” patient results reported before detecting an out-of-control condition
• Depends on • When patient results are reported • What recovery strategy the laboratory employs for
identifying and correcting erroneous patient results
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Main Chapters (Draft) 3. Purpose of Statistical Quality Control 4. Assessing Quality Control Performance 5. Planning a Statistical Quality Control Strategy 6. Recovering from an Out-of-Control Condition 7. Ongoing Assessment of Quality Control Programs 8. Worked Examples
CLSI C24 - 4th Edition
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Main Chapters (Draft) 3. Purpose of Statistical Quality Control 4. Assessing Quality Control Performance 5. Planning a Statistical Quality Control Strategy 6. Recovering from an Out-of-Control Condition 7. Ongoing Assessment of Quality Control Programs 8. Worked Examples
CLSI C24 - 4th Edition
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Main Chapters (Draft) 3. Purpose of Statistical Quality Control 4. Assessing Quality Control Performance 5. Planning a Statistical Quality Control Strategy 6. Recovering from an Out-of-Control Condition 7. Ongoing Assessment of Quality Control Programs 8. Worked Examples
CLSI C24 - 4th Edition
Greg Miller: “Planning a Statistical Quality Control Strategy”
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Main Chapters (Draft) 3. Purpose of Statistical Quality Control 4. Assessing Quality Control Performance 5. Planning a Statistical Quality Control Strategy 6. Recovering from an Out-of-Control Condition 7. Ongoing Assessment of Quality Control Programs 8. Worked Examples
CLSI C24 - 4th Edition
Niki Baumann: “Recovery From Out of Control Conditions”
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Our Speakers
• Nikola Baumann, PhD, DABCC – PhD from University of Wisconsin in Madison – Postdoc in Clinical Chemistry at Washington University – Asst. Prof. of Lab Medicine and Pathology, Mayo Clinic – Co-Director Central Clinical Laboratory, Director of
Central Processing, Director of the Clinical Chemistry Fellowship Program
– Active in AACC at both the regional and national level – An influential contributor to the topic of preparing for
and recovering from large-scale testing errors
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Our Speakers
• Greg Miller, PhD – PhD from University of Arizona in Tucson – Postdoc in Clinical Chemistry at Ohio State University – Professor of Pathology, Virginia Commonwealth – Director of Clinical Chemistry and Pathology
Information Systems – Past President of AACC (2012) and CLSI (2015) – Key contributor to committees and working groups for
several professional organizations involved with standardization, harmonization, quality control, and external quality assessment
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