Risk Management MasterClass

Extending Proven QC into Today’s

Statistical quality control transformed laboratory medicine by helping detect analytical error. Today’s laboratories face additional operational complexity, regulatory expectations, and patient-risk demands. This masterclass shows how to extend proven QC methodologies with real-time risk intelligence aligned with modern global standards.

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Medical laboratory scientists, technologists, supervisors, and managers looking to master risk management

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QA/QC coordinators, laboratory directors, and pathologists responsible for quality and patient safety

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Anyone seeking to implement value-based laboratory medicine and quantify ROI of quality improvements

RiskGATOR creates a win-win-win for everyone who cares about laboratory quality

Developed by clinical QC experts. Aligned with CLSI EP23A, ISO 15189, and modern risk-based QC principles.

Lower Healthcare Costs

Unnecessary QC tests, repeated analyses from false alarms, and lab errors that lead to wrong treatments all waste healthcare dollars that could be used to help more patients. Traditional QC estimates costs but doesn’t optimize them.

RiskGATOR quantifies avoidable healthcare costs caused by lab errors, evaluates the acceptability of error costs, and recommends improvements to reduce expenses. It guides labs to create QC processes verified to detect failure in a single run—eliminating waste.

Result: Healthcare systems save money on QC materials, staff time, and patient care—redirecting resources where they’re needed most.

Happier Lab Professionals

Lab professionals spend countless hours investigating false-positive QC flags, repeating tests, and dealing with processes that assume “QC processes are effective” without verification. This creates stress, burnout, and wasted time on problems that don’t actually threaten patient safety.

RiskGATOR reduces false positive QC flags and guides you to focus on real risks. It analyzes QC data to advise if an analytical process actually needs improvement in method accuracy or precision—not just arbitrary sigma values.

Result: Lab professionals reclaim hours each week, reduce stress, and focus on meaningful quality improvements.

Healthier Patients

Every lab error that reaches a patient can delay treatment, lead to incorrect diagnoses, or cause unnecessary procedures. Traditional QC methods remain essential for detecting analytical variation, but statistical indicators alone cannot always quantify patient impact in real time.

RiskGATOR quantifies the actual probability of harm—estimating how often an analytical process could produce one error every ‘x’ hours, days, weeks, months, or years. This means fewer missed errors, more accurate results, and better patient outcomes.

Result: Patients receive safer, more reliable lab results that lead to correct treatment decisions.

How do lab errors directly create patient harm and increase costs?

Which analytical shifts matter most to patient risk?

How can risk management strengthen existing QC strategies?

What do ISO 15189:2022, CLSI/CLIA, and EFLM recommend?

How do you define Total Allowable Error that protects patients?

Likelihood of errors vs Sigma metrics: what matters most?

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Change risk drivers for analytical quality and QC effectiveness. Watch real-time impact on patient risk and healthcare costs. Gain a deeper understanding of your data and what affects outcomes.

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Learn from global experts about regional challenges with accreditation, QC practice, and lab stress.
Case studies of reductions in patient errors and lab false positives
Reduce false positives and simplify lab processes

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30-day complimentary access to Interactive Risk Simulator to model how QC works and forecast patient risk

Full simulator access

Practice scenarios

Unlimited attempts

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Exclusive discounted pricing on RiskGATOR software

Early adopter pricing

Exclusive discounts

Limited-time offer

50% Discount for 3-hour Online Risk Management Course

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Free Downloads:

Best Practice Checklist for Quality Control & Risk Management

QC Problem-Solving Worksheet for Root Cause Analysis & Action Planning

Take the blindfold off sigma! Convert sigma to Medically Incorrect Results (MIRs) per year to see how:

1. variations in acceptable risk impacts Margin for Error (that drives QC process design) while sigma remains constant
2. the risk of errors varies with patient volumes while sigma remains constant
3. acceptability of risk varies with the TEa value selected,
4. Margin for Error and the risk of errors vary with analytical bias, while sigma remains constant
5. Margin for Error and the risk of errors vary with method SD
6. software can report the acceptability of risk instead of just statistics that you need to interpret
7. software can report risk metrics of the number, percent and probability of errors, instead of just statistics
8. Margin for Error (the number of SD to unacceptable risk) varies with acceptable risk and patient volume, while sigma remains constant
9. Risk Distribution Graphs that show current and failed performance adds meaning add clarity to QC data interpretation

Zoe Brooks

Building on decades of statistical QC science, Zoe developed the M.O.R.E. (Mathematically-OptimiZed Risk Evaluation) methodology to connect analytical variation with operational and patient-risk decision making.

Zoe is a globally recognized authority on laboratory risk management and quality control. Author of “Performance-Driven Quality Control” (AACC Press), multiple articles and scientific posters including the Award Winning “Impact of Seven Incremental Scenarios of QC Strategies. Her M.O.R.E. methodology powers AWEsome Numbers’ RiskGATOR software. (see more)