MLT 1305 Laboratory Automation part 2

Page 1: Introduction

• Title: Laboratory Automation in Clinical Chemistry Part 2

• Instructor: Vern Hurst

• Term: Winter 2024

Page 2: Objectives

• Objective 1: List Advantages of Automated Systems

  • Understand concept of automation in laboratory processes.

  • Identify advantages:

    • Increased efficiency.

    • Reduced human error.

    • Faster turnaround time.

  • Recognize impact on workflow/resource allocation.

• Objective 2: Necessity of Automation/Identify Drawbacks

  • Discuss reasons for adopting automation:

    • Workload management.

    • Improved accuracy and consistency.

  • Explore challenges:

    • Initial costs.

    • Maintenance issues.

    • Complexity of systems.

  • Analyze trade-offs of manual vs. automated processes.

• Objective 3: Automated Analyzer Functions

  • Explain roles:

    • Mixing, incubating, reagent transfer.

  • Illustrate contributions to accurate test results and real-world examples.

• Objective 4: Laboratory Process Phases & Autoverification

  • Explore how autoverification ensures result accuracy and flags discrepancies.

Page 3: Sequential Analyzers

• Work Flow:

  • Continuous flow processing of samples; efficient throughput.

• Integration of Steps:

  • Pre-Analytical: Aspiration, dilution, mixing.

  • Analytical: Sequential reactions throughout connected tubes.

  • Post-Analytical: Recording and reporting results.

• Methodology:

  • Employ flow techniques with interconnected modules.

Page 4: Advantages and Limitations of Sequential Analyzers

• Advantages:

  • Efficiency: High sample throughput due to continuous flow.

  • Consistency: Uniform conditions minimizing variability.

  • Multiple Parameters: Measurement of multiple analytes in a single run.

• Limitations:

  • Complexity: More intricate setup and maintenance.

  • Sample Volume: Larger sample volume required compared to discrete analysis.

Page 5: Discrete Analyzers

• Description: Automated chemical analyzers with discrete sample handling.

• Workflow:

  • Mimics manual lab processes; involves sample dispensing, reagent mixing, incubation, and measurement.

• Components:

  • Photometer: Specific filters for photometric analysis.

  • Dispensing Probes: Dispensing samples and reagents.

  • Incubator: Controls reaction temperature.

  • Mixer: Ensures thorough mixing of samples and reagents.

Page 6: Isolated Reaction Cells

• Each reaction cell is isolated with stabilized temperature, allowing controlled conditions for analysis.

• After mixing reagents and samples, photometric detection occurs based on light wavelengths, integrated with software for data interpretation.

Page 7: Benefits of Discrete Analyzers

• Benefits:

  • Flexibility: Direct read measurements enhance method development.

  • Automation: Reduces labor-intensive tasks in wet chemical analysis.

  • Cost-Effective: Lowers costs, waste, and hands-on time.

Page 8: Importance of Automation in Clinical Chemistry

• Efficiency and Speed: Streamlines repetitive tasks, enabling quick processing of large volumes of samples.

• Accuracy and Precision: Minimizes human error, promoting consistent results and reliability in diagnosis.

• Standardization: Enhances uniform processes for inter-laboratory comparability and research purposes.

Page 9: Workflow Optimization

• Workforce Optimization: Frees skilled staff to focus on complex analyses and quality control.

• Sample Tracking: Robust tracking ensures compliance and traceability.

• Cost-Effectiveness: Reduces long-term expenses associated with materials and errors.

Page 10: Enhanced Automation Benefits

• Consistency: Maintains controlled conditions minimizing operator variability.

• Integration with LIS: Facilitates efficient data management and result reporting.

• Complex Assays: Handles intricate tests effectively, improving accuracy.

• High-Throughput Testing: Supports laboratories in processing numerous samples without compromising quality.

Page 11: Drawbacks of Clinical Chemistry Automation

• Initial Costs: High upfront investments for equipment and infrastructure.

• Increased Supplies Costs: Regular maintenance and specialized reagents increase ongoing expenditures.

• Space Requirements: Larger systems may strain smaller laboratory setups.

Page 12: Operational Challenges

• Staff Overcrowding: Can result from reduced manual activities; proper workflow is vital.

• Noise and Heat: Generations from equipment require management to maintain lab conditions.

• Risk of Downtime: Technical issues can disrupt workflow and delay results.

Page 13: Psychological and Operational Issues

• Dependence on Automation: May erode confidence in manual techniques among staff.

• Biospecimen Management: Requires careful integrity and traceability planning.

• Disruption of Staff Training: Transition may affect staff trained in traditional methods.

• Manufacturer Dependence: Risk of being tied to specific manufacturers due to standardization.

Page 14: Functions of Automated Analyzers

• Mixing:

  • Continuous Flow: Liquids are pumped through a tubing system, utilizing air bubbles as separators.

  • Discrete Analysis: Reagents are mixed in individual containers (cuvettes), ensuring thorough reaction.

Page 15: Incubation Processes

• Sequential Incubation: Maintains controlled conditions during sample processing with proper timing.

• ELISA Analyzers: Automated workstations streamline the handling and processing of plates.

Page 16: Reagent Transfer

• Automated Pipetting: Robotic arms ensure precise reagent transfer to reaction cells.

• Sample Handling: Sequential analyzers maintain order in reagent addition and timing.

Page 17: Understanding Autoverification

• Definition: Autoverification uses algorithms to manage laboratory test results with minimal manual intervention.

Page 18: Autoverification Process

• Immediate Verification: Results are verified right after analysis against predefined limits.

• Repeat Analysis: Results outside acceptable ranges may initiate further testing.

• Reflex Testing: Additional tests can be triggered automatically based on initial results.

Page 19: Autoverification Benefits

• Efficiency: Speeds up result reporting and decreases turnaround times.

• Error Detection: Identifies pre-analytical and analytical errors in the workflow.

• Staff Optimization: Allows staff to concentrate on complex tasks rather than routine ones.

Page 20: Corrective Actions in Autoverification

• Flagging: Alerts staff if results fall outside acceptable ranges for review.

• Manual Review: Some results necessitate human evaluation based on context.

• Quality Control Checks: Regular checks ensure autoverified results' accuracy and integrity.

• Algorithm Refinement: Algorithms are refined based on evolving patient data and laboratory needs.

Page 21: Moving Averages in Autoverification

• Real-Time Data Monitoring (RTDM): Enables continuous tracking of assay performance over time.

• Advantages: Improves detection of shifts in performance compared to traditional quality control methods.

Page 22: Systematic Error Detection

• Systematic Error Monitoring: Moving averages help identify gradual performance shifts due to changes in materials or methods.

Page 23: Impact of Moving Averages

• Reducing Medical Errors: Enhances patient safety by identifying issues in real time.

• Comprehensive Quality Assurance: Complements QC methods, providing a dynamic quality control approach.

Page 24: Reporting Critical Results

• Critical Risk Values: Significant deviations requiring immediate physician notification 24/7, based on laboratory values and patient factors.

Page 25: Reporting Procedures

• Immediate Reporting: Critical results must be communicated promptly.

• Written Confirmation: Verbal communications require written documentation to ensure accuracy.

Page 26: Documentation Protocols

• Reporting staff must clearly identify themselves and confirm patient information before reporting critical results.

Page 27: Summary of Key Topics

• Automation Benefits: Streamlines tasks, reduces errors, and enhances workforce optimization.

• Automation Challenges: Consider initial costs, ongoing supply expenditures, and potential disruptions.

• Automated Analyzer Functions: Include essential processes like mixing and transferring reagents for various assays.

• Autoverification Benefits: Promotes efficiency, error detection, and optimal staff use through algorithmic handling of results.