Errors In Lab Tests Flashcards
Explain the quality assurance cycle
The image illustrates the Quality Assurance Cycle, which is divided into three main phases: Pre-Analytic, Analytic, and Post-Analytic. Each phase comprises several key activities that ensure the accuracy and reliability of laboratory results.
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Pre-Analytic Phase:
- Patient/Client Preparation and Sample Collection: Properly preparing the patient and collecting the sample is crucial. This includes explaining the procedure to the patient and ensuring the sample is collected correctly.
- Personnel Competency Test Evaluations: Ensuring that the staff involved in sample collection and processing are competent and properly trained.
- Sample Receipt and Accessioning: Properly receiving, labeling, and logging the samples into the system to avoid mix-ups.
- Sample Transport: Safely and efficiently transporting the samples to the laboratory without compromising their integrity.
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Analytic Phase:
- Quality Control Testing: Performing tests and procedures to ensure the quality and accuracy of the laboratory tests. This includes running control samples to verify that the test systems are working correctly.
- Data and Lab Management: Managing the data generated from the tests and ensuring the lab environment meets the required standards.
- Safety: Maintaining safety protocols to protect both staff and samples.
- Customer Service: Providing information and support to patients and healthcare providers.
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Post-Analytic Phase:
- Reporting: Accurately reporting the test results to the relevant healthcare providers.
- Record Keeping: Maintaining detailed and accurate records of all tests and results to ensure traceability and accountability.
In the center of the cycle, core aspects such as data and lab management, safety, and customer service are highlighted, indicating their overarching importance throughout all phases of the quality assurance process.
Customer service and reporting test results both involve interactions with patients and healthcare providers, but they occur at different stages of the laboratory process and serve different purposes:
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Providing Information and Support During Testing: During the analytical stage, customer service focuses on assisting patients and healthcare providers with inquiries related to the testing process. This might include:
- Clarifying Test Procedures: Explaining how tests are conducted and what patients need to do during the process.
- Addressing Concerns: Responding to questions or concerns about the testing procedure, potential delays, or any issues that arise during the analysis.
- Immediate Support: Offering real-time assistance to healthcare providers regarding the status of tests, preliminary observations, or any immediate needs that impact the ongoing testing process.
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Communicating Final Results: In the post-analytical stage, the focus shifts to communicating the final outcomes of the tests. This includes:
- Interpreting Results: Providing clear, accurate, and comprehensible reports of the test results to healthcare providers and, if appropriate, to patients.
- Follow-up Information: Offering detailed explanations or consultations regarding the implications of the test results and potential next steps.
- Documentation: Ensuring that results are properly documented and integrated into patients’ medical records.
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Timing:
- Analytical Stage: Customer service during the testing process addresses immediate, ongoing inquiries and support needs.
- Post-analytical Stage: Reporting test results happens after the tests are completed and focuses on communicating the final outcomes.
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Purpose:
- Analytical Stage: Support during the analytical stage is about ensuring the smooth progression of the testing process and addressing any issues or questions that arise in real-time.
- Post-analytical Stage: Reporting test results is about conveying the findings of the tests, interpreting the data, and providing actionable information based on the results.
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Interactions:
- Analytical Stage: Interactions might involve explaining procedures, addressing immediate concerns, and providing updates on test progress.
- Post-analytical Stage: Interactions focus on delivering, explaining, and discussing the results of the tests.
By understanding these distinctions, you can more accurately determine which stage a particular customer service activity belongs to in the context of laboratory processes.
Under factors that affect test results, The sources of errors in biochemical tests are conventionally described in three categories,state and define them
The sources of errors in biochemical tests are conventionally described in three categories:
• preanalytical: that is, either outside or within the laboratory, but before the analysis is performed
• analytical: these may be random (e.g. due to the presence of an interfering substance in the specimen) or systematic (e.g. because of a bias in the method)
• postanalytical: that is, occurring during data processing or transmission, or in relation to the interpretation of the data.
Which of the three categories of lab errors are the most common?
What is the next most common and the least common?
Preanalytical
• 46 - 68%
Postanalytical
• 18 - 47%
Analytical
• 8 - 17%
What is the pre analytical phase in laboratory practice?
Pre-analytical phase in laboratory practice begins from the requisition of the test by the health practitioner until the moment the sample is ready for analysis.
A lab guy labeled a sample collection tube incorrectly and mismatched the sample, what category of lab error is this?
State three more examples
Pre analytical errors.
Examples of pre-analytical errors
• Wrong test ordered
• Poor blood draw (e.g. haemolyzed sample)
•Wrong specimen collection tube used
•Excessive delays in sample transport to lab
•Sample collection tube labeled incorrectly
• Sample mis-match, lost in transit etc.
State five main processes involved in the pre analytical phase
Five main processes are involved in this phase
• Patient’s status,
• Specimen collection,
• Specimen transportation to the laboratory,
• Specimen processing and
• Specimen delivery to the instrument for analysis.
Specimen processing refers to the steps taken to prepare the collected sample for analysis. This includes a series of actions to ensure the sample is suitable for testing and to maintain its integrity. Specimen processing typically involves:
- Labeling: Ensuring that each sample is correctly labeled with patient information and a unique identifier to avoid mix-ups.
- Aliquoting: Dividing the sample into smaller portions if multiple tests are required, ensuring that each aliquot is properly labeled.
- Centrifugation: Spinning blood samples to separate plasma or serum from blood cells, which is necessary for many types of tests.
- Storage: Storing samples at appropriate temperatures (e.g., refrigeration, freezing) to preserve their integrity until analysis.
- Documentation: Recording details about the sample, such as collection time, processing steps, and any specific instructions for handling.
Specimen delivery to the instrument for analysis involves the steps taken to transfer the processed sample to the laboratory equipment that will perform the analysis. This includes:
- Transport: Moving the sample from the processing area to the analytical area within the lab. This must be done carefully to prevent contamination or degradation.
- Loading: Placing the sample into the appropriate position on the analytical instrument. This might involve loading samples into a carousel, placing them in a sample rack, or inserting them into an automated system.
- Calibration and Quality Control: Ensuring that the instrument is calibrated and quality control samples are run to verify that the instrument is working correctly before analyzing patient samples. Chat gpt says this is analytical not pre analytical
- Verification: Double-checking that the sample and instrument settings match the test requirements, ensuring that all necessary parameters are set for the analysis.
The pre-analytical stage encompasses all activities up until the point where the actual analysis begins. Handling the sample during processing and delivery to the instrument are considered pre-analytical because they involve preparatory steps. The analytical stage begins when the sample is actively being tested or analyzed by the laboratory instrument.
- Pre-analytical: A lab technician labels, aliquots, centrifuges, and stores a blood sample. They then transport the sample and load it into the analyzer.
- Analytical: The moment the instrument starts running the test on the sample, the analytical stage begins. This includes the actual measurement, detection, and recording of results.
By understanding these distinctions, you can more accurately categorize different steps in the laboratory process as pre-analytical or analytical.
What are analytical errors
State the three main causes
These errors occur during actual testing of the specimen.
Causes:
Personnel inadequacies or integrity of personnel
Instrument related problems or integrity of instruments
Sample related errors or integrity of specimen
You are correct that equipment calibration and setup are critical pre-analytical activities, but issues that arise from these processes can manifest as both pre-analytical and analytical errors, depending on when they are detected and how they impact the testing process.
Pre-analytical Activities:
- Calibration of Instruments: Ensuring that laboratory instruments are properly calibrated before beginning the analysis.
- Equipment Setup: Preparing and setting up equipment correctly before use.
- Sample Collection and Handling: Collecting, labeling, transporting, and storing samples properly.
Pre-analytical Errors:
- Calibration Errors: Incorrect calibration of instruments before testing begins, leading to potential inaccuracies in all subsequent analyses.
- Setup Errors: Improper setup or preparation of equipment that can affect the quality of the analysis.
- Sample Handling Errors: Errors in how samples are collected, labeled, transported, or stored that can impact their integrity and suitability for analysis.
Analytical Activities:
- Testing and Analysis: The actual process of analyzing the sample using calibrated instruments and established protocols.
- Staining Procedures: Applying stains (e.g., Giemsa stain) and preparing the sample for microscopic or other analyses.
- Data Collection: Recording the results obtained from the analytical instruments.
Analytical Errors:
- Personnel Errors: Mistakes made by lab personnel during the actual testing process (e.g., incorrect execution of protocols).
- Instrument Errors: Issues that occur during the analysis due to equipment malfunction, drift, or failure to maintain calibration (e.g., an instrument not maintaining its calibrated state during the test).
- Sample Errors: Problems with the sample that affect the analysis, such as contamination or degradation that become apparent during the testing process.
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Pre-analytical Stage:
- Calibration: An instrument is not correctly calibrated before the testing begins. This error affects all tests performed until the calibration error is corrected.
- Setup: Incorrect settings applied to the equipment before analysis starts. This can lead to pre-analytical errors that affect the entire batch of samples.
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Analytical Stage:
- Calibration Drift: An instrument was correctly calibrated initially, but drifts out of calibration during the analysis, causing errors in the results of those tests.
- Incorrect Use of Equipment: The lab technician uses the equipment incorrectly during the testing process, despite proper pre-analytical calibration and setup.
- Pre-analytical Errors: Involve issues that occur before the actual testing starts, such as failing to properly calibrate or set up the equipment.
- Analytical Errors: Involve issues that arise during the testing process, including equipment malfunctions that occur during analysis, incorrect application of test protocols, and sample-related issues detected during the test.
While the calibration and setup of instruments are pre-analytical activities, the impact of errors in these processes can extend into the analytical stage, manifesting as inaccuracies during the testing itself. Proper calibration and setup are essential to avoid both pre-analytical and analytical errors.
Explain the three causes of analytical errors
CAUSES:
1. Personnel inadequacy (integrity of personnel)
• Knowledge and experience inadequate for performing the test
• Not meticulous enough, cuts corners - runs tests without controls or control after samples.
• Does not check abnormal test results or may not even be aware of which test results are abnormal.
• Does not communicate with more senior personnel when necessary for help and advice on problems encountered
ERRORS AFFECTING TEST RESULTS
2. Instrument-related problems (integrity of instrument)
-Instrument not calibrated / poorly calibrated instruments, instrument mal-functioning
-Inappropriate reagents - poor quality, expired, poor storage, not adhering to instructions.
ERRORS AFFECTING TEST RESULTS
3.
• Inappropriate sample - wrong anticoagulant, lipaemic, haemolyzed, clotted sample.
• Inadequate sample for test
• Sequence identification error
slides categorize these as analytical errors, they may be referring to the fact that these errors, although originating in the pre-analytical phase, directly affect the analytical process. For instance:
• A clotted sample or a sample with the wrong anticoagulant could lead to faulty analytical measurements, which would directly impact the results obtained during the analytical phase. • Inadequate sample for a test could disrupt the measurement process itself. • Sequence identification errors may affect how samples are handled or processed during the analytical run.
So, in a broader context, these errors impact the analytical outcomes and could be viewed as contributing to analytical errors. The distinction might be more about the focus on the impact rather than the process step in which the error initially occurs.
If your slides focus on how these errors affect the analytical results rather than where they originate, this might be why they are labeled as “analytical” in that context.
Explain the three causes of analytical errors
CAUSES:
1. Personnel inadequacy (integrity of personnel)
• Knowledge and experience inadequate for performing the test
• Not meticulous enough, cuts corners - runs tests without controls or control after samples.
• Does not check abnormal test results or may not even be aware of which test results are abnormal.
• Does not communicate with more senior personnel when necessary for help and advice on problems encountered
ERRORS AFFECTING TEST RESULTS
2. Instrument-related problems (integrity of instrument)
-Instrument not calibrated / poorly calibrated instruments, instrument mal-functioning Poorly calibrated instruments can lead to analytical errors even though calibration is a pre-analytical process. Here’s how this works:
- Calibration and Analytical Errors:• Calibration Process: Calibration is performed before sample analysis (pre-analytical) to ensure that the instrument provides accurate measurements. This involves adjusting the instrument using known standards.
• Impact on Analysis: If an instrument is poorly calibrated, it will provide incorrect measurements during the actual analysis of samples. This means the data collected will be inaccurate, leading to analytical errors in the results
-Inappropriate reagents - poor quality, expired, poor storage, not adhering to instructions.
ERRORS AFFECTING TEST RESULTS
3.
• Inappropriate sample - wrong anticoagulant, lipaemic, haemolyzed, clotted sample.
• Inadequate sample for test
• Sequence identification error
What is lipaemia
What causes it
How can it be avoided
Lipaemic (or lipemic) refers to a condition in which there is an abnormally high concentration of lipids (fats) in a blood sample, causing it to appear milky or turbid. This condition can affect the accuracy of certain laboratory tests, as the high lipid content can interfere with the measurement of other substances in the blood.
Common causes of lipaemia include:
• Recent ingestion of fatty foods: Consuming a high-fat meal before the blood draw can temporarily elevate lipid levels. • Hyperlipidemia: A medical condition characterized by chronically elevated levels of lipids in the blood. • Certain medications: Some drugs can increase lipid levels. • Metabolic disorders: Conditions like diabetes can affect lipid metabolism and lead to lipaemia.
To mitigate the impact of lipaemia on laboratory tests, patients are often advised to fast for several hours before having their blood drawn
What are post analytical errors
These are errors that occur after the test procedure has been completed.
They are the second most frequently encountered errors in the laboratory accounting for up to 47% of all laboratory errors.
What are the three main causes of post analytical errors
1.Transcription errors-Transcription errors occur when there are mistakes in recording or transferring data from one format to another. In a medical or laboratory context, these errors can have significant implications for patient care and diagnostic accuracy. Here are some common types of transcription errors:
- Manual Entry Errors: Mistakes made when manually entering data into a system, such as typographical errors or incorrect data input.
- Misinterpretation: Misreading handwritten notes or misinterpreting verbal instructions, leading to incorrect data being recorded.
- Omissions: Failing to record necessary information or leaving out critical data.
- Transposition Errors: Reversing numbers or letters, such as recording “56” instead of “65”.
- Duplication: Entering the same data multiple times.
- Inconsistent Data Entry: Using different formats or units of measurement inconsistently (e.g., mixing up milligrams and micrograms).
- Copy-Paste Errors: Mistakes arising from copying and pasting data incorrectly or into the wrong fields.
To reduce transcription errors, it’s important to implement robust quality control measures, such as:
- Double-checking entries
- Using electronic health records (EHRs) with automated data entry systems
- Implementing standardized procedures and training for data entry
- Regular audits and reviews of data for accuracy
2.Patient identification errors (data storage errors)
3.Errors of interpretation of results, leading to wrong reports.
Let’s consider a scenario where misinterpretation of information occurs in a laboratory setting:
Context: A laboratory technician is analyzing blood test results and is preparing a report for a patient. The test results are recorded in handwritten notes, and the technician also receives verbal instructions from a senior colleague about how to interpret certain results.
Details:
1. Handwritten Notes: The technician notes the results of a cholesterol test on a sheet of paper. The handwritten notes show a cholesterol level of 240 mg/dL, which is elevated according to standard reference ranges.
- Verbal Instructions: The technician is verbally instructed by a senior colleague that results in the range of 240 mg/dL to 260 mg/dL are considered normal for this specific patient due to special circumstances (e.g., a new treatment protocol that was not yet officially updated in the standard guidelines).
Misinterpretation:
- Error in Handwritten Notes: The technician misreads the handwritten notes and incorrectly records the cholesterol level as 200 mg/dL instead of the actual 240 mg/dL. This could happen due to poor handwriting or confusion in reading the notes.
- Error in Verbal Instructions: The technician misinterprets the verbal instruction and believes that a cholesterol level of 240 mg/dL is abnormal, whereas it is actually considered normal under the new protocol. This misunderstanding leads to the incorrect interpretation that the patient’s cholesterol level is dangerously high.
Outcome:
- Incorrect Data Recorded: The technician records the cholesterol level as 200 mg/dL in the report.
- Incorrect Interpretation: Due to the misinterpretation of the verbal instructions, the technician flags the result as needing urgent follow-up, even though the result is within the new acceptable range.
In this scenario, the misinterpretation of the handwritten notes and verbal instructions occurs after the testing is complete and involves the final steps of data handling, interpretation, and reporting. The errors here include:
- Misreading Handwritten Notes: Leads to incorrect data entry.
- Misinterpreting Verbal Instructions: Leads to incorrect conclusions about the patient’s health status.
These types of errors impact the final report and patient management decisions, highlighting the importance of clear documentation and accurate interpretation in the post-analytical stage.
State three examples of post analytical errors
Wrong interpretation
• Result does not reach physician
• Test not performed
• Panic value not communicated
• Sample not stored properly (in case retest ordered): Sample storage is typically considered a pre-analytical activity when it involves the handling and preservation of the sample before any testing has occurred. Here’s how to distinguish between pre-analytical and post-analytical aspects of sample storage:
Context:
- Before Analysis: The sample is being prepared for analysis, and its handling is crucial to ensure its integrity.
- Storage Procedures: Proper storage conditions are required to preserve the sample’s quality until it can be analyzed.
Pre-analytical Issues:
- Improper Handling: If the sample is not collected, labeled, or stored correctly immediately after collection, this falls under pre-analytical errors.
- Incorrect Storage Conditions: If a sample is not stored at the correct temperature or conditions immediately after collection and before analysis, it can lead to degradation. For example, blood samples that should be refrigerated but are left at room temperature.
Example:
- A blood sample is collected and immediately needs to be stored in a refrigerator. If it is accidentally left at room temperature, this improper storage before the analysis affects the sample’s integrity.
Context:
- After Initial Analysis: The sample has already been tested, and issues related to its storage impact the ability to perform any subsequent analyses or retests.
- Follow-Up Actions: It affects the reliability of any future testing or confirmatory procedures.
Post-analytical Issues:
- Storage for Retesting: If a sample is improperly stored after the initial test and a retest is ordered later, this improper storage affects the quality and reliability of the retest.
Example:
- After a cholesterol test, the sample is stored improperly. When a retest is later requested, the sample is now degraded due to previous improper storage, leading to potentially inaccurate retest results.
- Pre-analytical: Concerns with sample storage immediately after collection and before testing begins.
- Post-analytical: Concerns with sample storage after the initial testing, especially if a retest or further analysis is required.
Understanding these distinctions helps ensure that the appropriate measures are taken to maintain sample integrity throughout the laboratory process.
Post-analytical errors occur after the testing and analysis of samples, impacting the reporting and interpretation of results. Here are explanations for the given examples:
1. Wrong Interpretation • Example: A lab technician misinterprets a test result due to incorrect reference ranges or misunderstanding the clinical significance of the results. For instance, if a patient’s blood glucose level is within the normal range but is interpreted as high due to outdated reference values, this can lead to incorrect conclusions and unnecessary anxiety or treatment adjustments. • Impact: This error affects the clinical decisions made based on the test results, potentially leading to inappropriate treatment or follow-up actions. 2. Result Does Not Reach Physician • Example: A test result is completed and finalized, but due to a communication breakdown or administrative error, the result is not delivered to the physician who ordered it. For example, the report might be misplaced or not sent through the electronic health record system. • Impact: This results in the physician not having access to critical information needed for patient care, potentially delaying treatment or diagnosis. 3. Test Not Performed • Example: A test is ordered and scheduled, but due to an oversight or procedural error, the test is never actually conducted. For instance, a laboratory might accidentally omit a cholesterol test from a patient’s scheduled panel of tests. • Impact: This means the patient’s condition might not be fully assessed or managed, leading to incomplete diagnostic information and possible delay in appropriate care. 4. Panic Value Not Communicated • Example: A test result indicates a critical or “panic” value, such as a dangerously high potassium level, but the laboratory fails to promptly notify the physician. For instance, if the lab technician does not follow the protocol for urgent communication of critical results. • Impact: Failure to communicate panic values in a timely manner can delay urgent intervention, which might lead to serious patient complications or worsening of the condition.
Under effects of variables on the quality of lab testing,what are para analytical and analytical variables? Give three examples of such variables under each
Effects of Variables on the Quality of Laboratory Testing
• Para-analytical variables (pre & post analytical variables
• Analytical variables
Pre analytical:
-Test requests/ordering
-Patient identification
-Specimen acquisition
-Specimen transport
-Specimen processing: I understand now—you’re pointing out that specimen processing is indeed a pre-analytical step. You are right.
Specimen processing includes steps such as:
- Handling: Properly transporting and handling the specimen to avoid degradation or contamination.
- Labeling: Ensuring correct identification to avoid mix-ups.
- Centrifugation: Separating components (e.g., plasma, serum) after collection.
- Aliquoting: Dividing samples for different tests.
These steps occur after specimen collection but before the actual analytical phase in the lab. Therefore, errors occurring during specimen processing are considered pre-analytical errors because they happen before the testing (analytical phase) starts.
-Preparation of worklists and logs
-Maintenance records(preventive maintenance. includes all processes and quality checks before the actual testing begins. This could extend to ensuring that all equipment is properly maintained and calibrated before any specimen is processed or analyzed.
• Proper maintenance records ensure that instruments and equipment are functioning correctly, preventing errors right from the start of sample handling and preparation, thereby affecting the pre-analytical quality control.)
Analytic:
Competency
Controls
Methodology
Procedures
Monitoring of equipment
Monitoring of materials
Test validation
Post analytical:
Result reporting
Result interpretation
Result distribution
What is point of care testing?
WHAT IS POINT OF CARE TESTING?
• Point-of-care testing (POCT) is laboratory testing conducted close to the site of patient care.
• Point-of-care testing (POCT) refers to any testing conducted outside a lab, in a hospital, in a clinic or by a health care organization providing ambulatory care.
