Introduction: In the realm of medical laboratory testing, ensuring the accuracy and reliability of examination results is paramount for effective patient care. ISO 15189 outlines various requirements to guarantee the quality and consistency of laboratory processes. Among these requirements, section 7.3.7.4 emphasizes the importance of establishing comparability of examination results when different methods, equipment, or testing sites are utilized. This is achieved through the concept of commutability, which plays a crucial role in ensuring the validity of laboratory test results.
What is Commutability? Commutability refers to the property of a reference material or sample to behave in a manner similar to patient samples when subjected to different laboratory testing methods, equipment, or conditions. In simpler terms, a commutable sample yields results that accurately reflect the patient’s true biological status, regardless of the testing environment.
Imagine you’re baking a cake and you have two recipes. One recipe measures sugar in cups (Method A) and the other measures sugar in grams (Method B). Now, to make sure both recipes give you the same sweetness in the cake, you need to know if a cup of sugar is the same as a gram of sugar. If it is, we say the sugar is “commutable” between the two methods.
Example 1: Commutable Sample
- Method A (measuring in cups): You use 1 cup of sugar.
- Method B (measuring in grams): You use 200 grams of sugar.
In this case, if you convert 200 grams of sugar to cups, you’ll find it’s also 1 cup. So, the sugar behaves the same way in both methods. That’s what we mean by “commutable” – the measurements give you the same result even though they’re done differently.
Example 2: Non-Commutable Sample
- Method A (measuring in cups): You use 1 cup of sugar.
- Method B (measuring in grams): You use 150 grams of sugar.
Now, if you convert 150 grams of sugar to cups, you might find it’s less than 1 cup. This means the sugar doesn’t behave the same way in both methods. So, we say it’s “non-commutable” because the measurements don’t match up.
For a laboratory technician, they need to compare results from different methods or units to see if they match. If they do, it’s likely the sample is commutable. But if there’s a big difference between the results, it suggests the sample might not be behaving the same way in both methods, meaning it’s non-commutable. So, during comparison, technicians need to look for consistency – if the measurements give similar results, it’s commutable; if not, it’s non-commutable.
Importance of Comparability of Examination Results: Ensuring comparability of examination results is essential for several reasons:
- Patient Care: Accurate and reliable test results are vital for appropriate diagnosis, treatment decisions, and patient management.
- Clinical Decision Making: Healthcare professionals rely on laboratory test results to make informed clinical decisions. Inaccurate or inconsistent results can lead to misdiagnosis or inappropriate treatment.
- Quality Assurance: Maintaining comparability of results demonstrates the laboratory’s commitment to quality assurance and adherence to international standards.
ISO 15189 Requirements: ISO 15189 outlines specific requirements for establishing comparability of examination results, particularly when different methods, equipment, or testing sites are utilized. These requirements include:
- Specifying procedures for establishing comparability of results for patient samples throughout clinically significant intervals.
- Using patient samples when comparing different examination methods to avoid limitations associated with the limited commutability of Internal Quality Control (IQC) materials.
- Exploring alternative options, such as External Quality Assessment (EQA), when patient samples are unavailable or impractical.
Establishing Comparability: To establish comparability between Method A and Method B, the laboratory must ensure that both methods yield results that accurately reflect the patient’s hemoglobin concentration. This involves:
- Selecting Commutable Samples: Utilizing patient samples that represent a range of hemoglobin concentrations and biological matrices.
- Performing Comparative Studies: Analyzing patient samples using both Method A and Method B to assess agreement and identify any discrepancies.
- Statistical Analysis: Employing statistical methods, such as regression analysis or Bland-Altman plots, to evaluate the correlation and agreement between the results obtained from Method A and Method B.
- Adjusting Results if Necessary: Implementing correction factors or calibration adjustments to align the results obtained from Method A and Method B, if significant discrepancies are identified.
Example Scenarios: Consider two scenarios involving the measurement of hemoglobin concentration using different methods: Method A and Method B.
Example:
Test Parameter: Glucose concentration
Method A: Measurement in mg/dL (milligrams per deciliter)
Method B: Measurement in mmol/L (millimoles per liter)
Given:
- Method A (mg/dL): Glucose concentration = 100 mg/dL
- Method B (mmol/L): Glucose concentration = 5.55 mmol/L
Conversion Formula: To convert glucose concentration from mg/dL to mmol/L, we use the following formula: Glucose (mmol/L)=Glucose (mg/dL)18.015Glucose (mmol/L)=18.015Glucose (mg/dL)
Applying the Values: Glucose (mmol/L)=10018.015≈5.55 mmol/LGlucose (mmol/L)=18.015100≈5.55 mmol/L
Now, let’s compare the converted value (5.55 mmol/L) with the value obtained from Method B (5.55 mmol/L).
Since both values match, we can conclude that the sample is commutable between Method A and Method B for glucose concentration measurement.
Analysis: In this example, we have successfully converted the glucose concentration from mg/dL to mmol/L using the appropriate conversion formula. The converted value matches the value obtained directly from Method B, indicating that the sample behaves similarly in both methods. Therefore, we can confidently say that the sample is commutable between the two methods for glucose concentration measurement.
how much difference in results is acceptable to say it is commutable?
The acceptable difference in results to determine commutability depends on various factors, including the specific test parameter, the clinical significance of the measurement, and the intended use of the results. In general, a small difference between measurements obtained from different methods or units may still be considered acceptable if it falls within predetermined criteria for comparability.
There isn’t a universally defined threshold for acceptable differences in results to declare commutability, as it can vary depending on the context and requirements of the laboratory. However, laboratories often establish their own criteria based on factors such as:
- Clinical Guidelines: Some clinical guidelines or regulatory requirements may specify acceptable limits of difference for certain test parameters based on their clinical significance.
- Analytical Performance: The analytical performance characteristics of the testing methods involved may influence the acceptable difference. Methods with higher precision and accuracy may tolerate smaller differences.
- Biological Variation: Understanding the inherent biological variation of the analyte being measured can provide insights into the expected range of differences between measurements.
- Quality Control Data: Historical quality control data and proficiency testing results may be used to assess the variability of measurements and determine acceptable differences.
- Clinical Impact: Consideration of the potential clinical impact of differences in results is essential. If the difference is large enough to affect clinical decisions or patient management, it may not be acceptable.
Ultimately, laboratories should establish and document their own criteria for determining commutability based on a thorough understanding of the test parameters, analytical methods, and clinical context. Regular monitoring of assay performance and ongoing evaluation of commutability can help ensure the reliability and accuracy of laboratory testing results.
Case study :
Hypothetical Test Parameter: Serum Creatinine
Serum creatinine is a commonly measured parameter in clinical biochemistry used to assess kidney function. It is typically expressed in units of mg/dL (milligrams per deciliter). However, some laboratories may use an alternative method that reports creatinine levels in μmol/L (micromoles per liter).
Scenario: A laboratory is using two different methods for measuring serum creatinine:
- Method A: Measures creatinine concentration in mg/dL
- Method B: Measures creatinine concentration in μmol/L
Given:
- Method A (mg/dL): Serum creatinine = 1.0 mg/dL
- Method B (μmol/L): Serum creatinine = 88.4 μmol/L
Establishing Commutability: To determine if the results obtained from Method A and Method B are commutable, we need to convert the units to a common scale and compare them.
Conversion Formula: To convert serum creatinine from mg/dL to μmol/L, we use the following formula: Creatinine (μmol/L)=Creatinine (mg/dL)×88.4Creatinine (μmol/L)=Creatinine (mg/dL)×88.4
Applying the Values: Creatinine (μmol/L)=1.0×88.4=88.4 μmol/LCreatinine (μmol/L)=1.0×88.4=88.4 μmol/L
Comparison: The converted value (88.4 μmol/L) matches the value obtained directly from Method B (88.4 μmol/L), indicating that the sample is commutable between the two methods for serum creatinine measurement.
Acceptability of Variation: In this scenario, the difference between the results obtained from Method A and Method B is negligible. However, if the difference between the results were significant and fell outside of predefined acceptable limits established by the laboratory, it would indicate non-commutability.
Reasons for Non-Commutable Variation:
- Biological Variation: Serum creatinine levels can be influenced by various factors, including age, gender, muscle mass, and dietary intake. Differences in patient populations or sample characteristics may contribute to non-commutable variations between methods.
- Analytical Variability: Variability in the analytical performance of the methods, such as precision and accuracy, can lead to differences in results. Non-commutable variations may arise if one method has inherently poorer analytical performance compared to the other.
- Unit Conversion Errors: Errors in unit conversion or calibration adjustments between methods can introduce discrepancies in results. Inaccurate conversion factors or calibration procedures may result in non-commutability.
Conclusion: Establishing commutability between different methods for laboratory testing is essential to ensure the accuracy and reliability of test results. By applying appropriate conversion techniques and comparing results, laboratories can determine the acceptability of variations and make informed decisions regarding result reporting. In cases where non-commutable variations are identified, further investigation and corrective actions may be necessary to improve assay performance and maintain the quality of laboratory testing.
So, Commutability plays a crucial role in ensuring the comparability of examination results in medical laboratory testing. By adhering to ISO 15189 requirements and employing appropriate strategies, laboratories can confidently assess and establish the comparability of results when utilizing different methods, equipment, or testing sites. This ensures the delivery of accurate and reliable laboratory test results, ultimately contributing to improved patient care and clinical outcomes.
About the Author
Dr. Sambhu Chakraborty is a distinguished consultant in quality accreditation for laboratories and hospitals. With a leadership portfolio that includes directorial roles in two laboratory organizations and a consulting firm, as well as chairman of IOL ( An ILAC stakeholder organisation), Dr. Chakraborty is a respected voice in the field. For further engagement or inquiries, Dr. Chakraborty can be contacted through email at director@iaqmconsultants.com and contact information are available on his websites,https://www.quality-pathshala.com and https://www.sambhuchakraborty.com , or via WhatsApp at +919830051583