Lab Med Online.  2023 Oct;13(4):255-262. 10.47429/lmo.2023.13.4.255.

Application of the Analytical Performance Specification for Quality Management of Clinical Chemistry Tests

• Yim J
• Rim hH
• Lim YK
• Cho Y
• Park Y
• Kim S
• Yun YM

• KMID: 2552751
• DOI: http://doi.org/10.47429/lmo.2023.13.4.255

Abstract

In the realm of clinical laboratories, the implementation of a quality management system is vital for the quality management of various test results for patient treatment. Analytical performance specifications (APS) serve as the critical criteria for assessing whether clinical requirements have been fulfilled, and ensuring that these standards are based on appropriate evidence is crucial to effectively estimate the processes and outcomes of the quality management system. Our aim was to define practical APS goals as acceptability criteria for evaluating test quality. This would make it straightforward for laboratories to apply these guidelines. To this end, we examined relevant Clinical and Laboratory Standards Institute guidelines employed in the quality management of clinical laboratories, such as encompassing precision, linearity, comparison between measurement procedures or samples, comparison between reagent lots, delta check of patients’ results, bias evaluation of test methods, among others. Furthermore, after discussion with the Committee on Standardization and Quality Improvement of Korean Society of Clinical Chemistry, we proposed definitions on the evaluation criteria provided in each guideline and the types of APS such as imprecision, bias, and the total allowable error corresponding to them. Setting multiple evidence-based APS goals for each clinical chemistry test would assist in establishing a range of performance levels that clinical laboratories should aim for. We expect the data suggested in this review to facilitate effective quality management for various clinical chemistry tests and simplify the selection and application of APS for the unique circumstances of each laboratory.

Keyword

Analytical performance specification; Biological variation; Clinical chemistry; Quality management

Reference

1. Allen LC. 2013; Role of a quality management system in improving patient safety - laboratory aspects. Clin Biochem. 46:1187–93. DOI: 10.1016/j.clinbiochem.2013.04.028. PMID: 23648455.

2. Schmidt RL, Moore RA, Walker BS, Rudolf JW. 2023; Precision quality control: a dynamic model for risk-based analysis of analytical quality. Clin Chem Lab Med. 61:679–87. DOI: 10.1515/cclm-2022-1094. PMID: 36617955.

3. Lim CY, Lee JJS, Choy KW, Badrick T, Markus C, Loh TP. 2023; Between and within calibration variation: implications for internal quality control rules. Pathology. 55:525–30. DOI: 10.1016/j.pathol.2022.11.013. PMID: 36894352.

4. Tan RZ, Markus C, Loh TP. 2020; An approach to optimize delta checks in test panels - The effect of the number of rules included. Ann Clin Biochem. 57:215–22. DOI: 10.1177/0004563220904749. PMID: 31955587.

5. Walker BS, Pearson LN, Schmidt RL. 2020; An analysis of multirules for monitoring assay quality control. Lab Med. 51:94–8. DOI: 10.1093/labmed/lmz038. PMID: 31250900.

6. Westgard JO. 2003; Internal quality control: planning and implementation strategies. Ann Clin Biochem. 40:593–611. DOI: 10.1258/000456303770367199. PMID: 14629798.

7. Song Z, Zhang J, Liu B, Wang H, Bi L, Xu Q. 2022; Practical application of European biological variation combined with Westgard Sigma Rules in internal quality control. Clin Chem Lab Med. 60:1729–35. DOI: 10.1515/cclm-2022-0327. PMID: 36036501.

8. Plebani M. 2017; Quality in laboratory medicine: 50years on. Clin Biochem. 50:101–4. DOI: 10.1016/j.clinbiochem.2016.10.007. PMID: 27760306.

9. Braga F, Pasqualetti S, Borrillo F, Capoferri A, Chibireva M, Rovegno L, et al. 2022; Definition and application of performance specifications for measurement uncertainty of 23 common laboratory tests: linking theory to daily practice. Clin Chem Lab Med. 61:213–23. DOI: 10.1515/cclm-2022-0806. PMID: 36282875.

10. Braga F, Panteghini M. Performance specifications for measurement uncertainty of common biochemical measurands according to Milan models. Clin Chem Lab Med. 2021; 59:1362–8. DOI: 10.1515/cclm-2021-0170. PMID: 33725754.

11. Ceriotti F, Fernandez-Calle P, Klee GG, Nordin G, Sandberg S, Streichert T, et al. 2017; Criteria for assigning laboratory measurands to models for analytical performance specifications defined in the 1st EFLM Strategic Conference. Clin Chem Lab Med. 55:189–94. DOI: 10.1515/cclm-2016-0091. PMID: 27506603.

12. Sandberg S, Fraser CG, Horvath AR, Jansen R, Jones G, Oosterhuis W, et al. 2015; Defining analytical performance specifications: consensus statement from the 1st strategic conference of the European federation of clinical chemistry and laboratory medicine. Clin Chem Lab Med. 53:833–5. DOI: 10.1515/cclm-2015-0067. PMID: 25719329.

13. Ricós C, Álvarez V, Perich C, Fernández-Calle P, Minchinela J, Cava F, et al. 2015; Rationale for using data on biological variation. Clin Chem Lab Med. 53:863–70. DOI: 10.1515/cclm-2014-1142. PMID: 25928757.

14. Keleş M. 2022; Evaluation of the clinical chemistry tests analytical performance with Sigma Metric by using different quality specifications - Comparison of analyser actual performance with manufacturer data. Biochem Med (Zagreb). 32:010703. DOI: 10.11613/BM.2022.010703. PMID: 34955671. PMCID: PMC8672391.

15. The Royal College of Pathologists of Australasia. Analytical performance specifications. https://rcpaqap.com.au/resources/. Updated on Dec 2022.

16. Clinical and Laboratory Standards Institute. 2022. Verification of comparability of patient results within one health care system implementation guide. 1st ed. CLSI implementation guide EP31-Ed1-IG. Clinical and Laboratory Standards Institute.

17. Clinical and Laboratory Standards Institute. 2022. User evaluation of acceptability of a reagent lot change implementation guide. CLSI implementation guide EP26-Ed2-IG. Clinical and Laboratory Standards Institute;Wayne PA:

18. Clinical and Laboratory Standards Institute. 2022. User evaluation of acceptability of a reagent lot change. 2nd ed. CLSI guideline EP26. Clinical and Laboratory Standards Institute;Wayne PA:

19. Clinical and Laboratory Standards Institute. 2022. Evaluation of commutability of processed samples. 4th ed. CLSI guideline EP14. Clinical and Laboratory Standards Institute;Wayne PA:

20. Clinical and Laboratory Standards Institute. 2022. User VERIFICATION OF LINEARITY IMPLEMENTATION Guide. 1st ed. CLSI implementation guide EP06-Ed2-IG. Clinical and Laboratory Standards Institute;Wayne PA:

21. Clinical and Laboratory Standards Institute. 2021. Evaluation of total analytical error for quantitative medical laboratory measurement procedures implementation guide. 1st ed. CLSI implementation guide EP21-Ed2-IG. Clinical and Laboratory Standards Institute;Wayne PA:

22. Clinical and Laboratory Standards Institute. 2021. Evaluation of detection capability implementation guide. 1st ed. CLSI implementation guide EP17-Ed2-IG. Clinical and Laboratory Standards Institute;Wayne PA:

23. Clinical and Laboratory Standards Institute. 2021. User verification of bias (trueness) implementation guide. 1st ed. CLSI implementation guide EP15-Ed3-IG2. Clinical and Laboratory Standards Institute;Wayne PA:

24. Clinical and Laboratory Standards Institute. 2021. User verification of precision implementation guide. 1st ed. CLSI implementation guide EP15-Ed3-IG1. Clinical and Laboratory Standards Institute;Wayne PA:

25. Clinical and Laboratory Standards Institute. 2020. Evaluation of linearity of quantitative measurement procedures. 2nd ed. CLSI guideline EP06. Clinical and Laboratory Standards Institute;Wayne PA:

26. Clinical and Laboratory Standards Institute. 2019. Assessment of equivalence or suitability of specimen types for medical laboratory measurement procedures. 1st ed. CLSI guideline EP35. Clinical and Laboratory Standards Institute;Wayne, PA:

27. Clinical and Laboratory Standards Institute. 2018. Measurement procedure comparison and bias estimation using patient samples. 3rd ed. CLSI guideline EP09c. Clinical and Laboratory Standards Institute;Wayne, PA:

28. Clinical and Laboratory Standards Institute. 2016. Evaluation of total analytical error for quantitative medical laboratory measurement procedures. 2nd ed. CLSI guideline EP21. Clinical and Laboratory Standards Institute;Wayne, PA:

29. Clinical and Laboratory Standards Institute. 2016. Use of delta checks in the medical laboratory. 1st ed. CLSI guideline EP33. Clinical and Laboratory Standards Institute;Wayne, PA:

30. Clinical and Laboratory Standards Institute. 2014. User verification of precision and estimation of bias; Approved guideline-Third edition. CLSI document EP15-A3. Clinical and Laboratory Standards Institute;Wayne, PA:

31. Clinical and Laboratory Standards Institute. 2014. Evaluation of precision of quantitative measurement procedures; Approved guideline-Third edition. CLSI document EP05-A3. Clinical and Laboratory Standards Institute;Wayne, PA:

32. Clinical and Laboratory Standards Institute. 2012. Verification of comparability of patient results within one health care system; Approved guideline (interim revision). CLSI document EP31-A-IR. Clinical and Laboratory Standards Institute;Wayne, PA:

33. Clinical and Laboratory Standards Institute. 2012. Expression of measurement uncertainty in laboratory medicine; Approved guideline. CLSI document EP29-A. Clinical and Laboratory Standards Institute;Wayne, PA:

34. Clinical and Laboratory Standards Institute. 2012. Evaluation of detection capability for clinical laboratory measurement procedures; Approved guideline-Second edition. CLSI document EP17-A2. Clinical and Laboratory Standards Institute;Wayne, PA:

35. Simundic AM, Kackov S, Miler M, Fraser CG, Petersen PH. 2015; Terms and symbols used in studies on biological variation: the need for harmonization. Clin Chem. 61:438–9. DOI: 10.1373/clinchem.2014.233791. PMID: 25403815.

36. Aarsand AK, Fernandez-Calle P, Webster C, Coskun A, Gonzales-Lao E, Diaz-Garzon J, et al. The EFLM Biological Variation Database. https://biologicalvariation.eu/. Last accessed on May 2023.

37. Westgard QC. Desirable biological variation database specifications. https://www.westgard.com/biodatabase1.htm. Updated on 2014.

38. Ricós C, Alvarez V, Cava F, García-Lario JV, Hernández A, Jiménez CV, et al. 1999; Current databases on biological variation: pros, cons and progress. Scand J Clin Lab Invest. 59:491–500. DOI: 10.1080/00365519950185229. PMID: 10667686.

39. Caudill SP, Cooper GR, Smith SJ, Myers GL. 1998; Assessment of current National Cholesterol Education Program guidelines for total cholesterol triglyceride, HDL-cholesterol, and LDL-cholesterol measurements. Clin Chem. 44:1650–8. DOI: 10.1093/clinchem/44.8.1650. PMID: 9702951.

40. The Association for Diagnostics & Laboratory Medicine. NACB: Laboratory support for the diagnosis and monitoring of thyroid disease. https://www.aacc.org/-/media/Files/Science-and-Practice/Practice-Guidelines/Thyroid-Disease/ThyroidArchived2010.pdf?la=en&hash=0556298535B60C441FBB6AC742E3A4652E0332F8. Updated on Jan 2002.

41. Lund F, Petersen PH, Fraser CG, Sölétormos G. 2015; Calculation of limits for significant unidirectional changes in two or more serial results of a biomarker based on a computer simulation model. Ann Clin Biochem. 52:237–44. DOI: 10.1177/0004563214534636. PMID: 24757181.

42. Bettencourt da Silva R, Williams A. Eurachem/CITAC guide: setting and using target uncertainty in chemical measurement. 1st ed. https://www.eurachem.org/images/stories/Guides/pdf/STMU_2015_EN.pdf. Updated on 2015.

43. Petersen PH, Fraser CG, Westgard JO, Larsen ML. 1992; Analytical goal-setting for monitoring patients when two analytical methods are used. Clin Chem. 38:2256–60. DOI: 10.1093/clinchem/38.11.2256. PMID: 1424120.

44. Westgard QC. Consolidated comparison of chemistry performance specifications. https://www.westgard.com/consolidated-goals-chemistry.htm. Updated on Oct 2022.