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Continual improvement of the pre-analytical process in a public health laboratory with quality indicators-based risk management

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Published/Copyright: May 3, 2019
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 57 Issue 10

Abstract

Background

Quality indicators (QIs) and risk management are important tools for a quality management system designed to reduce errors in a laboratory. This study aimed to show the effectiveness of QI-based risk management for the continual improvement of pre-analytical processes in the Kayseri Public Health Laboratory (KPHL) which serves family physicians and collects samples from peripheral sampling units.

Methods

QIs of pre-analytical process were used for risk assessment with the failure modes and effects analysis (FMEA) method. Percentages and risk priority numbers (RPNs) of QIs were quantified. QI percentages were compared to the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) performance specifications and RPNs were compared to risk level scale, and corrective actions planned if needed. The effectiveness of risk treatment actions was re-evaluated with the new percentages and with RPNs of predefined QIs.

Results

RPNs related to four QIs required corrective action according to the risk evaluation scale. After risk treatment, the continual improvement was achieved for performance and risk level of “transcription errors”, for risk levels of “misidentified samples” and “not properly stored samples” and for the performance of “hemolyzed samples”. “Not properly stored samples” had the highest risk score because of sample storage and centrifugation problems of peripheral sampling units which are not under the responsibility of the KPHL.

Conclusions

Public health laboratories may have different risk priorities for pre-analytical process. Risk management based on predefined QIs can decrease the risk levels and increase QI performance as evidence-based examples for continual improvement of the pre-analytical process.

Keywords: continual improvement; FMEA; pre-analytical process; public health laboratory; quality indicators; risk management

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Plebani M. The detection and prevention of errors in laboratory medicine. Ann Clin Biochem 2010;47:101–10.10.1258/acb.2009.009222Search in Google Scholar PubMed

2. Simundic AM, Lippi G. Preanalytical phase – a continuous challenge for laboratory professionals. Biochem Med (Zagreb) 2012;22:145–9.10.11613/BM.2012.017Search in Google Scholar PubMed PubMed Central

3. Plebani M, Sciacovelli L, Marinova M, Marcuccitti J, Chiozza ML. Quality indicators in laboratory medicine: a fundamental tool for quality and patient safety. Clin Biochem 2013;46:1170–4.10.1016/j.clinbiochem.2012.11.028Search in Google Scholar PubMed

4. Barth JH. Clinical quality indicators in laboratory medicine. Ann Clin Biochem 2012;49:9–16.10.1258/acb.2011.011126Search in Google Scholar PubMed

5. Lippi G, Guidi GC. Risk management in the preanalytical phase of laboratory testing. Clin Chem Lab Med 2007;45:720–7.10.1515/CCLM.2007.167Search in Google Scholar PubMed

6. Remona Eliza D, Monodora D. Risk management in laboratory medicine: from theory to practice. Acta Med Marisiensis 2015;61:372–77.10.1515/amma-2015-0086Search in Google Scholar

7. Plebani M. Quality in laboratory medicine: 50 years on. Clin Biochem 2017;50:101–4.10.1016/j.clinbiochem.2016.10.007Search in Google Scholar PubMed

8. ISO 15189:2012. Medical laboratories – requirements for quality and competence. Geneva, Switzerland: International Organization for Standardization, 2012.Search in Google Scholar

9. ISO Guide 73:2009. Risk management – Vocabulary. Geneva, Switzerland: International Organization for Standardization, 2009.Search in Google Scholar

10. ISO/IEC Guide 51:2014. Safety aspects – guidelines for their inclusion in standards. Geneva, Switzerland: International Organization for Standardization, 2014.Search in Google Scholar

11. ISO 31000:2018. Risk management – guidelines. Geneva, Switzerland: International Organization for Standardization, 2018.Search in Google Scholar

12. IEC 31010:2009. Risk management – risk assessment techniques. Geneva, Switzerland: International Organization for Standardization, 2009.Search in Google Scholar

13. ISO/TS 22367:2008. Medical laboratories – reduction of error through risk management and continual improvement. Geneva, Switzerland: International Organization for Standardization, 2008.Search in Google Scholar

14. CLSI document EP23-A. Laboratory quality control based on risk management; approved guideline. Wayne, PA: Clinical and Laboratory Standards Institute, 2012.Search in Google Scholar

15. CLSI document EP18-A2. Risk management techniques to identify and control laboratory error sources; approved guideline, 2nd ed. Wayne, PA: Clinical and Laboratory Standards Institute, 2009.Search in Google Scholar

16. Lu Y, Teng F, Zhou J, Wen A, Bi Y. Failure mode and effect analysis in blood transfusion: a proactive tool to reduce risks. Transfusion 2013;53:3080–7.10.1111/trf.12174Search in Google Scholar PubMed

17. Romero A, Gómez-Salgado J, Romero-Arana A, Ruiz-Frutos C. Utilization of a health care failure mode and effects analysis to identify error. Biochem Med (Zagreb) 2018;28:020713.10.11613/BM.2018.020713Search in Google Scholar PubMed PubMed Central

18. Joint Commission on Accreditation of Healthcare Organizations. An introduction to FMEA. Using failure mode and effects analysis to meet JCAHO’s proactive risk assessment requirement. Failure Modes and Effect Analysis. Health Devices 2002;31:223–6.Search in Google Scholar

19. Ricos C, Biosca C, Ibarz M, Minchinela J, Llopis M, Perich C, et al. Quality indicators and specifications for strategic and support processes in laboratory medicine. Clin Chem Lab Med 2008;46:1189–94.10.1515/CCLM.2008.225Search in Google Scholar PubMed

20. Llopis MA, Trujillo G, Llovet MI, Tarrés E, Ibarz M, Biosca C, et al. Quality indicators and specifications for key, analytical-extra analytical process in the clinical laboratory. Five years’ experience using the six sigma concept. Clin Chem Lab Med 2011;49:463–70.10.1515/CCLM.2011.067Search in Google Scholar PubMed

21. Shcolnik W, de Oliveira CA, Sá de São José A, de Oliveira Galoro CA, Plebani M, Burnett D. Brazilian laboratory indicators program. Clin Chem Lab Med 2012;50:1923–34.10.1515/cclm-2012-0357Search in Google Scholar PubMed

22. Meier FA, Souers RJ, Howanitz PJ, Tworek JA, Perrotta PL, Nakhleh RE, et al. Seven Q-Tracks monitors of laboratory quality drive general performance improvement: experience from the College of American Pathologists Q-Tracks Program 1999–2011. Arch Pathol Lab Med 2015;139:762–75.10.5858/arpa.2014-0090-CPSearch in Google Scholar PubMed

23. Plebani M, Sciacovelli L, Lippi G. Quality indicators for laboratory diagnostics: consensus is needed. Ann Clin Biochem 2011;48:479.10.1258/acb.2011.011088Search in Google Scholar PubMed

24. Sciacovelli L, Plebani M. The IFCC Working Group on laboratory errors and patient safety. Clin Chim Acta 2009;404:79–85.10.1016/j.cca.2009.03.025Search in Google Scholar PubMed

25. Sciacovelli L, O’Kane M, Skaik YA, Caciagli P, Pellegrini C, Da Rin G, et al. IFCC WG-LEPS. Quality indicators in laboratory medicine: from theory to practice. Preliminary data from the IFCC Working Group Project “Laboratory Errors and Patient Safety”. Clin Chem Lab Med 2011;49:835–44.10.1515/CCLM.2011.128Search in Google Scholar

26. Plebani M, Astion ML, Barth JH, Chen W, de Oliveira Galoro CA, Escuer MI, et al. Harmonization of quality indicators in laboratory medicine. A preliminary consensus. Clin Chem Lab Med 2014;52:951–8.10.1515/cclm-2014-0142Search in Google Scholar PubMed

27. Sciacovelli L, Lippi G, Sumarac Z, West J, Garcia Del Pino Castro I, Furtado Vieira K, et al. Working Group “Laboratory Errors and Patient Safety” of International Federation of Clinical Chemistry and Laboratory Medicine (IFCC). Quality Indicators in Laboratory Medicine: the status of the progress of IFCC Working Group “Laboratory Errors and Patient Safety” project. Clin Chem Lab Med 2017;55:348–57.10.1515/cclm-2016-0929Search in Google Scholar PubMed

28. International Federation of Clinical Chemistry and Laboratory Medicine. Working Group “Laboratory Errors and Patient Safety, Model of Quality Indicators. Available at: http://www.ifcc-mqi.com/MqiWeb/resources/doc/Quality_Indicators_Key_Processes.pdf. Accessed: 5 Jan 2019.Search in Google Scholar

29. Plebani M, O’Kane M, Vermeersch P, Cadamuro J, Ooostherius H, Sciacovelli L, et al. The use of extra-analytical phase quality indicators by clinical laboratories: the results of an international survey. Clin Chem Lab Med 2016;54:e315–7.10.1515/cclm-2016-0770Search in Google Scholar PubMed

30. Flegar Mestric Z, Perkov S, Radeljak A, Paro MM. Risk analysis of the preanalytical process based on quality indicators data. Clin Chem Lab Med 2017;55:368–77.10.1515/cclm-2016-0235Search in Google Scholar PubMed

31. Badrick T, Gay S, Mackay M, Sikaris K. The key incident monitoring and management system – history and role in quality improvement. Clin Chem Lab Med 2018;56:264–72.10.1515/cclm-2017-0219Search in Google Scholar PubMed

32. Zaninotto M, Tasinato A, Padoan A, Vecchiato G, Pinato A, Sciacovelli L, et al. Effects of sample transportation on commonly requested laboratory tests. Clin Chem Lab Med 2012;50:1755–60.10.1515/cclm-2012-0150Search in Google Scholar PubMed

33. Lippi G, Salvagno GL, Montagnana M, Guidi GC. Preparation of a quality sample: effect of centrifugation time on stat clinical chemistry testing. Lab Med 2007;38:172–6.10.1309/D8TJCARUW575CXYHSearch in Google Scholar

34. Lippi G, Salvagno GL, Danese E, Lima-Oliveira G, Brocco G, Guidi GC. Inversion of lithium heparin gel tubes after centrifugation is a significant source of bias in clinical chemistry testing. Clin Chim Acta 2014;436:183.10.1016/j.cca.2014.05.028Search in Google Scholar PubMed

35. Lippi G, Banfi G, Churcha S, Cornesa M, De Carli G, Grankvist K, et al. Preanalytical quality improvement. In pursuit of harmony, on behalf of European Federation for Clinical Chemistry and Laboratory Medicine (EFLM Working group for Preanalytical Phase (WG-PRE). Clin Chem Lab Med 2015;53:357–70.10.1515/cclm-2014-1051Search in Google Scholar PubMed

36. Giménez-Marín A, Rivas-Ruiz F, del Mar Pérez-Hidalgo M, Molina-Mendoza P. Pre-analytical errors management in the clinical laboratory: a five-year study. Biochem Med (Zagreb) 2014;24:248–57.10.11613/BM.2014.027Search in Google Scholar PubMed PubMed Central

37. Bonini P, Plebani M, Ceriotti F, Rubboli F. Errors in laboratory medicine. Clin Chem 2002;48:691–8.10.1093/clinchem/48.5.691Search in Google Scholar

38. Lippi G, Blanckaert N, Bonini P, Green S, Kitchen S, Palicka V, et al. Haemolysis: an overview of the leading cause of unsuitable specimens in clinical laboratories. Clin Chem Lab Med 2008;46:764–72.10.1515/CCLM.2008.170Search in Google Scholar PubMed

39. Romero A, Cobos A, Gómez J, Muñoz M. Role of training activities for the reduction of pre-analytical errors in laboratory samples from primary care. Clin Chim Acta 2012;413: 166–9.10.1016/j.cca.2011.09.017Search in Google Scholar PubMed

40. Simundic AM, Cornes M, Grankvist K, Lippi G, Nybo M, Kovalevskaya S, et al. Survey of national guidelines, education and training on phlebotomy in 28 European countries: an original report by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group for the Preanalytical Phase (WG-PA). Clin Chem Lab 2013;51:1585–93.10.1515/cclm-2013-0283Search in Google Scholar PubMed

41. Lippi G, Sciacovelli L, Simundic AM, Plebani M. Innovative software for recording preanalytical errors in accord with the IFCC quality indicators. Clin Chem Lab Med 2017;55:e51–3.10.1515/cclm-2016-1138Search in Google Scholar PubMed

42. Aita A, Sciacovelli L, Plebani M. Extra-analytical quality indicators-where to now? Clin Chem Lab Med 2019;57:127–33.10.1515/cclm-2017-0964Search in Google Scholar PubMed

43. Potts HW, Anderson JE, Colligan L, Leach P, Davis S, Berman J. Assessing the validity of prospective hazard analysis methods: a comparison of two techniques. BMC Health Serv Res 2014;14:41.10.1186/1472-6963-14-41Search in Google Scholar PubMed PubMed Central

44. Shebl NA, Franklin BD, Barber N. Failure mode and effects analysis outputs: are they valid? BMC Health Serv Res 2012;12:150.10.1186/1472-6963-12-150Search in Google Scholar PubMed PubMed Central

45. Janssens PM. Practical, transparent prospective risk analysis for the clinical laboratory. Ann Clin Biochem 2014;51:695–704.10.1177/0004563214521160Search in Google Scholar PubMed

46. Plebani M. Quality in laboratory medicine: an unfinished journey. J Lab Precis Med 2017;2:63.10.21037/jlpm.2017.08.04Search in Google Scholar

47. Lippi G, Plebani M. A Six-Sigma approach for comparing diagnostic errors in healthcare – where does laboratory medicine stand? Ann Transl Med 2018;6:180.10.21037/atm.2018.04.02Search in Google Scholar PubMed PubMed Central

48. Aita A, Sciacovelli L, Plebani M. Laboratory-related errors: you cannot manage what you don’t measure. You manage what you know and measure. Diagnosis (Berl) 2017;4:193–5.10.1515/dx-2017-0038Search in Google Scholar PubMed

Received: 2019-01-06
Accepted: 2019-04-08
Published Online: 2019-05-03
Published in Print: 2019-09-25

©2019 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Blood biomarkers in neurology: “a call to arms” for laboratory professionals
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  24. Next-generation reference intervals for pediatric hematology
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  26. Preliminary evaluation of a new flow cytometry method for the routine hematology workflow
  27. Diabetes
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  29. Infectious Diseases
  30. Utility of procalcitonin for differentiating cryptogenic organising pneumonia from community-acquired pneumonia
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  32. Letters to the Editor
  33. Evaluation of reference change values for a hs-cTnI immunoassay using both plasma samples of healthy subjects and patients and quality control samples
  34. Outlier removal methods for skewed data: impact on age-specific high-sensitive cardiac troponin T 99th percentiles
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  37. Erroneous thyroid and steroid hormones profile due to anti-streptavidin antibodies
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https://doi.org/10.1515/cclm-2019-0019
Keywords for this article
continual improvement; FMEA; pre-analytical process; public health laboratory; quality indicators; risk management

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Blood biomarkers in neurology: “a call to arms” for laboratory professionals
  4. Reviews
  5. Diagnostic accuracy of glycated hemoglobin for gestational diabetes mellitus: a systematic review and meta-analysis
  6. Laboratory medicine: health evaluation in elite athletes
  7. Prostate cancer screening: guidelines review and laboratory issues
  8. Opinion Papers
  9. Extra-analytical sources of uncertainty: which ones really matter?
  10. Benefits and harms of wellness initiatives
  11. Genetics and Molecular Diagnostics
  12. Analytical and clinical validation of a novel amplicon-based NGS assay for the evaluation of circulating tumor DNA in metastatic colorectal cancer patients
  13. General Clinical Chemistry and Laboratory Medicine
  14. Pre-analytical practices for routine coagulation tests in European laboratories. A collaborative study from the European Organisation for External Quality Assurance Providers in Laboratory Medicine (EQALM)
  15. Preanalytical robustness of blood collection tubes with RNA stabilizers
  16. Continual improvement of the pre-analytical process in a public health laboratory with quality indicators-based risk management
  17. Comparison of six commercial serum exosome isolation methods suitable for clinical laboratories. Effect in cytokine analysis
  18. A multicenter study to evaluate harmonization of assays for N-terminal propeptide of type I procollagen (PINP): a report from the IFCC-IOF Joint Committee for Bone Metabolism
  19. Correlations between serum and CSF pNfH levels in ALS, FTD and controls: a comparison of three analytical approaches
  20. Dynamics of extracellular matrix proteins in cerebrospinal fluid and serum and their relation to clinical outcome in human traumatic brain injury
  21. Free light chains in the cerebrospinal fluid. Comparison of different methods to determine intrathecal synthesis
  22. Reference Values and Biological Variations
  23. Reference interval by the indirect approach of serum thyrotropin (TSH) in a Mediterranean adult population and the association with age and gender
  24. Next-generation reference intervals for pediatric hematology
  25. Hematology and Coagulation
  26. Preliminary evaluation of a new flow cytometry method for the routine hematology workflow
  27. Diabetes
  28. Trueness assessment of HbA1c routine assays: are processed EQA materials up to the job?
  29. Infectious Diseases
  30. Utility of procalcitonin for differentiating cryptogenic organising pneumonia from community-acquired pneumonia
  31. A high C-reactive protein/procalcitonin ratio predicts Mycoplasma pneumoniae infection
  32. Letters to the Editor
  33. Evaluation of reference change values for a hs-cTnI immunoassay using both plasma samples of healthy subjects and patients and quality control samples
  34. Outlier removal methods for skewed data: impact on age-specific high-sensitive cardiac troponin T 99th percentiles
  35. Comparison of precision and operational performances across six immunochemistry analyzers
  36. Evaluation of the possible interference of abiraterone therapy on testosterone immunoassay
  37. Erroneous thyroid and steroid hormones profile due to anti-streptavidin antibodies
  38. Reference values for 24,25-dihydroxyvitamin D and the 25-hydroxyvitamin D/24,25-dihydroxyvitamin D ratio
  39. Pre-analytical error in a hematology laboratory: an avoidable cause of compromised quality in reporting
  40. Stability of tubular damage markers epidermal growth factor and heparin-binding EGF-like growth factor in urine
  41. Blood from heparin tubes is an acceptable alternative to assess hematocrit determination
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