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Clinical Chemistry and Laboratory Medicine (CCLM)

Published in Association with the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM)

Editor-in-Chief: Plebani, Mario

Ed. by Gillery, Philippe / Lackner, Karl J. / Lippi, Giuseppe / Melichar, Bohuslav / Payne, Deborah A. / Schlattmann, Peter / Tate, Jillian R.

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IMPACT FACTOR 2016: 3.432

CiteScore 2016: 2.21

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Source Normalized Impact per Paper (SNIP) 2016: 1.112

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Volume 56, Issue 2


The key incident monitoring and management system – history and role in quality improvement

Tony Badrick / Stephanie Gay / Mark Mackay / Ken Sikaris
Published Online: 2017-08-03 | DOI: https://doi.org/10.1515/cclm-2017-0219



The determination of reliable, practical Quality Indicators (QIs) from presentation of the patient with a pathology request form through to the clinician receiving the report (the Total Testing Process or TTP) is a key step in identifying areas where improvement is necessary in laboratories.


The Australasian QIs programme Key Incident Monitoring and Management System (KIMMS) began in 2008. It records incidents (process defects) and episodes (occasions at which incidents may occur) to calculate incident rates. KIMMS also uses the Failure Mode Effects Analysis (FMEA) to assign quantified risk to each incident type. The system defines risk as incident frequency multiplied by both a harm rating (on a 1–10 scale) and detection difficulty score (also a 1–10 scale).


Between 2008 and 2016, laboratories participating rose from 22 to 69. Episodes rose from 13.2 to 43.4 million; incidents rose from 114,082 to 756,432. We attribute the rise in incident rate from 0.86% to 1.75% to increased monitoring. Haemolysis shows the highest incidence (22.6% of total incidents) and the highest risk (26.68% of total risk). “Sample is suspected to be from the wrong patient” has the second lowest frequency, but receives the highest harm rating (10/10) and detection difficulty score (10/10), so it is calculated to be the 8th highest risk (2.92%). Similarly, retracted (incorrect) reports QI has the 10th highest frequency (3.9%) but the harm/difficulty calculation confers the second highest risk (11.17%).


TTP incident rates are generally low (less than 2% of observed episodes), however, incident risks, their frequencies multiplied by both ratings of harm and discovery difficulty scores, concentrate improvement attention and resources on the monitored incident types most important to manage.

Keywords: Failure Mode Effects Analysis (FMEA); post-analytical error; pre-analytical error; Quality Indicators


  • 1.

    Plebani M, Carraro P. Mistakes in a stat laboratory: types and frequency. Clin Chem 1997;43:1348–51.Google Scholar

  • 2.

    Kristensen GB, Aakre KM, Sandberg S. How to conduct External Quality Assessment Schemes for the pre-analytical phase? Biochem Med 2014;24:114–22.Google Scholar

  • 3.

    Khoury M, Burnett L, Mackay M. Error rate in Australian chemical pathology laboratories. Med J Aust 1996;165:128–30.PubMedGoogle Scholar

  • 4.

    Mainz J. Defining and classifying clinical indicators for quality improvement. Int J Qual Health Care 2003;15:523–30.CrossrefPubMedGoogle Scholar

  • 5.

    Naklhleh RE, Souers RJ, Bashleben CP, Talbert ML, Karcher DS, Meier FA, et al. Fiftenn years’ experience of a College of American Pathologists program for continuous quality improvement. Arch Pathol Lab Med 2014;138:1150–5.CrossrefPubMedGoogle Scholar

  • 6.

    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.Web of SciencePubMedCrossrefGoogle Scholar

  • 7.

    Shcolnik W, de Oliveira CA, de São José AS, de Oliveira Galoro CA, Plebani M, Burnett D. Brazilian laboratory indicators program. Clin Chem Lab Med 2012;50:1923–34.Web of SciencePubMedGoogle Scholar

  • 8.

    Kirchner MJ, Funes VA, Adzet CB, Clar MV, Escuer MI, Girona JM, et al. Quality indicators and specifications for key processes in clinical laboratories: a preliminary experience. Clin Chem Lab Med 2007;45:672–7.Web of SciencePubMedGoogle Scholar

  • 9.

    Barth JH. Selecting clinical quality indicators for laboratory medicine. Ann Clin Biochem 2012;49:257–61.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 10.

    Barth JH. Clinical quality indicators in laboratory medicine. Ann Clin Biochem 2012;49:9–16.CrossrefWeb of SciencePubMedGoogle Scholar

  • 11.

    Simundic AM, Topic E. Quality indicators. Biochem Med 2008;18:311–9.Google Scholar

  • 12.

    Plebani M, Sciacovelli L, Lippi G. Quality indicators for laboratory diagnostics: consensus is needed. Ann Clin Biochem 2011;48:479.PubMedWeb of ScienceCrossrefGoogle Scholar

  • 13.

    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.Google Scholar

  • 14.

    Green SF. The cost of poor blood specimen quality and errors in preanalytical processes. Clin Biochem 2013;46:1175–9.CrossrefWeb of SciencePubMedGoogle Scholar

  • 15.

    Institute for Health Improvement. Risk Priority Number. http://www.ihi.org/resources/Pages/Measures/RiskPriorityNumberfromFailureModesandEffectsAnalysis.aspx. Accessed 7 April 2017.

  • 16.

    Plebani M, O’Kane M, Vermeersch P, Cadamuro J, Oosterhuis W, 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.Web of ScienceGoogle Scholar

  • 17.

    The Institute of Medicine. Improving diagnosis in healthcare. Washington: National Academies of Sciences, Engineering and Medicine, 2015.

About the article

Received: 2017-03-12

Accepted: 2017-06-29

Published Online: 2017-08-03

Published in Print: 2018-01-26

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

Research funding: None declared.

Employment or leadership: None declared.

Honorarium: None declared.

Competing interests: The funding organisation(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.

Citation Information: Clinical Chemistry and Laboratory Medicine (CCLM), Volume 56, Issue 2, Pages 264–272, ISSN (Online) 1437-4331, ISSN (Print) 1434-6621, DOI: https://doi.org/10.1515/cclm-2017-0219.

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