Home The key incident monitoring and management system – history and role in quality improvement
Article
Licensed
Unlicensed Requires Authentication

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

  • Tony Badrick EMAIL logo , Stephanie Gay , Mark Mackay and Ken Sikaris
Published/Copyright: August 3, 2017
Become an author with De Gruyter Brill
Submit Manuscript Author Information
Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 56 Issue 2

Abstract

Background:

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.

Methods:

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).

Results:

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%).

Conclusions:

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. 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 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.

References

1. Plebani M, Carraro P. Mistakes in a stat laboratory: types and frequency. Clin Chem 1997;43:1348–51.10.1093/clinchem/43.8.1348Search in Google Scholar

2. Kristensen GB, Aakre KM, Sandberg S. How to conduct External Quality Assessment Schemes for the pre-analytical phase? Biochem Med 2014;24:114–22.10.11613/BM.2014.013Search in Google Scholar PubMed PubMed Central

3. Khoury M, Burnett L, Mackay M. Error rate in Australian chemical pathology laboratories. Med J Aust 1996;165:128–30.10.5694/j.1326-5377.1996.tb124883.xSearch in Google Scholar

4. Mainz J. Defining and classifying clinical indicators for quality improvement. Int J Qual Health Care 2003;15:523–30.10.1093/intqhc/mzg081Search in Google Scholar PubMed

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;138:1150–5.10.5858/arpa.2014-0148-OASearch in Google Scholar PubMed

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;139:762–75.10.5858/arpa.2014-0090-CPSearch in Google Scholar PubMed

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;50:1923–34.10.1515/cclm-2012-0357Search in Google Scholar PubMed

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.Search in Google Scholar

9. Barth JH. Selecting clinical quality indicators for laboratory medicine. Ann Clin Biochem 2012;49:257–61.10.1258/acb.2011.011159Search in Google Scholar PubMed

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

11. Simundic AM, Topic E. Quality indicators. Biochem Med 2008;18:311–9.10.11613/BM.2008.027Search in Google Scholar

12. 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

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;49:835–44.10.1515/CCLM.2011.128Search in Google Scholar

14. Green SF. The cost of poor blood specimen quality and errors in preanalytical processes. Clin Biochem 2013;46:1175–9.10.1016/j.clinbiochem.2013.06.001Search in Google Scholar PubMed

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

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:e315–7.10.1515/cclm-2016-0770Search in Google Scholar PubMed

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

Received: 2017-03-12
Accepted: 2017-06-29
Published Online: 2017-08-03
Published in Print: 2018-01-26

©2018 Walter de Gruyter GmbH, Berlin/Boston

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Need for better PTH assays for clinical research and patient treatment
  4. Reviews
  5. Liquid biopsy in ovarian cancer: recent advances on circulating tumor cells and circulating tumor DNA
  6. Hair testing of GHB: an everlasting issue in forensic toxicology
  7. Opinion Paper
  8. The use of error and uncertainty methods in the medical laboratory
  9. Genetics and Molecular Diagnostics
  10. Results of the first external quality assessment scheme (EQA) for isolation and analysis of circulating tumour DNA (ctDNA)
  11. The importance of biochemical and genetic findings in the diagnosis of atypical Norrie disease
  12. General Clinical Chemistry and Laboratory Medicine
  13. Various glycolysis inhibitor-containing tubes for glucose measurement cannot be used interchangeably due to clinically unacceptable biases between them
  14. Measurement uncertainty of γ-glutamyltransferase (GGT) in human serum by four approaches using different quality assessment data
  15. Oxidation of PTH: in vivo feature or effect of preanalytical conditions?
  16. A comparison between high resolution serum protein electrophoresis and screening immunofixation for the detection of monoclonal gammopathies in serum
  17. The key incident monitoring and management system – history and role in quality improvement
  18. Is it necessary for all samples to quantify 25OHD2 and 25OHD3 using LC-MS/MS in clinical practice?
  19. Contamination of dried blood spots – an underestimated risk in newborn screening
  20. Comparative study of the diagnostic and prognostic value of antibodies against chimeric citrullinated synthetic peptides and CCP3/CCP3.1 assays
  21. Development and validation of a multivariable prediction rule for detecting a severe acquired ADAMTS13 activity deficiency in patients with thrombotic microangiopathies
  22. Use of the sFlt-1/PlGF ratio to rule out preeclampsia requiring delivery in women with suspected disease. Is the evidence reproducible?
  23. Evaluation of a new free light chain ELISA assay: bringing coherence with electrophoretic methods
  24. Hematology and Coagulation
  25. The frequency of occurrence of fish-shaped red blood cells in different haematologic disorders
  26. Reference Values and Biological Variations
  27. Pediatric reference intervals for 29 Ortho VITROS 5600 immunoassays using the CALIPER cohort of healthy children and adolescents
  28. Cancer Diagnostics
  29. Prevalence and causes of abnormal PSA recovery
  30. Cardiovascular Diseases
  31. Serum omentin-1 is a novel biomarker for predicting the functional outcome of acute ischemic stroke patients
  32. Letters to the Editor
  33. BD Vacutainer® Barricor tube in the emergency department: reduced hemolysis rates using partial draw tubes with reduced vacuum
  34. The risk of unjustified BRCA testing after the “Angelina Jolie effect”: how can we save (laboratory) medicine from the Internet?
  35. Sweat travels: the issue of sweat chloride transportation
  36. Individual values of antineutrophil cytoplasmic antibodies do not correspond between antigen-specific assays
  37. False negative results caused by erroneous automated result interpretation algorithm on the FilmArray 2.0 instrument
  38. Quantification of 1,25-dihydroxyvitamin D – value of manufacturers’ product information
  39. Interference between ethosuximide and barbiturates in an immunochromatographic method
  40. In vivo interference of Ioversol in serum and urine capillary electrophoresis: an optimized protocol for sample collection
  41. Evaluation of the new Elecsys SCC assay: comparison with the Kryptor SCC assay
  42. Congress Abstracts
  43. 9th National Congress of the Portuguese Society of Clinical Chemistry, Genetics and Laboratory Medicine
  44. ACBI 2017 40TH Annual Conference
https://doi.org/10.1515/cclm-2017-0219
Keywords for this article
Failure Mode Effects Analysis (FMEA); post-analytical error; pre-analytical error; Quality Indicators

Articles in the same Issue

  1. Frontmatter
  2. Editorial
  3. Need for better PTH assays for clinical research and patient treatment
  4. Reviews
  5. Liquid biopsy in ovarian cancer: recent advances on circulating tumor cells and circulating tumor DNA
  6. Hair testing of GHB: an everlasting issue in forensic toxicology
  7. Opinion Paper
  8. The use of error and uncertainty methods in the medical laboratory
  9. Genetics and Molecular Diagnostics
  10. Results of the first external quality assessment scheme (EQA) for isolation and analysis of circulating tumour DNA (ctDNA)
  11. The importance of biochemical and genetic findings in the diagnosis of atypical Norrie disease
  12. General Clinical Chemistry and Laboratory Medicine
  13. Various glycolysis inhibitor-containing tubes for glucose measurement cannot be used interchangeably due to clinically unacceptable biases between them
  14. Measurement uncertainty of γ-glutamyltransferase (GGT) in human serum by four approaches using different quality assessment data
  15. Oxidation of PTH: in vivo feature or effect of preanalytical conditions?
  16. A comparison between high resolution serum protein electrophoresis and screening immunofixation for the detection of monoclonal gammopathies in serum
  17. The key incident monitoring and management system – history and role in quality improvement
  18. Is it necessary for all samples to quantify 25OHD2 and 25OHD3 using LC-MS/MS in clinical practice?
  19. Contamination of dried blood spots – an underestimated risk in newborn screening
  20. Comparative study of the diagnostic and prognostic value of antibodies against chimeric citrullinated synthetic peptides and CCP3/CCP3.1 assays
  21. Development and validation of a multivariable prediction rule for detecting a severe acquired ADAMTS13 activity deficiency in patients with thrombotic microangiopathies
  22. Use of the sFlt-1/PlGF ratio to rule out preeclampsia requiring delivery in women with suspected disease. Is the evidence reproducible?
  23. Evaluation of a new free light chain ELISA assay: bringing coherence with electrophoretic methods
  24. Hematology and Coagulation
  25. The frequency of occurrence of fish-shaped red blood cells in different haematologic disorders
  26. Reference Values and Biological Variations
  27. Pediatric reference intervals for 29 Ortho VITROS 5600 immunoassays using the CALIPER cohort of healthy children and adolescents
  28. Cancer Diagnostics
  29. Prevalence and causes of abnormal PSA recovery
  30. Cardiovascular Diseases
  31. Serum omentin-1 is a novel biomarker for predicting the functional outcome of acute ischemic stroke patients
  32. Letters to the Editor
  33. BD Vacutainer® Barricor tube in the emergency department: reduced hemolysis rates using partial draw tubes with reduced vacuum
  34. The risk of unjustified BRCA testing after the “Angelina Jolie effect”: how can we save (laboratory) medicine from the Internet?
  35. Sweat travels: the issue of sweat chloride transportation
  36. Individual values of antineutrophil cytoplasmic antibodies do not correspond between antigen-specific assays
  37. False negative results caused by erroneous automated result interpretation algorithm on the FilmArray 2.0 instrument
  38. Quantification of 1,25-dihydroxyvitamin D – value of manufacturers’ product information
  39. Interference between ethosuximide and barbiturates in an immunochromatographic method
  40. In vivo interference of Ioversol in serum and urine capillary electrophoresis: an optimized protocol for sample collection
  41. Evaluation of the new Elecsys SCC assay: comparison with the Kryptor SCC assay
  42. Congress Abstracts
  43. 9th National Congress of the Portuguese Society of Clinical Chemistry, Genetics and Laboratory Medicine
  44. ACBI 2017 40TH Annual Conference
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 13.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/cclm-2017-0219/html
Scroll to top button