Literature DB >> 28771429

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

Tony Badrick1, Stephanie Gay2, Mark Mackay2, Ken Sikaris3.   

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.

Entities:  

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

Mesh:

Year:  2018        PMID: 28771429     DOI: 10.1515/cclm-2017-0219

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN: 1434-6621            Impact factor:   3.694


  2 in total

1.  Changes in error rates in the Australian key incident monitoring and management system program.

Authors:  Stephanie Gay; Tony Badrick
Journal:  Biochem Med (Zagreb)       Date:  2020-04-15       Impact factor: 2.313

2.  Review of current incidents and risk calculations used in the Royal College of Australasian Pathologists Key Incident Management and Monitoring Systems - a system that could be used by all Australasian medical laboratories, and easily adapted to worldwide use.

Authors:  Stephanie Gay; Belinda Pope; Tony Badrick; Michael Whiley
Journal:  Biochem Med (Zagreb)       Date:  2021-12-15       Impact factor: 2.313

  2 in total

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