Biochemia Medica, Vol. 30 No. 2, 2020.
Original scientific paper
https://doi.org/10.11613/BM.2020.020704
Changes in error rates in the Australian key incident monitoring and management system program
Stephanie Gay
; Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP), Key Incident Monitoring and Management System program (KIMMS), Sydney, Australia
Tony Badrick
; Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP), Key Incident Monitoring and Management System program (KIMMS), Sydney, Australia
Abstract
Introduction: The Key incident monitoring and management system program (KIMMS) program collects data for 19 quality indicators (QIs) from
Australian medical laboratories. This paper aims to review the data submitted to see whether the number of errors with a higher risk priority number
(RPN) have been reduced in preference to those with a lower RPN, and to calculate the cost of these errors.
Materials and methods: Data for QIs from 60 laboratories collected through the KIMMS program from 2015 until 2018 were retrospectively reviewed.
The results for each QI were averaged for the four-year average and coefficient of variation. To review the changes in QI frequency, the yearly
averages for 2015 and 2018 were compared. By dividing the total RPN by 4 and multiplying that number by the cost of recollection of 30 AUD, it was
possible to assign the risk cost of these errors.
Results: The analysis showed a drop in the overall frequency of incidents (6.5%), but a larger drop in risk (9.4%) over the period investigated. Recollections
per year in Australia cost the healthcare industry 27 million AUD. If the RPN data is used, this cost increases to 66 million AUD per year.
Conclusions: Errors with a higher RPN have fallen more than those with lower RPN. The data shows that the errors associated with phlebotomy are
the ones that have most improved. Further improvements require a better understanding of the root cause of the errors and to achieve this, work is
required in the collection of the data to establish best-practice guidelines.
Keywords
preanalytical errors; postanalytical errors; preanalytical risk; postanalytical risk
Hrčak ID:
238907
URI
Publication date:
15.6.2020.
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