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

Evaluation of 18 quality indicators from the external quality assurance preanalytical programme of the Spanish Society of Laboratory Medicine (SEQCML)

Objectives

Most errors in laboratory medicine occur in the pre- and post-analytical phases of the total testing process (TTP). In 2014, the Spanish Society of Laboratory Medicine (SEQC^ML) started the current Preanalytical Phase EQA Programme, with the objective of providing a tool for the improvement of the preanalytical phase. The aim of this study was to review the evolution of quality indicators (QI) and the comparability of established performance specifications (PS) with other EQA programmes.

Methods

In the SEQC^ML programme, participants were asked to register rejections of the main specimens and the causes for rejections. Data collected from 2014 to 2017, and then reviewed biennially (2018-2019), was used to calculate the percentiles; p25, p50, p75, and p90 for every round, and their means were set as PS. These PS were compared with the results of other programmes.

Results

The evolution of QI results for 2018-2019 period showed general maintenance or improvement, e.g., a significant decrease in the number of serum samples with a haemolytic index ≥0.5 g/L, except for EDTA and citrate samples handle, maybe for an improvement in detection. The comparison with PS for the QI of the IFCC Working Group "Laboratory Errors and Patient Safety" and the Key Incident Management and Monitoring System (KIMMS) programme of the RCPA showed comparable results, supporting the validity of the established specifications.

Conclusions

The PS obtained are a helpful tool for benchmarking and to identify processes of the preanalytical phase whose improvement should be set as a priority.

External quality assessment of serum indices: Spanish SEQC-ML program

OBJECTIVES

Serum indices included in clinical chemistry instruments are widely used by laboratories to assess the quality of samples. Instruments that report quantitative results allow an evaluation of their diagnostic performance in a similar way to other biochemical tests. The Spanish Society of Laboratory Medicine (SEQC-ML) launched a monthly External Quality program of serum indices in 2018 using three lyophilized materials of simultaneous annual distribution. We present the results of the first three years of the program.

METHODS

The use of four different quality control materials with different concentrations in three alternate months allows an annual evaluation of the participant's accuracy. Assigned values are established by consensus among homogeneous groups, considering necessary at least 10 participants for a comparison at instrument level. The average percentage difference results per instrument allow the assessment of bias among groups.

RESULTS

The imprecision of the three indices ranges between 3 and 9%, with no major differences among instruments. Significant differences were observed in all indices among instruments with more than 10 participants (Roche Cobas, Abbott Architect, Abbott Alinity and Siemens Advia). The 90th percentile of the distribution of percentage differences was used as the analytical performance specification (APS). An improvement in performance was observed in the first three years of the program, probably due to the learning curve effect. In 2020, APS of 7.8, 12.2 and 9.7% were proposed for hemolytic, icteric and lipemic indices, respectively.

CONCLUSIONS

Serum indices have a great impact on the quality and the reliability of laboratory test results. Participation in proficiency testing programs for serum indices is helpful to encourage harmonization among providers and laboratories.

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

Introduction

The Royal College of Pathologists of Australasia Quality Assurance Programs (RCPAQAP) Key Incident Monitoring and Management Systems (KIMMS) program has found that some existing Quality Indicators are too broad or not well defined. The risk matrix in use does not allow changes in incident Detection or Probability. In 2020, a review was performed: what issues should KIMMS include as Key Incidents and how could risk measurement be improved?

Materials and methods

Twenty-seven networked and stand-alone laboratories enrolled in KIMMS during 2020 were surveyed on 45 current and new indicators of risk in the total testing process. They were asked which indicators they considered were significant in causing patient harm. Existing risk matrices in use by members of the KIMMS Advisory Committee laboratories were reviewed regarding their size or structure (3x3 or 5x5) and the descriptions of consequences and probability.

Results

Thirteen participants indicated 21 indicators should be monitored, and the KIMMS Advisory committee added a further 13 (11 from the remaining 24 and 2 new). Of the five risk matrices reviewed, all consistently used a 5x5 matrix to estimate Consequences vs Probability of harm. The KIMMS advisory committee added a third parameter to the calculation of Risk, Detectability.

Conclusion

All 34 pre- and post- indicators should be monitored, covering all aspects of the total testing cycle other than analytical. The risk measurement can be improved by introducing a 5x5 risk matrix to evaluate harm (consequences x probability) and then evaluating risk by adding detectability; risk equals harm x detectability.

Gamma-Glutamyl Transferase (GGT) Is the Leading External Quality Assurance Predictor of ISO15189 Compliance for Pathology Laboratories

Pathology results are central to modern medical practice, informing diagnosis and patient management. To ensure high standards from pathology laboratories, regulators require compliance with international and local standards. In Australia, the monitoring and regulation of medical laboratories are achieved by conformance to ISO15189-National Pathology Accreditation Advisory Council standards, as assessed by the National Association of Testing Authorities (NATA), and an external quality assurance (EQA) assessment via the Royal College of Pathologists of Australasia Quality Assurance Program (RCPAQAP). While effective individually, integration of data collected by NATA and EQA testing promises advantages for the early detection of technical or management problems in the laboratory, and enhanced ongoing quality assessment. Random forest (RF) machine learning (ML) previously identified gamma-glutamyl transferase (GGT) as a leading predictor of NATA compliance condition reporting. In addition to further RF investigations, this study also deployed single decision trees and support vector machines (SVM) models that included creatinine, electrolytes and liver function test (LFT) EQA results. Across all analyses, GGT was consistently the top-ranked predictor variable, validating previous observations from Australian laboratories. SVM revealed broad patterns of predictive EQA marker interactions with NATA outcomes, and the distribution of GGT relative deviation suggested patterns by which to identify other strong EQA predictors of NATA outcomes. An integrated model of pathology quality assessment was successfully developed, via the prediction of NATA outcomes by EQA results. GGT consistently ranked as the best predictor variable, identified by combining recursive partitioning and SVM ML strategies.