Impact of reference change value (RCV) based autoverification on turnaround time and physician satisfaction

Fernández-Grande, Esther; Valera-Rodriguez, Carolina; Sáenz-Mateos, Luis; Sastre-Gómez, Amparo; García-Chico, Pilar; Palomino-Muñoz, T.J.

doi:10.11613/bm.2017.037

Cited by 16 publications

(12 citation statements)

References 21 publications

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“…Therefore, it is important to define exactly how the criteria for delta check rule will be defined. Participants of this survey answered that criteria used for delta check were usually obtained by calculation of RCV, and this is consistent with literature data (2,14,21).…”

Section: Discussionsupporting

confidence: 85%

General position of Croatian medical biochemistry laboratories on autovalidation

Rimac

Jokić²,

Podolar³

et al. 2020

Biochem. med. (Online)

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Introduction: Autovalidation (AV) is an algorithm based on predefined rules designed, among others, to automate and standardize the postanalytical phase of laboratory work. The aim of this study was to examine the overall opinion of Croatian medical biochemistry laboratories regarding various aspects of AV. Material and methods: This retrospective study is an analysis of the responses of a survey about AV comprised of 18 questions, as part of Module 10 (“Postanalytical phase of laboratory testing”) of national External Quality Assessment program, administered by the Croatian Centre for Quality Assessment in Laboratory Medicine. Results were reported as percentages of total number of participants in survey or as proportions of observed data if the overall number of data was <100. Results: 121 laboratories responded to the survey, of which 76% do not use AV, while 11% of laboratories use AV in routine laboratory work. 16/29 laboratories implemented semi-automated AV for general biochemistry (7/29), haematology (5/29), and coagulation (4/29) tests. Analytical measurement ranges, critical values, flags from analysers, interference indices and delta check were the most commonly used rules in the algorithm. 12/29 laboratories performed validation of AV with less than 500 samples (8/29). 7/13 laboratories report the percentage of AV being 20-50%, while 10/13 answered that introduction of AV significantly reduced turnaround time (TAT) (for 20 - 25%), especially for biochemistry tests. Conclusions: Despite of its numerous benefits (i.e. shorter TAT, less manual validation, standardization of the postanalytical phase), only a small number of Croatian laboratories use AV.

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Section: Discussionsupporting

confidence: 85%

General position of Croatian medical biochemistry laboratories on autovalidation

Rimac

Jokić²,

Podolar³

et al. 2020

Biochem. med. (Online)

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“…Therefore, we suggest that the best AV rules should be established by disease groups. Furthermore, since we wrote the algorithm of the AV process directly into LIS without an intermediate software, the test results could be released directly to the physicians as soon as they passed the AV process.…”

Section: Discussionmentioning

confidence: 99%

Establishing and validating of an laboratory information system‐based auto‐verification system for biochemical test results in cancer patients

Yan

Zhang

et al. 2019

Clinical Laboratory Analysis

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BackgroundTo establish and validate an laboratory information system (LIS)‐based auto‐verification (AV) system by using large amounts of biochemical test results in cancer patients.MethodsAn algorithm of the AV process was designed for pre‐analysis, analysis, and post‐analysis. The limit range check was adjusted three times, while the delta check criteria were first replaced by the same patients’ historical extremum results. AV rules of 51 biochemical test items were tested by using data of 121 123 samples (6 177 273 tests) in 2016 that were manually reviewed through the simulative i‐Vertification software of Roche. The improved and optimal AV rules were programed into our LIS and validated by using 140 113 clinical specimens in 2018.ResultsThe AV passing rate for samples tested in our laboratory increased from 15.57% to the current overall passing rate of 49.70%. The passing rate of each item for rule 3 was between 71.16% and 99.91%. Different cancer groups had different passing rate, while the disease group of liver, gallbladder, and pancreas always had the lowest passing rate. A total of 9420 reports (6.72%) were not verified by AV but could be verified by MV in 2018, while there were no reports that were verified by AV but not by MV. The TAT of March 2018 decreased with increase in sample size compared with the same time in 2017.ConclusionWe have firstly established an LIS‐based AV system and implemented it in actual clinical care for cancer patients.

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“…The concept of reference change values (RCVs) based on biological variation is widely used for interpreting changes in serial laboratory results; it has been applied to clinical laboratory tests such as delta check and auto-verification [1,[11][12][13][14][15]. However, RCV still has limitations as many of the biochemical analytes have high intra-individual variation [13,14].…”

Section: Introductionmentioning

confidence: 99%

Clinical Application of Overlapping Confidence Intervals for Monitoring Changes in Serial Clinical Chemistry Test Results

Cho

Seo

2020

Ann Lab Med

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Background: Interpretation of changes in serial laboratory results is necessary for both clinicians and laboratories; however, setting decision limits is not easy. Although the reference change value (RCV) has been widely used for auto-verification, it has limitations in clinical settings. We introduce the concept of overlapping confidence intervals (CIs) to determine whether the changes are statistically significant in clinical chemistry laboratory test results.Methods: In total, 1,202,096 paired results for 33 analytes routinely tested in our clinical chemistry laboratory were analyzed. The distributions of delta% absolute values and cutoff values for certain percentiles were calculated. The CIs for each analyte were set based on biological variation, and data were analyzed at various confidence levels. Additionally, we analyzed the data using RCVs and compared their clinical utility.Results: Most analytes had low indexes of individuality with large inter-individual variability. The 97.5th percentile cut-offs for each analyte were much larger than conventional RCVs. The percentages of results exceeding RCV95% and RCV99% corresponded to those with no overlap at the 83.4% and 93.2% confidence levels, respectively.Conclusions: The use of overlapping CIs in serial clinical chemistry test results can overcome the limitations of existing RCVs and replace them, especially for analytes with large intra-individual variation.

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Impact of reference change value (RCV) based autoverification on turnaround time and physician satisfaction

Cited by 16 publications

References 21 publications

General position of Croatian medical biochemistry laboratories on autovalidation

General position of Croatian medical biochemistry laboratories on autovalidation

Establishing and validating of an laboratory information system‐based auto‐verification system for biochemical test results in cancer patients

Clinical Application of Overlapping Confidence Intervals for Monitoring Changes in Serial Clinical Chemistry Test Results

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