Impact of delta check time intervals on error detection capability
-
Rui Zhen Tan
und
Tze Ping Loh
Abstract
Background
The delta check time interval limit is the maximum time window within which two sequential results of a patient will be evaluated by the delta check rule. The impact of time interval on delta check performance is not well studied.
Methods
De-identified historical laboratory data were extracted from the laboratory information system and divided into children (≤18 years) and adults (>21 years). The relative and absolute differences of the original pair of results from each patient were compared against the delta check limits associated with 90% specificity. The data were then randomly reshuffled to simulate a switched (misidentified) sample scenario. The data were divided into 1-day, 3-day, 7-day, 14-day, 1-month, 3-month, 6-month and 1-year time interval bins. The true positive- and false-positive rates at different intervals were examined.
Results
Overall, 24 biochemical and 20 haematological tests were analysed. For nearly all the analytes, there was no statistical evidence of any difference in the true- or false-positive rates of the delta check rules at different time intervals when compared to the overall data. The only exceptions to this were mean corpuscular volume (using both relative- and absolute-difference delta check) and mean corpuscular haemoglobin (only absolute-difference delta check) in the children population, where the false-positive rates became significantly lower at 1-year interval.
Conclusions
This study showed that there is no optimal delta check time interval. This fills an important evidence gap for future guidance development.
Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Employment or leadership: None declared.
Honorarium: None declared.
Competing interests: The funding organization(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
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Supplementary Material
The online version of this article offers supplementary material (https://doi.org/10.1515/cclm-2019-1004).
©2020 Walter de Gruyter GmbH, Berlin/Boston
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- Frontmatter
- Editorial
- Progress in understanding the use of human chorionic gonadotropin as a tumor marker
- Reviews
- Biomarkers for prostate cancer: prostate-specific antigen and beyond
- Gut microbiome investigation in celiac disease: from methods to its pathogenetic role
- Opinion Papers
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