Abstract
Objectives
Currently, most medical laboratories do not have a dedicated software for managing report recalls, and relying on traditional manual methods or laboratory information system (LIS) to record recall data is no longer sufficient to meet the quality management requirements in the large regional laboratory center. The purpose of this article was to describe the research process and preliminary evaluation results of integrating the Medical Laboratory Electronic Record System (electronic record system) laboratory report recall function into the iLab intelligent management system for quality indicators (iLab system), and to introduce the workflow and methods of laboratory report recall management in our laboratory.
Methods
This study employed cluster analysis to extract commonly used recall reasons from laboratory report recall records in the electronic record system. The identified recall reasons were validated for their applicability through a survey questionnaire and then incorporated into the LIS for selecting recall reasons during report recall. The statistical functionality of the iLab system was utilized to investigate the proportion of reports using the selected recall reasons among the total number of reports, and to perform visual analysis of the recall data. Additionally, we employed P-Chart to establish quality targets and developed a “continuous improvement process” electronic flow form.
Results
The reasons for the recall of laboratory reports recorded in the electronic recording system were analyzed. After considering the opinions of medical laboratory personnel, a total of 12 recall reasons were identified, covering 73.05 % (1854/2538) of the recalled laboratory reports. After removing data of mass spectra lab with significant anomalies, the coverage rate increased to 82.66 % (1849/2237). The iLab system can generate six types of statistical graphs based on user needs, including statistical time, specialty labs (or divisions), test items, reviewers, reasons for report recalls, and distribution of the recall frequency of 0–24 h reports. The control upper limit of the recall rate of P-Chart based on laboratory reports can provide quality targets suitable for each professional group at the current stage. Setting the five stages of continuous process improvement reasonably and rigorously can effectively achieve the goal of quality enhancement.
Conclusions
The enhanced iLab system enhances the intelligence and sustainable improvement capability of the recall management of laboratory reports, thus improving the efficiency of the recall management process and reducing the workload of laboratory personnel.
Funding source: Shenzhen Key Medical Discipline
Award Identifier / Grant number: SZXK054
Acknowledgments
We would like to thank HuiKang Technology for their digital expertise and technical support in software development and the engineers of Luohu Hospital Group for their help in system commissioning.
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Research ethics: The local Institutional Review Board deemed the study exempt from review.
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Informed consent: Not applicable.
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Author contributions: Chuang Zhang participated in the implementation of this study, including data collection, data analysis, statistical analysis, and writing of the manuscript. Dayang Chen provided guidance for this study. Xiang Ji, Jiehong Wei, and Xiaowen Dou are involved in the monitoring and maintenance of quality indicators. Xiuming Zhang participated in the topic design, technical guidance, and funding support of this study in Clinical Chemistry and Laboratory Medicine. The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Competing interests: The authors state no conflict of interest.
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Research funding: Shenzhen Key Medical Discipline (SZXK054).
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Data availability: The raw data can be obtained on request from the corresponding author.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/cclm-2023-0786).
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