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首页> 外文期刊>BMC Medical Informatics and Decision Making >Development and implementation of an LIS-based validation system for autoverification toward zero defects in the automated reporting of laboratory test results
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Development and implementation of an LIS-based validation system for autoverification toward zero defects in the automated reporting of laboratory test results

机译：基于LIS的验证系统的开发和实施，以便自动归零零缺陷在实验室测试结果的自动报告中

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Validation of the autoverification function is one of the critical steps to confirm its effectiveness before use. It is crucial to verify whether the programmed algorithm follows the expected logic and produces the expected results. This process has always relied on the assessment of human–machine consistency and is mostly a manually recorded and time-consuming activity with inherent subjectivity and arbitrariness that cannot guarantee a comprehensive, timely and continuous effectiveness evaluation of the autoverification function. To overcome these inherent limitations, we independently developed and implemented a laboratory information system (LIS)-based validation system for autoverification. We developed a correctness verification and integrity validation method (hereinafter referred to as the "new method") in the form of a human–machine dialog. The system records personnel review steps and determines whether the human–machine review results are consistent. Laboratory personnel then analyze the reasons for any inconsistency according to system prompts, add to or modify rules, reverify, and finally improve the accuracy of autoverification. The validation system was successfully established and implemented. For a dataset consisting of 833 rules for 30 assays, 782 rules (93.87%) were successfully verified in the correctness verification phase, and 51 rules were deleted due to execution errors. In the integrity validation phase, 24 projects were easily verified, while the other 6 projects still required the additional rules or changes to the rule settings. Taking the Hepatitis B virus test as an example, from the setting of 65 rules to the automated releasing of 3000 reports, the validation time was reduced from 452 (manual verification) to 275?h (new method), a reduction in validation time of 177?h. Furthermore, 94.6% (168/182) of laboratory users believed the new method greatly reduced the workload, effectively controlled the report risk and felt satisfied. Since 2019, over 3.5 million reports have been automatically reviewed and issued without a single clinical complaint. To the best of our knowledge, this is the first report to realize autoverification validation as a human–machine interaction. The new method effectively controls the risks of autoverification, shortens time consumption, and improves the efficiency of laboratory verification.
机译：Autoverification函数的验证是在使用前确认其有效性的关键步骤之一。验证程序化算法是否遵循预期逻辑并产生预期结果是至关重要的。这一过程一直依赖于对人机一致性的评估，并且主要是手动记录和耗时的活动，具有固有的主观性和武装，不能保证自动化功能的全面，及时和持续的效果评估。为了克服这些内在的局限性，我们独立开发并实施了实验室信息系统（LIS）基础的验证系统以进行Autoverification。我们以人机对话框的形式开发了一个正确性验证和完整性验证方法（以下称为“新方法”）。系统记录人员审查步骤，并确定人机审查结果是否一致。然后，实验室人员根据系统提示分析任何不一致的原因，添加到或修改规则，reverify，最终提高Autoverification的准确性。验证系统已成功建立和实施。对于由833规则组成的数据集，为30个分析，782项规则（93.87％）在正确的验证阶段成功验证，由于执行错误，删除了51条规则。在完整性验证阶段，容易验证24个项目，而其他6个项目仍然需要其他规则或更改规则设置。以乙型肝炎病毒测试为例，从65规则的设置到自动释放3000报告，验证时间从452（手动验证）降低到275？H（新方法），减少验证时间177？h。此外，94.6％（168/182）实验室用户认为，新方法大大降低了工作量，有效地控制了报告风险并感到满意。自2019年以来，未经单一的临床投诉，已自动审查和发行了超过350万报告。据我们所知，这是第一个实现Autoverification验证作为人机互动的报告。新方法有效地控制了自动化的风险，缩短时间消耗，提高了实验室验证的效率。

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