Literature DB >> 28490181

Designing and evaluating autoverification rules for thyroid function profiles and sex hormone tests.

Jiancheng Li1, Bizhen Cheng2, Huizhen Ouyang2, Tongtong Xiao2, Jing Hu2, Yingmu Cai2.   

Abstract

Purpose Following the analytical phase, the current practice of many hospital laboratories involves the manual verification of all test results followed by the production of the report. However, manual verification is a time-consuming and tedious process. In this paper, we provide a detailed description of how to design autoverification rules for thyroid function test profiles and sex hormones. Materials and methods We used DM2 (Data manager 2) to construct the algorithm and build the database for autoverification of thyroid function test profiles and sex hormones, with reference to Boolean logic, Auto 10-A and CLSI'88. The rules consist of checking quality control, instrument error flags, critical values, the analytical measurement range (AMR), the limit range, consistency check and delta check. Firstly, we established the rules in the DM2, collected clinical specimens for validation, then tested the rules in a 'live' environment. Results Agreement was achieved between manual verification by two senior laboratory personnel and verification using the autoverification rules in 99.78% of the cases. The total autoverification rate for all tests was 77.06%. Following implementation of the rules, the laboratory turnaround time (TAT) was reduced by 54.55% and staffing numbers fell from three to two whole time equivalents (WTE). Statistical analysis resulted in a kappa statistic of 0.99 ( P < 0.001). Moreover, after implementing the autoverification rules, the error rate fell to 0.04%, indicating that errors were almost completely eliminated. Conclusion Implementing autoverification rules can reduce TAT, minimize the number of samples that require manual verification and allow for a reduction in staffing numbers. It also allows laboratory staff to devote more time and effort to the handling of problematic test results and contributing to improved patient care.

Entities:  

Keywords:  Autoverification; DM2; laboratory automation; sex hormones; thyroid hormones

Mesh:

Substances:

Year:  2017        PMID: 28490181     DOI: 10.1177/0004563217712291

Source DB:  PubMed          Journal:  Ann Clin Biochem        ISSN: 0004-5632            Impact factor:   2.057


  6 in total

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

Authors:  Cuie Yan; Yujuan Zhang; Jia Li; Jia Gao; Chanjuan Cui; Chun Zhang; Guiyu Song; Mengyao Yu; Jianjun Mu; Feng Chen; Xiaohong Han; Wei Cui
Journal:  J Clin Lab Anal       Date:  2019-03-06       Impact factor: 2.352

2.  Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory.

Authors:  Zhongqing Wang; Cheng Peng; Hui Kang; Xia Fan; Runqing Mu; Liping Zhou; Miao He; Bo Qu
Journal:  BMC Med Inform Decis Mak       Date:  2019-07-03       Impact factor: 2.796

3.  Combined strategy of knowledge-based rule selection and historical data percentile-based range determination to improve an autoverification system for clinical chemistry test results.

Authors:  Jing Zhu; Hao Wang; Beili Wang; Xiaoke Hao; Wei Cui; Yong Duan; Yi Zhang; Liang Ming; Yingchun Zhou; Haitao Ding; Hongling Ou; Weiwei Lin; Liu Lu; Yuanjiang Shang; Yong Yang; Xianming Liang; Jiangtao Ma; Wenhua Sun; Te Chen; Guang Han; Meng Han; Weiting Yu; Baishen Pan; Wei Guo
Journal:  J Clin Lab Anal       Date:  2022-01-10       Impact factor: 2.352

4.  Designing and validating an autoverification system of biochemical test results in Hatay Mustafa Kemal University, clinical laboratory.

Authors:  Bahar Ünlü Gül; Oğuzhan Özcan; Serdar Doğan; Abdullah Arpaci
Journal:  Biochem Med (Zagreb)       Date:  2022-08-05       Impact factor: 2.515

5.  Development and implementation of an LIS-based validation system for autoverification toward zero defects in the automated reporting of laboratory test results.

Authors:  Di Jin; Qing Wang; Dezhi Peng; Jiajia Wang; Bijuan Li; Yating Cheng; Nanxun Mo; Xiaoyan Deng; Ran Tao
Journal:  BMC Med Inform Decis Mak       Date:  2021-06-02       Impact factor: 2.796

6.  Implementation of total laboratory automation at a tertiary care hospital in Saudi Arabia: effect on turnaround time and cost efficiency.

Authors:  Tracy Louise Ellison; Maha Alharbi; Morad Alkaf; Shamad Elimam; Mariam Alfaries; Randa Al Nounou; Rasheed Nasr; Tarek Owaidah
Journal:  Ann Saudi Med       Date:  2018 Sep-Oct       Impact factor: 1.526

  6 in total

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