Establishment and optimization of an autoverification system for thyroid function reports
10.3760/cma.j.cn114452-20240809-00441
- VernacularTitle:甲状腺功能五项检验报告自动审核系统的建立与优化
- Author:
Junhua CUI
1
;
Jing ZHU
1
;
Wenqi SHAO
1
;
Jing YANG
1
;
Baishen PAN
1
;
Beili WANG
1
;
Wei GUO
1
Author Information
1. 复旦大学附属中山医院检验科，上海200032
- Publication Type:Journal Article
- Keywords:
Thyroid function tests;
Autoverificaion system;
Clinical laboratory techniques
- From:
Chinese Journal of Laboratory Medicine
2025;48(2):207-213
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To establish and optimize an autoverification system for thyroid function test reports of 5 items using historical test data.Methods:Based on the docoment' Autoverification of Clinical Laboratory Quantitative Test Results′, CLSI AUTO 10-A and AUTO 15 guidelines, an autoverification system for thyroid function test reports of 5 items was established combining with manual verification experience. A total of 193 860 thyroid function test reports of 5 items in 2021 were collected for the assessment of the original system. Totally 210 097 thyroid function test reports of 5 items in 2022 and 299 198 reports in 2023 were collected for the optimization of the autoverification system. There were 160 666 thyroid function test reports of 5 items from the first half of 2024 for the manual and autoverification comparison after optimization.Results:The pass rate of the autoverification system based on original thyroid function report in 2021 was 69.56%(134 849/193 860). The optimized system utilizing historical data from 2022 and 2023 covered 21 pattern rules and established verification for different patterns including range rules, delta check rules, and review rules. Taking manual verification as the standard for the data from the first half of 2024, the sensitivity and specificity of the optimized system were 100% (499/499) and 81.57% (130 646/160 167), respectively, with a false-negative rate of 0. The concordance rate between autoverification and manual verification was 81.63% (131 145/160 666), and the pass rate was 81.32% (130 646/160 666).Conclusion:Establishing and optimizing the autoverification system for thyroid function tests of 5 items using historical test data, and formulating verification rules for different patterns can be applied to clinical practise, which not only ensures the accuracy of test reports but also improves work efficiency, allowing continuously optimized and perfected of the system.
