Abstract:
Objective Use the self-developed all-factor intelligent auditing platform in the KMClient laboratory information system to release a large number of inspection reports, the automatic auditing and early warning rules of items are set up in biochemical luminescence, clinical blood, clinical immunology, mass spectrometry, microorganism, gene and pathology and a large number of inspection reports originally required to be issued by manual auditing are submitted to the computer for publication, thus reduce the number of people and the error of the report result caused by manual error, reduce the sample turn around time (TAT), save labor costs and improve work efficiency.
Methods According to the technical requirements and industry standards of biochemical luminescence, clinical blood, clinical immunology, clinical microbiology, gene and pathology, several autoverification rules are set up respectively to judge the results. The results can be released by computer if judgement is passed, otherwise the results will be intercepted and released by manual verification statistical regularly on the status of automatic audit approval of each test item, and gradually optimize the early warning rules, compare the TAT changes before and after the use of automatic audit function and the number changes of report approval personnel to evaluate the effectiveness of automatic audit.
Results After the use of the automatic audit in all disciplines of the laboratory, the accuracy and timeliness of the report have been significantly improved. The average TAT in each department has been shortened by 0.5 h and the total number of staffs has been reduced by 4, and the defect rate of the report defect rate has been reduced by 80%.
Conclusion The all-factor intelligent auditing platform developed by our center can meet the needs of many disciplines, and is superior to most of the automatic audit middleware in the market. The use of automatic audit can not only further improve the efficiency of laboratory work and shorten TAT, but also reduce the quality defects caused by human factors, and maintain the quality assurance of laboratory analysis.
Key words:
Comprehensive,
Intelligence autoverification,
Warning rules,
Efficacy evaluation
Ju Zhang, Ran Tao, Yuan Mao, Shuhui Bian, Peng Cao. Effectiveness evaluation of the all-factor intelligent auditing applying to release reports in different clinical department[J]. Chinese Journal of Clinical Laboratory Management(Electronic Edition), 2019, 07(01): 43-47.