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人工智能病案质控系统对病案质量和质控效率的影响

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目的 分析人工智能病案质控系统对病案质量和病案质控效率的影响,为人工智能病案质控系统的进一步研究和应用提供参考.方法 随机抽取10个临床科室,将其2022年1月1日-2022年5月31日采用传统质控医师人工质控的5154份病案为对照组;2022年6月1日-2022年10月31日采用人工智能病案质控系统加质控医师复核方法质控的6646份病案为研究组.对两组的病案内涵缺陷率、缺陷类型、首页漏填率、病案质量得分情况、质控工作效率进行比较.结果 研究组的内涵缺陷率(39.86%)和住院病案首页漏填率(4.24%)均显著低于对照组(73.44%、10.05%),差异具有统计学意义(P<0.05).研究组的病案质量平均得分(92.73分)显著高于对照组(87.73分),差异具有统计学意义(P<0.05),各项病案记录的内涵缺陷量下降明显,平均降幅30.20%,且同等数量人力所用的质控时间也少于对照组1个月.结论 人工智能病案质控系统有助于降低首页漏填率、减少病案内涵缺陷、提高病案质控工作效率.
The Impact of Artificial Intelligence Medical Record Quality Control System on Medical Record Quality and Quality Control Efficiency
Objectives This study aims to analyze the impact of the artificial intelligence medical record quality control system on medical record quality and medical record quality control efficiency and provide a reference for further research and application of the artificial intelligence medical record quality control system.Methods 10 clinical departments were randomly selected.5154 medical records that were manually controlled by traditional quality control physicians from January 1,2022 to May 31,2022 were used as the control group.6,646 medical records from June 1,2022 to October 31,2022,which were quality controlled using the artificial intelligence medical record quality control system and quality control physician review method,were selected as the research group.The connotative defect rate of medical records,defect types,missed fill-in rate on the front page,medical record quality score,and quality control efficiency between the two groups were compared.Results The connotation defect rate(39.86%)and the missed filling rate of the front page of inpatient medical records(4.24%)in the study group were significantly lower than those in the control group(73.44%,10.05%),and the differences were statistically significant(P<0.05).The average score of medical record quality in the study group(92.73 points)was significantly higher than that in the control group(87.73 points),and the difference was statistically significant(P<0.05).The number of connotative defects in various medical records dropped significantly,with an average decrease of 30.20%.The quality control time for the same amount of manpower was less than 1 month for the control group.Conclusions The artificial intelligence medical record quality control system can help reduce the missed filling rate of the homepage,reduce the connotation defects of medical records,and improve the efficiency of medical record quality control.

Artificial intelligence medical record quality control systemMedical record qualityMedical record connotation defectsOmission rate of medical record front page

吕力军、张然、佟朝霞、马云波、丁吉雪

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首都医科大学附属北京安贞医院,北京市,100029

北京中医药大学东直门医院,北京市,100700

人工智能病案质控系统 病案质量 病案内涵缺陷 病案首页漏填率

2024

中国病案
中国医院协会

中国病案

CSTPCD
影响因子:1.197
ISSN:1672-2566
年,卷(期):2024.25(5)
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