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护理学报 ›› 2022, Vol. 29 ›› Issue (19): 20-24.doi: 10.16460/j.issn1008-9969.2022.19.020

• 护理管理 • 上一篇    下一篇

基于AI语音的传染性疾病临床护理数据采集系统的构建及应用

侯绪娜1a, 隋伟玉1a, 韩凤萍2, 朱洁宏1a, 赵海芹3, 王静1b, 李启虹1c, 卢鹏章1d   

  1. 1.烟台市奇山医院 a.护理部;b.肝病科;c.感染科;d.信息科,山东 烟台 264000;
    2.北京大学护理学院基础教研室,北京 100191;
    3.首都医科大学附属北京地坛医院中西医结合一科,北京 100015
  • 收稿日期:2022-05-05 发布日期:2022-11-08
  • 作者简介:侯绪娜（1968-）,女,山东烟台人,硕士,主任护师。E-mail:811707668@qq.com
  • 基金资助:
    烟台市科技计划项目（2021YD088）

Construction and Application of Clinical Care Data Collection System of Infectious Diseases Based on AI-powered Speech

HOU Xu-na1a, SUI Wei-yu1a, HAN Feng-ping2, ZHU Jie-hong1a, ZHAO Hai-qin3, WANG Jing1b, LI Qi-hong1c, LU Peng-zhang1d   

  1. 1a. Dept. of Nursing Administration; 1b. Dept. of Hepatology; 1c. Dept. of Infectious Disease; 1d. Information Center, Qishan Hospital, Yantai 264000, China;
    2. Teaching and Research Office of Basic Courses, School of Nursing, Peking University, Beijing 100191, China;
    3. Dept. of Integrated Traditional Chinese Medicine and Western Medicine, Unit I, Beijing Ditan Hospital Affiliated to Capital Medical University, Beijing 100015, China
  • Received:2022-05-05 Published:2022-11-08

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摘要： 目的 构建基于AI语音的传染性疾病临床护理数据采集系统,并评价其应用效果。方法 以AI语音转文字技术为核心设计思路,构建以护理端AI语音知识库模块、AI语音系统与医院信息系统的对接集成模块、体温单和危重护理记录单内容解读及实时结构化处理模块、一次口述多表单同步提交模块、数据实时质控模块为一体的临床护理数据采集系统。于2020年5月—2021年10月在某三级传染病专科医院进行系统运行,比较护理文书书写质量指标、住院患者生命体征数据录入医院信息系统用时和护士使用体验。结果 基于AI语音的传染性疾病临床护理数据采集系统使用后,护理文书书写质量指标明显提高,与传统数据采集方式比较,差异有统计学意义（P<0.001）。系统使用前后新入院患者初次生命体征采集上传完成及时性差异有统计学意义（χ2=74.02,P<0.001）。系统使用后住院患者生命体征数据录入医院信息系统用时明显缩短（t=19.115,P<0.01）。在培训质量、服务质量、信息质量、使用意愿维度护士使用体验较好。结论 将基于AI语音的传染性疾病临床护理数据采集系统嵌入护理文书书写环节,提高了护理文书书写的完整性、及时性,且护士对该系统总体体验良好。

关键词: AI语音, 人工智能, 传染性疾病, 临床护理数据采集系统

Abstract: Objective To construct an AI-powered speech-based clinical nursing data collection system for infectious diseases and evaluate its application effect. Methods With AI-powered speech-to-text transcription as the core design idea, a clinical nursing data collection system was constructed with AI speech knowledge base module at the nursing end, interfacing and integration module of AI speech system with hospital information system (HIS), content interpretation and real-time structured processing module for temperature sheets and critical care record sheets, simultaneous submission module for multiple forms in one dictation, and real-time data quality control module. The system was run in a tertiary specialized hospital for infectious diseases from May 2020 to October 2021 to compare the quality indicators of nursing document writing, time spent on inpatient vital sign data entry into HIS, and nurses' using experience of the system. Results Compared with traditional data collection method, AI-powered speech-based clinical nursing data collection system for infectious diseases helped to significantly improve the quality of nursing document writing and the difference was statistically significant (P<0.001). There was statistically significant difference in the timeliness of completing and uploading initial vital sign collection for newly admitted patients before and after the use of the system (χ2=74.02, P<0.001). The time taken for inpatient vital sign data entry into HIS was significantly shorter (t=19.115, P<0.01). Nurses were satisfied with the system in the dimensions of training quality, service quality, information quality, and willingness to use. Conclusion The combination of AI-powered speech-based clinical nursing data collection system for infectious diseases with nursing document writing improves the completeness, timeliness of nursing records writing, and nurses have a generally good experience with the system.

Key words: AI-powered speech, artificial intelligence, infectious disease, clinical care data collection system

中图分类号: 

  • R47
[1] 步宏. 积极推动人工智能在病理学的应用[J].中华病理学杂志,2021,50(4):307-309. DOI:10.3760/cma.j.cn112151-20210219-00148.
[2] Stead WW.Clinical Implications and Challenges of Artificial Intelligence and Deep Learning[J]. JAMA, 2018,320(11):1107-1108. DOI:10.1001/jama.2018.11029.
[3] 王红迁,汪鹏,左锋,等.医疗智能语音识别系统的研发与应用[J].中国数字医学,2018,13(10):5-13. DOI:10.3969/j.issn.1673-7571.2018.10.002.
[4] Blackley SV,Huynh J,Wang L,et al.Speech Recognition for Clinical Documentation from 1990 to 2018: A Systematic Review[J]. J Am Med Inform Assoc,2019,26(4):324-338. DOI: 10.1093/jamia/ocy179.
[5] 帅仁俊,陈平,李文煜,等.语音智能识别在健康管理系统中的应用研究[J].中国卫生信息管理杂志, 2018,15(5):492-495. DOI:10.3969/j.issn.1672-5166.2018.05.02.
[6] Chen CM,Hou IC,Chen HP,et al. Design of an Electronic Reminder System for Supporting the Integerity of Nursing Records[J]. Stud Health Technol Inform, 2016(225):830-831.PMID:27332364.DOI10.3233/978-1-61499-658-3-830.
[7] 赵永信,顾莺,张晓波,等.住院患儿疼痛管理决策支持系统的构建与应用研究[J].中华护理杂志,2020,55(8):1147-1153. DOI:10.3761/j.issn.0254-1769.2020.08.004.
[8] 黄聪,谌永毅,刘翔宇,等. 移动医疗在护理领域的应用进展[J]. 中华护理杂志, 2019, 54(8):1264-1 269. DOI:10.3761/j.issn.0254-1769.2019.08.031.
[9] 霍然,刘畅,周金阳,等. 人工智能语音系统在护理领域的应用进展[J].中华现代护理杂志, 2021, 27(6):728-731. DOI:10.3760/cma.j.cn115682-20200509-03247.
[10] 郭江博,徐家富,苏玉成,等.医院实施语音录入系统的可行性[J].医疗装备,2017,30(23):27-28. DOI:10.3969/j.issn.1002-2376.2017.23.015.
[11] 冯梅,吴颖,吴小玲,等.新型冠状病毒肺炎一线支援医疗队护理团队建设[J].中国呼吸与危重症监护杂志,2020,19(2):137-140.DOI:10.7507/1671-6205.202002013.
[12] 彭盼,张英伟,吴金奇,等. 本科实习护生护理信息能力与临床适应及心理弹性的相关性分析[J].护理学报,2017,24(24):38-41.DOI:10.16460/j.issn1008-9969.2017.24.038.
[13] 高璐璐,盛瑾倩,李甜甜. 护理单元配备信息管理护士的做法与效果[J]. 护理学报,2019,26(1):22-24. DOI: 10.16460/j.issn1008-9969.2019.01.022.
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