基于物联网技术智能健康管理系统在临床护理中的应用研究
发布时间：2018-08-28 07:54
【摘要】：一、研究目的和意义探讨基于物联网技术的智能健康管理系统在临床护理中的应用,通过研究了解物联网技术在临床护理应用中凸显出的先进性、科学性、实用性以及在应用中产生的新问题。为进一步实现物联网技术与护理信息管理系统的无缝对接和提高其在护理信息管理系统应用中的深度与广度提供了实践与理论基础。从护理实践活动量化的方式、实时监控、科学管理、智能决策的角度,为实现提高护理服务品质、减少差错、降低劳动强度、提高工作效率和临床科研水平,保障高效、优质、科学、精准、规范的临床护理工作提供新思路与新方法。二、材料与方法通过实验室自身平行对照研究,评价物联网技术与传统技术两种不同的临床测量方法,在T、P、R、SP02上是否具有一致性,同时研究物联网技术在临床护理应用中的价值与优势,分析其在应用中出现的问题,从而进一步完善物联网在护理领域的规划与建设。采取便利取样法与自愿的原则,筛选实习护生10名及心脑血管科住院病人30名。采用SPSS16.0软件进行统计分析与处理,其中计量资料用均数±标准差表示,结果采用重复测量数据的方差分析、相关回归、配对t检验、Bland-Altman等方法进行综合分析,结合临床实际,对两种测量方法进行一致性评价,研究两种不同的临床测量方法是否可以完全替代,以及验证新方法是否具有科学性、先进性与实用性,并提出新方法在应用过程中出现的问题以及解决对策。三、主要研究结果两种测量方法所获得数据样本,在R上不存在统计学差异(P=0.160.05),但T、 P、 SP02上均存在统计学差异(P0.05)。通过相关回归分析,计算出两组T、P对照数据,存在线性关系,具有一致性偏倚,并成立回归方程,说明其紧密程度高,智能健康管理系统可以通过定标检测后再行决定是否需要进行模型校对和调整,即可转换一致。SP02通过Bland-Altman法,计算出两组数据的差值95%以上位于96.7%～99.8%的界限内,结合临床评价,得出结论：两种不同测量方法完全可以替代。临床实验结果：智能健康管理系统从仪器佩戴到终端显示数据仅需要4±1分钟。并且接收器与网络后台是同步显示实时数据。在护士工作站或者Internet相关路径下通过授权的账号密码显示出的整个动态数据包括T、P、R、SP02等生理参数,表现形式分为文本与图形方式分别显示在电子病历和护理病历中,并高度实现信息共享。四、主要结论研究数据表明：不同原理的两种测量方式在临床应用上完全可以替代,且CIM比传统(手工和半自动化)方式在测绘T、P、R上时间效率分别提高了76.20%和72.02%。智能健康管理系统在数据采集-分析-清洗-存储-服务应用上超越了传统信息技术,实现了智能自动化、标准化数据采集方式,保障了数据的真实性和“信息流”的实时性、满足了资源共享和医疗区域互联互通的需求。
[Abstract]:First, the purpose and significance of this study is to discuss the application of intelligent health management system based on Internet of things technology in clinical nursing, and to understand the advanced and scientific nature of Internet of things technology in clinical nursing application. Practicability and new problems in application. It provides a practical and theoretical basis for realizing seamless connection between Internet of things technology and nursing information management system and improving the depth and breadth of its application in nursing information management system. In order to improve nursing service quality, reduce errors, reduce labor intensity, improve work efficiency and clinical scientific research level, and ensure high efficiency and high quality, from the point of view of quantification of nursing practice, real-time monitoring, scientific management and intelligent decision making, this study aims at improving nursing service quality, reducing errors, improving work efficiency and improving clinical scientific research level. Scientific, accurate and standardized clinical nursing work provides new ideas and methods. Secondly, the materials and methods were evaluated by the laboratory's own parallel control study to evaluate the consistency of the two different clinical measurement methods of the Internet of things technology and the traditional technology. At the same time, the value and advantage of Internet of things technology in clinical nursing application were studied, and the problems in its application were analyzed, so as to further improve the planning and construction of Internet of things in the field of nursing. The convenient sampling method and voluntary principle were adopted to screen 10 nursing students and 30 inpatients in cardio-cerebrovascular department. The statistical analysis and processing were carried out by SPSS16.0 software, in which the measurement data were expressed as mean 卤standard deviation. The results were analyzed comprehensively by means of ANOVA, correlation regression, paired t test and Bland-Altman, combined with clinical practice. To evaluate the consistency of the two measuring methods, to study whether the two different clinical methods can be completely replaced, and to verify whether the new method is scientific, advanced and practical. The problems in the application of the new method and the countermeasures are put forward. Third, the main results of the two methods of measurement data samples, there is no statistical difference in R (P0. 160. 05), but there is a statistical difference in T, P, SP02 (P0.05). Through the correlation regression analysis, the two groups of TMP control data were calculated, there was a linear relationship, there was a consistent bias, and the regression equation was established, which shows that the tightness of the two groups is high. The intelligent health management system can determine whether or not model proofreading and adjustment are needed after calibration and testing, and can convert consistent .SP02. Through Bland-Altman method, the difference between the two groups of data is calculated to be more than 95% within the 99.8% limit of 96.7% or 99.8%, and combined with clinical evaluation. It is concluded that two different measurement methods can be completely substituted. Clinical trial results: it takes only 4 卤1 minute for the intelligent health management system to display data from instrument to terminal. And the receiver and the network background are synchronous display real-time data. The whole dynamic data displayed by the password of authorized account number under the nurse workstation or Internet related path includes physiological parameters such as TPS / RN SP02, which are displayed in the electronic medical record and the nursing medical record respectively in the form of text and graphics. And highly realize information sharing. 4. The main conclusions are as follows: the two measuring methods of different principles can be completely replaced in clinical application, and the time efficiency of CIM is 76.20% and 72.02% higher than that of traditional (manual and semi-automatic) methods in surveying and mapping. The intelligent health management system surpasses the traditional information technology in the application of data acquisition, analysis, cleaning, storage and service, realizes the intelligent automation, standardizes the data collection method, guarantees the authenticity of the data and the real-time of "information flow". It meets the need of resource sharing and medical regional interconnection.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R47
本文编号：2208764
[Abstract]:First, the purpose and significance of this study is to discuss the application of intelligent health management system based on Internet of things technology in clinical nursing, and to understand the advanced and scientific nature of Internet of things technology in clinical nursing application. Practicability and new problems in application. It provides a practical and theoretical basis for realizing seamless connection between Internet of things technology and nursing information management system and improving the depth and breadth of its application in nursing information management system. In order to improve nursing service quality, reduce errors, reduce labor intensity, improve work efficiency and clinical scientific research level, and ensure high efficiency and high quality, from the point of view of quantification of nursing practice, real-time monitoring, scientific management and intelligent decision making, this study aims at improving nursing service quality, reducing errors, improving work efficiency and improving clinical scientific research level. Scientific, accurate and standardized clinical nursing work provides new ideas and methods. Secondly, the materials and methods were evaluated by the laboratory's own parallel control study to evaluate the consistency of the two different clinical measurement methods of the Internet of things technology and the traditional technology. At the same time, the value and advantage of Internet of things technology in clinical nursing application were studied, and the problems in its application were analyzed, so as to further improve the planning and construction of Internet of things in the field of nursing. The convenient sampling method and voluntary principle were adopted to screen 10 nursing students and 30 inpatients in cardio-cerebrovascular department. The statistical analysis and processing were carried out by SPSS16.0 software, in which the measurement data were expressed as mean 卤standard deviation. The results were analyzed comprehensively by means of ANOVA, correlation regression, paired t test and Bland-Altman, combined with clinical practice. To evaluate the consistency of the two measuring methods, to study whether the two different clinical methods can be completely replaced, and to verify whether the new method is scientific, advanced and practical. The problems in the application of the new method and the countermeasures are put forward. Third, the main results of the two methods of measurement data samples, there is no statistical difference in R (P0. 160. 05), but there is a statistical difference in T, P, SP02 (P0.05). Through the correlation regression analysis, the two groups of TMP control data were calculated, there was a linear relationship, there was a consistent bias, and the regression equation was established, which shows that the tightness of the two groups is high. The intelligent health management system can determine whether or not model proofreading and adjustment are needed after calibration and testing, and can convert consistent .SP02. Through Bland-Altman method, the difference between the two groups of data is calculated to be more than 95% within the 99.8% limit of 96.7% or 99.8%, and combined with clinical evaluation. It is concluded that two different measurement methods can be completely substituted. Clinical trial results: it takes only 4 卤1 minute for the intelligent health management system to display data from instrument to terminal. And the receiver and the network background are synchronous display real-time data. The whole dynamic data displayed by the password of authorized account number under the nurse workstation or Internet related path includes physiological parameters such as TPS / RN SP02, which are displayed in the electronic medical record and the nursing medical record respectively in the form of text and graphics. And highly realize information sharing. 4. The main conclusions are as follows: the two measuring methods of different principles can be completely replaced in clinical application, and the time efficiency of CIM is 76.20% and 72.02% higher than that of traditional (manual and semi-automatic) methods in surveying and mapping. The intelligent health management system surpasses the traditional information technology in the application of data acquisition, analysis, cleaning, storage and service, realizes the intelligent automation, standardizes the data collection method, guarantees the authenticity of the data and the real-time of "information flow". It meets the need of resource sharing and medical regional interconnection.
【学位授予单位】：复旦大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R47
【参考文献】
相关期刊论文 前1条
1 蔡宝英;迟凤玉;金霞;熊伯芳;;网络环境下护理管理模式的转变与效果[J];护理研究;2011年28期
，本文编号：2208764
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