The Application Research Of Health Management System Based On The Internet Of Things Technology In Clinical Nursing Research

Objective:Discuss the application of Internet of things technology in clinical nursing, Through laboratory and clinical experiments, Understanding of the Internet of things technology in the application of clinical nursing highlights, the advanced nature, scientific, practicability and The new problems in the application. In order to further realize the Internet of things technology and nursing information management system (NIS) seamless docking, and to improve the depth and breadth in the NIS applications, provides the practical and theoretical basis. From nursing practice activities of quantitative methods, real-time monitoring, scientific management and intelligent decision-making perspective, in order to achieve to improve the nursing service quality, reduce errors, reduce labor intensity, improve work efficiency and clinical scientific research level, ensure efficient, high-quality, scientific, accurate, standardized clinical care work to provide new ideas and new methods.Method:This device is adopted in the experiment by real-time intelligent health monitoring system. Through laboratory itself parallel control study, evaluation of new technology and traditional technology of two different clinical measurements on T, P, R, SPO2, whether has consistency, in clinical nursing application value and advantage, analyzing the problems in the application, so as to further perfect the Internet of things in the planning and construction in the field of nursing. Take the convenience sampling method and the principle of voluntary, Screening 10 practice nursing students and 30 cardiovascular department hospitalized patients from hospital. Using SPSS16.0 software for statistical analysis and processing, The measurement data with mean ± standard deviation, according to the results using analysis of variance of repeated measurement data, related regression, paired t test and Bland - Altman method carries on the comprehensive analysis, combined with clinical practice, to judge the consistency of two methods of measuring, studies two kinds of different clinical measurement method can entirely replace, and verify the new method is scientific, advanced and practical, and put forward a new method in the application process the problems and countermeasures.Result:Two measurement methods to obtain data samples, R was not significant (P= 0.16> 0.05), but there are statistically significant difference (P<0.05) in the T, P, SP02. Through regression analysis to calculate the two sets of T, P control data, there is a linear relationship, consistent bias, And set up a regression equation, it show that the close degree is high. Intelligent health monitoring system can calibration tests again after deciding whether need to be adjusted, model checking and can transform. SP02 by Bland-Altman, calculate the difference between two groups of data within the limits of more than 95% in 95% 96.7% clinical evaluation, concluded:two different methods of measurement can completely replace. Results of clinical trials:smart health monitoring system worn from the instrument to the terminal display data requires only 4 ±1 minutes. And the receiver (patients carrying smart phone) network background is synchronized display real-time data. The entire dynamic data, including T, P, R, SP02. Form is divided into text and graphics modes, respectively displayed in the electronic medical records and nursing records, and highly realize information sharing.Conclusion:Experimental data show that the principle of two kinds of different measurement methods on the clinical application can completely replace, and intelligent health monitoring system than traditional mode (manual and semi-automatic) on T, P, R of surveying and mapping time efficiency increased by 76.20% and 72.02% respectively. Intelligent health monitoring system in data collection - analysis-cleaning - storage - service applications beyond traditional information technology, realized intelligent automation and standardized data collection way, ensuring the authenticity of the data and "information flow", meet the real-time demand interconnectivity and medical area resource sharing.