Model Construction,empirical Analysis And Strategy Optimization Of Diabetes Prevention And Control System Management Guided By "Mobile Internet Of Things Plus Continuous Medical Services"

BackgroundThe incidence of diabetes mellitus is high in the world,and the situation of prevention and control is extremely severe.Comprehensive,systematic and continuous disease management can effectively prevent and control the occurrence and development of diabetes.The application of mobile Internet of Things technology in medical field provides the possibility of real-time collection and sharing of massive health data,and also provides important technical support for innovating the management mode of diabetes prevention and control.It is of great theoretical and practical significance to construct the management mode of diabetes prevention and control system guided by "mobile Internet of Things plus continuous medical treatment" and to explore the feasible implementation strategy by effectively combining mobile Internet of Things with diabetes prevention and control management.ObjectivesBased on the exploration of diabetes prevention and control system management model guided by "mobile Internet of Things plus continuous medical treatment",this study aimed to establish the diabetes data information platform,develop and integrate the diabetes prevention and control management support system,construct the theoretical model of diabetes prevention and control system management model guided by "mobile Internet of Things plus continuous medical treatment";to validate and analyse the model based on real world multidimensional clinical data;to analyse the influencing factors and evaluate the existing problems of the management model;and to optimize the implementation strategy.Methods1.The diabetes data information platform is built based on Hadoop ecosystem in order to realize the collection,storage,integration,processing,sharing and application of multi-source data;the diabetes prevention and control management App is designed and connected with wearable medical equipment to provide a support system for the dynamic prevention and control of diabetes mellitus;the theoretical model of diabetes prevention and control system management model guided by "mobile Internet of Things plus continuous medical treatment" is constructed.2.A third-level first-class hospital of metabolic disease and five community health service centers in Tianjin were selected to set up an empirical test base to implement the diabetes prevention and control system management mode.Based on the real world multidimensional clinical data,the Microsoft Visual Basic Visual Program Compilation Platform was used to compile the processing program to clean up,standardize and integrate the data.Using epidemiological and health statistics methods,the control rate and means of glycemic indexes between patients with type 2diabetes in usual care and diabetes prevention and control system management mode were compared.3.The influencing factors of diabetes prevention and control system management mode guided by "mobile Internet of Things plus continuous medical treatment" were analyzed.The relevant parties in the ecosystem were evaluated.Based on clinical guidelines,expert experience and rule reasoning,the diagnosis model of diabetes is constructed,and diagnosis/differential diagnosis path is visualized.Health risk factor assessment method was used to construct diabetes risk assessment model and complication risk prediction model.Results1.This study built a distributed storage and computing platform based on Hadoop framework.The overall framework of the platform included data acquisition layer,physical resource layer,data storage layer,data analysis layer and data application layer,which can realize the collection,storage,integration,processing,sharing and application of multi-source data.The diabetes prevention and control management support system included diabetes prevention and control management App and wearable medical equipment‘s interface with App.Based on the theory of continuous medical service,this study constructed a theoretical model of diabetes prevention and control system management guided by "mobile Internet of Things plus continuous medical treatment",which included six functional modules,including continuity module of institutions,disciplines,interpersonal relationship,feelings,management,and information support.2.The results showed that the control rates of Hb A1 c,FBG and P 2BG in the diabetes prevention and control system management group were significantly higher than those in usual care group at 3,6,9 and 12 month follow-ups(P < 0.01).At the four follow-ups,the control rates of Hb A1 c in the diabetes prevention and control system management group were 69.97%,71.89%,75.38% and 72.13%,respectively;the control rates of FBG were 59.24%,56.61%,59.54% and 59.77%,and the control rates of P2 BG were 79.72%,80.20%,81.97% and 76.19%,respectively.The Hb A1 c,FBG and P2 BG in the diabetes prevention and control system management group maintained stable control rates from 3 month follow-up,and lasted longer(> 6months).The variation trend of Hb A1 c and P2 BG showed as "L" curve,and the curve turning point appeared at 6 month follow-up;the variation trend of FBG showed as "V" curve,and the curve turning point appeared at 3 month follow-up.3.Tendency factors included change of patients' health concept,preference for choice,trust,service group and disease awareness rate;contributing factors included rapid development of information technology,national policy,incentive and supervision of laws and regulations,and function design of App;strengthening factors included social support,patient benefits,social benefits,and economic benefits.Existing problems included the low activity of doctors in App,the lack of sufficient professional guidance for diabetic patients,the failure to give full play to the role of primary health care institutions in the management of diabetes outside the hospital,the limitation of the functions of health teachers and dietitians outside the hospital,the lack of individualized patient health guidance,and the lack of evidence-based approach.The diabetes diagnosis model was constructed to visualize the paths of diagnosis and differential diagnosis,and the risk assessment model of diabetes and the risk prediction model of complications were constructed.ConclusionsThe diabetes data information platform based on Hadoop Ecosystem provided an important technical support for the implementation of diabetes prevention and control system management mode.The diabetes prevention and control management support system included an App and the interface with wearable medical equipment.The theoretical model of diabetes prevention and control system management based on continuous medical service theory realized the path of "data acquisition-data transmission-touch management strategy package-generation of personalized management scheme-push reference results and suggestions",and the content of "one support,three collaborations,five continuities".Empirical analysis based on real world multidimensional clinical data showed that diabetes prevention and control system management model effectively improved the control rates of glycemic indexes,and the duration of the control rates lasted longer(> 6 months).Six month follow-up should be taken as the entry point of intensive management of patients to ensure the sustainability and stability of long-term effect of diabetes prevention and control system management model.Based on the existing problems in the implementation of this model,the optimized implementation strategies included extending the service chain forward,identifying high-risk groups through risk prediction,promoting the forward movement of the diabetes prevention and control gateway,standardizing the diabetes diagnosis and treatment path,giving full play to the role of grass-roots medical and health institutions,paying attention to multidimensional indicators,dynamic monitoring,and improving the comprehensive prevention and control strategy of diabetic complications.Policy SuggestionsEstablishing a systematic,continuous and integrated concept of chronic disease prevention and control management;promoting the extrapolation of the management mode of diabetes prevention and control system;expanding the value chain of the management mode of diabetes prevention and control system;accelerating the establishment of regional medical and health information data platform;strengthening the integration of diabetes management support system;encouraging clinical experts and patients with chronic diseases to participate in App design;strengthening the guarantee of mobile medical service system;and strengthening the management function of primary medical and health institutions.