Research On Continuing Nursing Model Of Stroke Based On Mobile Medical Care

Stroke has the characteristics of high disability,fatality,high recurrence,and long recovery period.The complications caused by it,such as disturbance of consciousness,hemiplegia,loss of speech function,etc,have seriously affected the quality of life of patients,and brought great impact to patients and medical units.At the same time,the quality of stroke continuation care services in China is uneven and lacks implementation.Effective stroke continuation care model has severely restricted the improvement of rehabilitation effect of stroke patients after discharge from hospital.Therefore,this study combines mobile medical technology to design a stroke continuation care model that improves the utilization of medical resources,in order to provide high-quality stroke continuation care services for stroke patients and improve the rehabilitation effect of patients.First of all,this article analyzes and summarizes the continuity nursing needs of patients with stroke rehabilitation and the problems in the traditional stroke continuity nursing model,and proposes the design concept of the combined medical and nursing care model for stroke continuity nursing,and constructs the model based on the design concept——The macro-architecture-multi-party collaboration mode and intelligent diagnosis and treatment mode,and analyzes the characteristics of the mode from the perspective of complex adaptive system,laying a basic framework for the subsequent mobile medical platform design and mode operation mechanism analysis.Secondly,this research is based on the multi-party collaboration model and the intelligent diagnosis and treatment model,combined with mobile medical technology,to design the stroke comprehensive care platform and the user’s functional requirements,functional modules,physical sign monitoring environment and database within the platform.In addition,on the basis of clarifying the flow of data and information within the platform,the platform-mode collaboration mechanism is analyzed,and the interaction paths and processes between the subjects in the multiple collaboration mode are refined,so that the comprehensive stroke care platform and mode are closely integrated.It provides support for the analysis and design of the follow-up early warning mechanism for stroke recurrence.Finally,in view of the high recurrence rate of stroke,this study preprocessed the data that can be collected in the physical sign monitoring environment,and screened out the factors that are highly related to stroke recurrence,and constructed them with CART decision trees,random forests and XGBoost algorithms.The stroke recurrence prediction model shows that under this index set,the performance of XGBoost algorithm is better than CART decision tree and random forest.On this basis,the XGBoost algorithm was used to construct an early warning mechanism for stroke recurrence,and the design of the intelligent function of the intelligent diagnosis and treatment mode was completed.