Investigations On The Classification Care Model Of Veterans

ObjectiveDue to the problems of aging,chronic disease and disability of veterans,this study aims to address the issue on the long-term care that the current medical care content is simple and extensive,and the service 1s difficult to match the actual needs of veterans.It is necessary to build a new care service model.Learning from the experience of advanced long-term classification care service home and abroad,combined with the existing functional defects and long-term care needs of veterans,the study will establish a continuous,quantitative and accurate classification care model.This model will be applied in patients with chronic kidney disease.Methods1.Based on the traditional comprehensive literature review,the literature that meet the inclusion criteria were collected,screened,evaluated and systematically analyzed to obtain evidence of service assessment,service contents and service grading in long-term care service.2.With the descriptive qualitative design,through the semi-structured interviews and observations of home care for veterans,the research on the status quo of home care for veterans was earried out.3.With the Delphi method,through two rounds of expert consultations,the rationality of care classification and care contents of the care model for veterans were demonstrated and a specific classification care model was constructed.4.The classification care model was applied in elderly CKD patients.The elderly CKD patients was divided into groups according to CKD stages.The differences in the dimensions of each group were compared and the empirical results of the application of the care model were obtained.Results1.A total of 22 literature were included in the study.It was found that the long-term care assessment at home and abroad covered the dimensions of disease burden,disability level,social support,mental state and care risk.The long-term care service divides the service category according to the degree of disability and the frequency of demand.The service content is personalized on the basis of satisfying the daily care.2.Through semi-structured interviews and related observations of 16 veterans,it is found that there are physical,cognitive and cognitive deficiencies related to age among veterans,and the risk of falls and nutrition is high,but the psychological state is better.There is a need for professional care,life care,and spiritual comfort in long-term care.3.With two rounds of expert consultations,a classification care model of veterans was constructed.After the assessment of four dimensions of disease burden,disability level,family support and care risk,combined with the weight combination of each dimension,the clients are graded and classified based on the scores of each dimension and the sum of them.The service contents mainly include four aspects:specific care,daily life care,rehabilitation guidance and psychosocial care.4.To validate the effectiveness of the classification care model,this model was applied in elderly CKD patients.The results showed that different stages of CKD patients had different medical care conceems.Care classification can identify risk stratification of elderly CKD patients,helpful to take targeted care measures.The classification of care can predict the short-term readmission rate of elderly patients with CKD.Therefore,the classification care model has good applicability in elderly patients with CKD.ConclusionsThis study established a classification care model based on the four assessment dimensions including disease burden,disability level,family support and care risk.The service assessment method was applied in elderly patients with CKD and had good applicability.This model takes the multiple health-related factors including physiology,psychology and society into account.It can screen out the key care populations,rationally allocate medical care resources.In the future,an intelligent evaluation system for long-term care of veterans can be developed to realize the intelligent,real-time and convenient evaluation and monitoring of home care.