Application Analysis Based on Big Data Technology in Stroke Rehabilitation Nursing

Abstract

According to the statistical analysis, the incidence of stroke disease has gradually increased, particularly in recent years, which poses a huge threat to the safety of human life. Due to the advancement in science and technology specifically big data and sensors, a new research dome known as data mining technology has been introduced, which has the potential value from the perspective of large amount of data analysis. Information has become a new trend of science and technology, and data mining has been used in various application areas to analyze and predict strokes at home and abroad. In this study, big data technology is utilized to collect potential information and explores clinical pathways of level-3 rehabilitation in certain regions of China. Moreover, application effects of data mining in the rehabilitation of patients with the first ischemic stroke have been evaluated and reported. For this purpose, fifty (50) first-time ischemic stroke patients have been screened through big data and were nonartificially assigned to level-3 clinical pathway and conventional rehabilitation groups, respectively, specifically through software. The first group of patients enters the clinical path of the corresponding level according to the way of three-level referral. These patients were analyzed based on the collected results of completing the unified rehabilitation treatment plan of the three-level rehabilitation medical institution in the patient record form. The second group was selected according to the routine rehabilitation model and method of the medical institution where the patients visited were divided into four stages: before treatment, three weeks after treatment, nine weeks after treatment, and seventeen weeks after treatment. For this purpose, a simplified Fugl-Meyer analysis (FMA), recording of various functions of limb movement, and modified Barthel index (MBI) scale were used to analyze and evaluate the ability of daily activities and compare their effects. The final results showed that FMA and MBI scores of the two groups were improved in the three stages after treatment. The FMA and MBI scores of the clinical pathway group on 3rd and 9th weekends were significantly different from those of the conventional rehabilitation group (which is $p<0.05$ ). Moreover, difference in FMA and MBI scores between the two at the 17th weekend was not significant. The total cost of the clinical pathway group, particularly at the ninth weekend, was higher than that of the conventional rehabilitation group, but the cost-benefit ratio was better and the incidence of complications was lower than that of the other group.