Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data

This work organically integrates a systematic and individualized nursing plan with big data technology and applies it to the care of patients with chronic obstructive pulmonary disease (COPD) and respiratory failure (RF) and explores the continuous care model based on modern big data technologies to improve COPD and RF. It aims to relieve the symptoms of COPD and RF, reduce the number of acute episodes of COPD and RF and the number of hospitalizations, and improve the quality of life of patients. One hundred COPD and RF patients hospitalized in the respiratory medicine department of a tertiary hospital were selected and were categorized into control and experimental group. The nursing mode of the patients in the control group was the original telephone follow-up in the department, and the contents of the follow-up were determined according to the questions of the patients on the telephone at that time. Based on the original nursing in the department, the experimental group adopted individualized continual nursing plans based on the Internet and big data techniques for patients to conduct a pulmonary rehabilitation-related functional assessment, functional exercise guidance, and health guidance. Experimental results show that, compared with traditional continuous care, individualized continuous care combined with big data techniques can improve the lung function of patients with stable COPD and RF, reduce the number of acute COPD and RF attacks and the number of readmissions, and improve self-management ability and quality of life. The method can be applied and implemented in continuous nursing care.