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...

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Main Authors: Yongqing Chen, Luyi Pan
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Journal of Healthcare Engineering
Online Access:http://dx.doi.org/10.1155/2021/2541751
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spelling doaj-c955b03c91ed4239aa0a89137befbd1d2021-10-11T00:39:40ZengHindawi LimitedJournal of Healthcare Engineering2040-23092021-01-01202110.1155/2021/2541751Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big DataYongqing Chen0Luyi Pan1Department of Respiratory and Critical Care MedicineEmergency DepartmentThis 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.http://dx.doi.org/10.1155/2021/2541751
collection DOAJ
language English
format Article
sources DOAJ
author Yongqing Chen
Luyi Pan
spellingShingle Yongqing Chen
Luyi Pan
Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
Journal of Healthcare Engineering
author_facet Yongqing Chen
Luyi Pan
author_sort Yongqing Chen
title Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
title_short Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
title_full Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
title_fullStr Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
title_full_unstemmed Nursing Research on Patients with Chronic Obstructive Pulmonary Disease and Respiratory Failure Based on Big Data
title_sort nursing research on patients with chronic obstructive pulmonary disease and respiratory failure based on big data
publisher Hindawi Limited
series Journal of Healthcare Engineering
issn 2040-2309
publishDate 2021-01-01
description 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.
url http://dx.doi.org/10.1155/2021/2541751
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