Nursing Intervention Based on Smart Medical Care on the Sleep Quality of Cardiology Patients

• Main Authors: Guifang Gao, Jingjing Su
• Format: Article
• Language: English
• Published: Hindawi Limited 2021-01-01
• Series: Journal of Healthcare Engineering
• Online Access: http://dx.doi.org/10.1155/2021/9947438

With the rapid development of society and the gradual improvement of people’s living standards, patients with cardiovascular diseases have higher standards and requirements for daily health care and quality of life. The main research of this article is based on the observation of the effect of smart medical nursing intervention on the sleep quality of cardiology patients. The convenience sampling method was used to randomly select 80 cardiology patients from the electronic medical record system of the hospital, and the patients were randomly divided into two groups. One group was the control group. The routine nursing method was adopted, and a dedicated nurse paid attention to the sleep status; the other group was the control group. The research group adopts targeted nursing methods. This paper selects three kinds of sensor data as features. When collecting each scene record, it is first divided into sleeping and awake states, and then the classified time is composed of time segments, and these time segments are finally accumulated into sleep duration. Using sleep time, waking time, and sleep duration as input, the participants were divided into good sleepers and poor sleepers. Through a self-made questionnaire survey, the factors that have an adverse effect on the patient’s sleep are divided into 7 aspects. Using the method of internal continuity measurement, Cronbach’s coefficient a is 0.811, suggesting that the internal consistency is better, and the calculation reliability and validity are 86.1% and 83.4%, respectively, suggesting that the table can be used for sleep in hospitalized patients. The P values of the study group and the control group were 0.420, 0.764, 0.740, 0.881, 0.842, 0.119, and 0.342 P>0.05. The results show that the application of smart medical services has a certain effect on the patient's sleep quality.