scholarly journals ISQUA18-1384Hospital-Community Integrated Blood Glucose Management Model: An Application Example of Hierarchical Diagnosis and Treatment System in China

2018 ◽  
Vol 30 (suppl_2) ◽  
pp. 16-16
Author(s):  
X GAO ◽  
J QIAN ◽  
Z SUN ◽  
H ZHAO
2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Weirong Li ◽  
Yan Zhou ◽  
Xiaohua Lu ◽  
Yan Liu ◽  
Minpin Deng ◽  
...  

Objective. In order to explore the application effect of blood glucose management mode of multi-team cooperation in perioperative period of general surgery patients. Methods. The perioperative blood glucose control of 94 patients undergoing surgical treatment in general surgery from January 2016 to March 2019 was reviewed by Non-synchronous. According to the perioperative blood glucose management model of multi-team cooperation, the patients were divided into intervention group and control group. From January 2016 to January 2018, 64 patients who did not implemented the multi-team blood glucose management model were the control group and from February 2018 to March 2019, 30 patients who implemented the multi-team blood glucose management model were the intervention group, compared with two group about the differences in perioperative blood glucose. Results. It is no statistically significant about two group in highest and lowest blood sugar levels under fasting stats; during the fluid diet the blood sugar level of the intervention group was lower than control group(P<0.05),and when the patients was in the semi-fluid or food-feeding period, the highest and lowest blood sugar level is that the intervention group was lower than control group(P<0.05). The time of the blood sugar reaching the standard, the coincidence of complications rate and average hospitalization days in the intervention group were particularly lower than control group(P<0.05). Conclusion. If we adopt multi-team blood glucose management model can better control the perioperative blood glucose of patients undergoing general sugar.


2021 ◽  
Vol 275 ◽  
pp. 02026
Author(s):  
Zehao Yao ◽  
Shihua Cao

In recent years, the “Internet + medical” exploration and the country’s vigorously promoted hierarchical diagnosis and treatment system have provided an opportunity to improve the status quo of diabetes. Some scholars have proposed “one-to-one binding community nurses” (Wang Li et al., 2016) and personalized treatment based on big data (He Ting et al., 2016). New chronic disease management concepts such as an integrated chronic disease management model for the elderly based on mobile medical technology (Che Fengyuan et al., 2016). Although different names are used, the core point of view is that patients and community doctors complete the contract, the community doctors will take care of the patients, and the hospital doctors will take care of the patients. The patient’s blood glucose data can be shared with relatives and friends, community doctors, and hospital doctors in real time with the help of platform tools such as blood glucose meters, mobile apps, and cloud medical platforms. And community and hospital doctors’ feedback on patients can also be sent to patients and relatives and friends in real time, thereby realizing hierarchical diagnosis and treatment of diabetic patients when medical resources are scarce and unevenly distributed. This article refers to this model as the “family-style chronic disease management model”. The interaction between patients, relatives and friends, community doctors, and hospital doctors is shown in Figure 1.


2021 ◽  
Vol 11 (5) ◽  
pp. 2006
Author(s):  
Jai-Chang Park ◽  
Seongbeom Kim ◽  
Je-Hoon Lee

Diabetes mellitus is a severe chronic disease, and the number of patients has increased. To manage blood glucose levels, patients should frequently measure their blood glucose and analyze which lifestyle habits affect blood glucose levels. However, it is hard to record and analyze the relationship between their blood glucose levels and lifestyle. The internet of things (IoT) is useful to interconnect, monitor, obtain, and process data between various devices used in everyday life to fulfill a common objective. This paper proposes an intelligent self-care platform using IoT technology that helps patients with chronic diabetes manage their blood glucose levels in their target range. In particular, we developed various devices called the self-care IoT pack. It consists of five different types of devices to obtain blood glucose levels, physical activities, food intake, medication, sleeping, and so on. They can collect blood glucose levels with lifestyles that automatically impact the patient’s blood glucose level. We also devised a self-care application to display and analyze the data obtained from the IoT pack. Consequently, the proposed self-care IoT platform collects the blood glucose levels and the lifestyles without any burden of record. By reviewing the accumulated information, the patients can find bad habits in blood glucose management and improve their lifestyle.


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