Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic

Kang, Jian; Chen, Yan; Zhao, Ying; Zhang, Chuan

doi:10.1016/j.pcd.2020.12.004

Cited by 36 publications

(39 citation statements)

References 31 publications

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“…Item 16 is not included in any subscales. The scale includes four subscales: glucose management (1,4,6,10,12), diet control (2,5,9,13), physical activity (8,11,15), and use of health services (3,7,14).…”

Section: Diabetes Self-management Questionnaire (Dsmq)mentioning

confidence: 99%

“…COVID-19 first appeared in China, then became a public health threat to the whole world, and in March 2020 was declared a pandemic by the World Health Organization (WHO) [1]. People of all ages are susceptible to COVID-19, but diabetic patients are at greater risk because they have many accompanying chronic illnesses and their immune systems are under pressure [2][3][4]. The COVID-19 pandemic has led to more variable blood sugar levels in diabetic patients, and to an increase in HbA1c levels, hospitalization and intensive care needs [5].…”

Section: Introductionmentioning

confidence: 99%

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The effect of the COVID-19 pandemic on self-management in patients with type 2 diabetics

Utli

Doğru

2021

Primary Care Diabetes

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Aims: The research was conducted with the aim of determining the effect of the COVID-19 pandemic on levels of self-management in individuals with type 2 diabetes. Methods: This cross-sectional descriptive type of study was conducted between 21 December 2020 and 1 April 2021. It was performed with 378 individuals with type 2 diabetes attending the endocrinology clinic and outpatients' department of a government hospital who agreed to participate in the research. In the collection of data, a Patient Identification Form, Visual Analog Scales (an Anxiety VAS and a Stress VAS), and the Diabetes Self-Management Questionnaire (DSMQ) were used. The Wilcoxon test, Independent Sample t test, One-Way Anova and binary logistic regression were used in the analysis of data. Results: The Diabetes Self-Management Questionnaire (DSMQ) total mean score of the individuals with type 2 diabetes participating in the study during the COVID-19 pandemic was 5.25 ± 1.04. Their anxiety total mean score was 0.32 ± 1.56, and their total mean stress score was 7.06 ± 1.62. Being male, over the age of 65, married and having a diagnosis of diabetes for 6-11 years, increased smoking, the COVID-19 pandemic, reduced physical activity (not walking) and support obtained from health professionals, and increased anxiety and stress levels were found to be risk factors affecting diabetic self-management. Conclusions: The findings show that the COVID-19 pandemic has had a negative effect on the selfmanagement levels of individuals with type 2 diabetes.

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Section: Diabetes Self-management Questionnaire (Dsmq)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The effect of the COVID-19 pandemic on self-management in patients with type 2 diabetics

Utli

Doğru

2021

Primary Care Diabetes

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“…People with diabetes have impaired phagocytosis by neutrophils, macrophages and monocytes, impaired neutrophil chemotaxis and bactericidal activity, and impaired innate cell-mediated immunity. As overall, CVDrelated deaths continue to decline among people with diabetes [15], [16].…”

Section: Management Of Patients With Dm During the Covid-19 Pandemic In Indonesiamentioning

confidence: 99%

“…Many patients with DM have concerns about going to the hospital during the pandemic, leading to delayed treatment adjustments and inadequate health education. In addition, during a pandemic, limited exercise, irregular diets, and poor patient selfmanagement skills make blood glucose management more difficult [16]. Poor glucose control will result in increased morbidity and mortality due to COVID-19 (Figure 1).…”

Section: Management Of Patients With Dm During the Covid-19 Pandemic In Indonesiamentioning

confidence: 99%

“…The epidemic has greatly affected patients with DM, because they are isolated at home, with limited physical activity, irregular eating and sleeping patterns, and weight gain [28]. Due to the concentration of medical resources in epidemic areas and the fear of patients going to hospital, DM treatment is very limited [16]. Local culture will affect diet patterns in people with diabetes, such as in Indonesia, who tend to like sweet foods and are reluctant to refuse food offered by others [29].…”

Section: Diet and Lifestylementioning

confidence: 99%

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Diabetes Mellitus Management during the Coronavirus disease-19 Pandemic: Literature Review

Susilo

Kusbaryanto

Kusumo

2021

Open Access Maced J Med Sci

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AIM: This paper aims to analyze the development of diabetes mellitus (DM) health service management during the coronavirus disease (COVID-19) pandemic situation. DM is a disease that has an increasing prevalence from year to year and has a high morbidity rate. This is not only the case in Indonesia but also globally. The severity of both diseases (DM and COVID-19) then demands the management of comprehensive patient services so as to reduce the risk of morbidity. METHOD: The method used in this writing is the literature review method, carried out by examining journals’ articles published between 2020 and 2021. RESULTS: The results showed that the impact of COVID-19 pandemic prevention will worsen the condition of DM sufferers where there will be the restrictions on the supply of healthy food, changes in eating habits, and access to health services due to concerns about COVID-19. CONCLUSIONS: Hence, the conclusion is, during the COVID-19 pandemic situation, it was necessary to adjust the management of DM services to prevent complications from DM itself by utilizing health technology. The use of telehealth in diabetes service management needs to be developed as a solution to prevent and treat DM during the COVID-19 pandemic.

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Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

Yogasingam

Konnyu

Lépine

et al. 2023

Cochrane Database of Systematic Reviews

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Background There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision‐makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations. Objectives To update existing systematic reviews of diabetes QI programmes and apply novel meta‐analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care. Search methods We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top‐up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section. Selection criteria We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system‐ or provider‐targeted QI strategy alone or in combination with a patient‐targeted strategy. ‐ System‐targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). ‐ Provider‐targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). ‐ Patient‐targeted: patient education (PE); promotion of self‐management (PSM); patient reminders (PR). Patient‐targeted QI strategies needed to occur with a minimum of one provider or system‐targeted strategy. Data collection and analysis We dual‐screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low‐density lipoprotein cholesterol (LDL‐C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta‐regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outco...

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Effect of remote management on comprehensive management of diabetes mellitus during the COVID-19 epidemic

Cited by 36 publications

References 31 publications

The effect of the COVID-19 pandemic on self-management in patients with type 2 diabetics

The effect of the COVID-19 pandemic on self-management in patients with type 2 diabetics

Diabetes Mellitus Management during the Coronavirus disease-19 Pandemic: Literature Review

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

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