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      Are home visits an effective method for diabetes management? A quantitative systematic review and meta‐analysis

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          Abstract

          Aims/Introduction

          Previous reviews have revealed uncertainty regarding the effectiveness of home visit interventions for managing diabetes. Therefore, we carried out a quantitative systematic review and meta‐analysis to evaluate the effects of home visit interventions among patients with diabetes.

          Materials and Methods

          We searched various electronic databases (PubMed, EMBASE, Cochrane Library, Web of Science, CINAHL, Wanfang and Chinese scientific full‐text databases) from their inception until March 2016. We included randomized controlled trials that included patients with diabetes, and evaluated the effects of home visit programs on glycated hemoglobin concentrations. Two reviewers independently used the Cochrane Collaboration methods to assess the included studies’ risk of bias and quality.

          Results

          We included seven randomized controlled trials with 686 participants. Compared with the usual care, the home visit group showed a greater reduction in glycated hemoglobin concentrations (mean difference −0.79% [−9 mmol/mol], 95% confidence interval [ CI]: −0.93 to −0.25% [11 to −3 mmol/mol]; < 0.05; I = 0%), systolic blood pressure (mean difference −5.94 mmHg, 95% confidence interval −11.34 to −0.54 mmHg) and diastolic blood pressure (mean difference −6.32 mmHg, 95% confidence interval −12.00 to −0.65 mmHg). Furthermore, home visits improved quality of life, high‐density lipoprotein, low‐density lipoprotein, total triglycerides and self‐management. However, there were no significant differences between the two groups in their bodyweight, total cholesterol, body mass index and self‐efficacy.

          Conclusion

          Home visits were associated with improved glycemic control and reduced cardiovascular risk factors, which shows that it is an effective method for diabetes management.

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          Most cited references36

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          Economic costs of diabetes in the U.S. In 2007.

          (2008)
          The prevalence of diabetes continues to grow, with the number of people in the U.S. with diagnosed diabetes now reaching 17.5 million. The objectives of this study are to quantify the economic burden of diabetes caused by increased health resource use and lost productivity, and to provide a detailed breakdown of the costs attributed to diabetes. This study uses a prevalence-based approach that combines the demographics of the population in 2007 with diabetes prevalence rates and other epidemiological data, health care costs, and economic data into a Cost of Diabetes Model. Health resource use and associated medical costs are analyzed by age, sex, type of medical condition, and health resource category. Data sources include national surveys and claims databases, as well as a proprietary database that contains annual medical claims for 16.3 million people in 2006. The total estimated cost of diabetes in 2007 is $174 billion, including $116 billion in excess medical expenditures and $58 billion in reduced national productivity. Medical costs attributed to diabetes include $27 billion for care to directly treat diabetes, $58 billion to treat the portion of diabetes-related chronic complications that are attributed to diabetes, and $31 billon in excess general medical costs. The largest components of medical expenditures attributed to diabetes are hospital inpatient care (50% of total cost), diabetes medication and supplies (12%), retail prescriptions to treat complications of diabetes (11%), and physician office visits (9%). People with diagnosed diabetes incur average expenditures of $11,744 per year, of which $6,649 is attributed to diabetes. People with diagnosed diabetes, on average, have medical expenditures that are approximately 2.3 times higher than what expenditures would be in the absence of diabetes. For the cost categories analyzed, approximately $1 in $5 health care dollars in the U.S. is spent caring for someone with diagnosed diabetes, while approximately $1 in $10 health care dollars is attributed to diabetes. Indirect costs include increased absenteeism ($2.6 billion) and reduced productivity while at work ($20.0 billion) for the employed population, reduced productivity for those not in the labor force ($0.8 billion), unemployment from disease-related disability ($7.9 billion), and lost productive capacity due to early mortality ($26.9 billion). The actual national burden of diabetes is likely to exceed the $174 billion estimate because it omits the social cost of intangibles such as pain and suffering, care provided by nonpaid caregivers, excess medical costs associated with undiagnosed diabetes, and diabetes-attributed costs for health care expenditures categories omitted from this study. Omitted from this analysis are expenditure categories such as health care system administrative costs, over-the-counter medications, clinician training programs, and research and infrastructure development. The burden of diabetes is imposed on all sectors of society-higher insurance premiums paid by employees and employers, reduced earnings through productivity loss, and reduced overall quality of life for people with diabetes and their families and friends.
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            Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study

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              Health-related quality of life in diabetes: The associations of complications with EQ-5D scores

              Background The aim of this study was to describe how diabetes complications influence the health-related quality of life of individuals with diabetes using the individual EQ-5D dimensions and the EQ-5D index. Methods We mailed a questionnaire to 1,000 individuals with diabetes type 1 and 2 in Norway. The questionnaire had questions about socio-demographic characteristics, use of health care, diabetes complications and finally the EQ-5D descriptive system. Logistic regressions were used to explore determinants of responses in the EQ-5D dimensions, and robust linear regression was used to explore determinants of the EQ-5D index. Results In multivariate analyses the strongest determinants of reduced MOBILITY were neuropathy and ischemic heart disease. In the ANXIETY/DEPRESSION dimension of the EQ-5D, "fear of hypoglycaemia" was a strong determinant. For those without complications, the EQ-5D index was 0.90 (type 1 diabetes) and 0.85 (type 2 diabetes). For those with complications, the EQ-5D index was 0.68 (type 1 diabetes) and 0.73 (type 2 diabetes). In the linear regression the factors with the greatest negative impact on the EQ-5D index were ischemic heart disease (type 1 diabetes), stroke (both diabetes types), neuropathy (both diabetes types), and fear of hypoglycaemia (type 2 diabetes). Conclusions The EQ-5D dimensions and the EQ-5D seem capable of capturing the consequences of diabetes-related complications, and such complications may have substantial impact on several dimensions of health-related quality of life (HRQoL). The strongest determinants of reduced HRQoL in people with diabetes were ischemic heart disease, stroke and neuropathy.
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                Author and article information

                Contributors
                hanlin@lzu.edu.cn
                Journal
                J Diabetes Investig
                J Diabetes Investig
                10.1111/(ISSN)2040-1124
                JDI
                Journal of Diabetes Investigation
                John Wiley and Sons Inc. (Hoboken )
                2040-1116
                2040-1124
                11 March 2017
                September 2017
                : 8
                : 5 ( doiID: 10.1111/jdi.2017.8.issue-5 )
                : 701-708
                Affiliations
                [ 1 ] Nursing Department Gansu Provincial Hospital Lanzhou Gansu China
                [ 2 ] School of Nursing Lanzhou University Lanzhou Gansu China
                [ 3 ] Medical College Northwest University for Nationalities Lanzhou Gansu China
                [ 4 ] Department of Endocrinology Gansu Provincial Hospital Lanzhou Gansu China
                [ 5 ] Evidence‐Based Medicine Center School of Basic Medical Sciences Lanzhou University Lanzhou Gansu China
                [ 6 ] Department of Cardiology Gansu Provincial Hospital Lanzhou Gansu China
                [ 7 ] School of Public Health Lanzhou University Lanzhou Gansu China
                [ 8 ] School of Nursing Gansu University of Chinese Medicine Lanzhou Gansu China
                [ 9 ] Nursing Department Affiliated Hospital of Medical College of Chinese People's Armed Police Force Tianjin China
                Author notes
                [*] [* ] Correspondence

                Lin Han

                Tel.: +86‐0931‐8281971

                Fax: +86‐0931‐8281971

                E‐mail address: hanlin@ 123456lzu.edu.cn

                These authors contributed equally to this work.

                Article
                JDI12630
                10.1111/jdi.12630
                5583953
                28109182
                a7ad4518-4877-48de-8b87-48ddd53c3561
                © 2017 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd

                This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

                History
                : 09 August 2016
                : 27 December 2016
                : 17 January 2017
                Page count
                Figures: 4, Tables: 2, Pages: 8, Words: 5342
                Funding
                Funded by: National Nature Science Foundation of China
                Award ID: 71363004
                Award ID: 71663002
                Funded by: Fundamental Research Funds for the Central Universities
                Award ID: 31920150046
                Categories
                Original Article
                Articles
                Clinical Science and Care
                Custom metadata
                2.0
                jdi12630
                September 2017
                Converter:WILEY_ML3GV2_TO_NLMPMC version:5.1.9 mode:remove_FC converted:05.09.2017

                diabetes,home visit,meta‐analysis
                diabetes, home visit, meta‐analysis

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