Diabetes management

About: Diabetes management is a research topic. Over the lifetime, 6060 publications have been published within this topic receiving 164670 citations.

Challenges in diabetes management in Indonesia: a literature review.

Abstract: The expanding diabetes epidemic worldwide could have potentially devastating effects on the development of healthcare systems and economies in emerging countries, both in terms of direct health care costs and loss of working time and disability. This study aims to review evidence on the burden, expenditure, complications, treatment, and outcomes of diabetes in Indonesia and its implications on the current health system developments. We conducted a comprehensive literature review together with a review of unpublished data from the Ministry of Health and a public health insurer (Askes). Studies presenting evidence on prevalence, incidence, mortality, costs, complications and cost of complications, treatment, and outcomes were included in the analysis. A limited number of international, national and local studies on the burden and cost of diabetes in Indonesia were identified. National survey data suggests that in 2007 the prevalence of diabetes was 5.7%, of which more than 70% of cases were undiagnosed. This estimate hides large intracountry variation. There was very limited data available on direct costs and no data on indirect costs. The most commonly-identified complication was diabetic neuropathy. There were a number of limitations in the data retrieved including the paucity of data representative at the national level, lack of a clear reference date, lack of data from primary care, and lack of data from certain regions of the country. If left unaddressed, the growing prevalence of diabetes in the country will pose a tremendous challenge to the Indonesian healthcare system, particularly in view of the Government’s 2010 mandate to achieve universal health coverage by 2014. Essential steps to address this issue would include: placing diabetes and non-communicable diseases high on the Government agenda and creating a national plan; identifying disparities and priority areas for Indonesia; developing a framework for coordinated actions between all relevant stakeholders.

Change in metabolic control and functional status after hospitalization. Impact of patient activation intervention in diabetic patients.

Abstract: Objective To determine whether a short intervention to enhance patient information seeking and decision making during hospitalization results in improved metabolic control and functional status in patients with diabetes mellitus. Research Design and Methods A randomized clinical trial was conducted in which control patients received a comprehensive 3-day evaluation and educational program, whereas experimental patients received a 45-min patient activation intervention and a 1-h self-administered booster in addition to the program. Metabolic control and functional status were measured at baseline and 4 mo postdischarge. Results During their discharge discussions, experimental patients asked significantly more questions than control patients (7.4 vs. 3.0, P > .001) and 4 mo later reported significantly fewer physical limitations in activities of daily living than the control group ( P = 0.02). Improvement in metabolic control was statistically significant only for experimental patients ( P = 0.02), although their glycosylated hemoglobin levels were not significantly lower than control patients9 at follow-up. The intervention did not diminish physician satisfaction with patient interactions, although it may have increased physician frustration with responsibilities that competed with patient care. CONCLUSIONS These results suggest that the addition of a patient activation intervention to a comprehensive diabetes management program may substantially enhance physical functioning among adults with diabetes mellitus.

Distress and type 2 diabetes-treatment adherence: A mediating role for perceived control.

Abstract: The rising prevalence of type 2 diabetes represents a significant challenge for population health in the US and internationally. Although it is well established that reductions in hemoglobin A1c (A1C), a key index of glycemic control in diabetes, can substantially reduce the risk of diabetes complications (United Kingdom Prospective Diabetes Study, 1998; Nathan et al., 2005), about half of US adults with diabetes are not at goal for A1C (Stark Casagrande et al., 2013) and many report nonadherence to prescribed medications (DiMatteo, 2004; Rubin, 2005). Nonadherence is associated with poor control of A1C, blood pressure and lipids, and increased risk of hospitalization and mortality (e.g., Ho et al., 2006); it is also linked to less effective care – providers are less likely to intensify treatment when indicated for nonadherent patients (Grant et al., 2007). Thus, identification of factors associated with diabetes treatment nonadherence is important and could guide interventions to improve health outcomes. Among patient-level factors, depressive symptoms have been consistently related to treatment nonadherence across a variety of chronic illnesses (DiMatteo, Lepper, Croghan, 2000). A meta-analysis of 47 independent samples showed that higher levels of depressive symptom severity are consistently associated with problematic diabetes self-management across various behavioral domains, including medication adherence (Gonzalez et al., 2008a). Beyond their consistent association with poorer diabetes self-management, depressive symptoms are also related to important diabetes health outcomes over time, such as development of complications (Lin et al., 2010; Black, Markides & Ray, 2003) and mortality (Park, Katon & Wolf, 2013). However, it is important to note that these relationships do not appear to be limited to cases of clinical depression, such as major depressive disorder (MDD). Indeed, depressive symptoms that fall well below MDD diagnostic thresholds are associated with worse self-management both cross-sectionally (Gonzalez et al., 2007) and longitudinally (Gonzalez et al. 2008b); they also predict complications and mortality (Black et al., 2003). Evidence suggests that these ‘subclinical’ depressive symptoms may often represent emotional distress specific to the burdens of living with diabetes rather than a co-morbid depressive mood disorder (Fisher et al., 2007). The need to differentiate diabetes-related emotional distress from depression has led to the development of widely used measures of ‘diabetes distress’ (Polonsky et al., 1995; Polonsky et al., 2005) and of behavioral interventions to directly target diabetes distress (Fisher et al., 2013). Greater precision in distinguishing between depression and diabetes distress could guide the selection of appropriate interventions for patients (Gonzalez, Fisher & Polonsky, 2011). Both diabetes distress and depressive symptoms have been independently associated with medication nonadherence, cross-sectionally and longitudinally, in adults treated for type 2 diabetes (Fisher et al., 2010; Gonzalez et al., 2007; Gonzalez et al., 2008b; Gonzalez, Delahanty, Safren, Meigs & Grant, 2008c; Aikens, 2012). However, the conceptual and measurement overlap between these constructs contributes to inconsistencies in the literature (Gonzalez, Fisher & Polonsky, 2011; Fisher, Gonzalez, & Polonsky, 2014). For example, although early studies showed consistent associations between depressive symptoms and glycemic control (Lustman et al., 2000), more recent studies examining change over time have failed to demonstrate this relationship (e.g., Georgiades et al., 2007; Fisher et al., 2010; Aikens, Perkins, Lipton & Piette, 2009; Aikens, 2012) and suggest that diabetes distress is more closely associated with glycemic control (Aikens, 2012; Fisher et al., 2010). Thus, although emotional distress is clearly implicated in sub-optimal diabetes treatment adherence and outcomes, there is inconsistency in these relationships. Some of this inconsistency may result from an over-reliance on self-report measures of depressive symptoms, which are often more reflective of general distress than clinical depression (Coyne, 1994) and may be particularly vulnerable to overlap with diabetes distress (Gonzalez et al., 2011). Despite the size of the literature on the relationship between emotional distress and diabetes self-management, little research is available to shed light on how distress is linked to diabetes self-management. Social-cognitive variables may play an important role. Negative mood states are known to have a direct influence on self-efficacy, generally reducing perceived ability to carry out activities across various domains (e.g., Kavanagh & Bower, 1985; Salovey & Birnbaum, 1989). Thus, one mechanism linking emotional distress with poor diabetes treatment adherence and health outcomes may involve self-efficacy. Several studies have reported evidence to support self-efficacy as a mediator of the relationship between depressive symptoms and type 2 diabetes self-management (Chao, Nau, Aikens, Taylor, 2005;Wagner, Tennen, Osborn, 2010). Evidence has also been reported for self-efficacy for diabetes management as a mediator of the relationship between depressive symptoms and glycemic control among males with type 2 diabetes (Cherrington, Wallston, Rothman, 2010). Although there is a rich literature that links perceptions of self-efficacy for specific activities to the amount of effort and persistence expended on these activities (Bandura, 1982), these perceptions should be distinguished from one’s perceived ability to meaningfully affect an outcome of interest, or perceived control (Bandura & Wood, 1989; Skinner, 1996). Bandura viewed self-efficacy and perceived control as linked through reciprocal causation (Bandura & Wood, 1989) and described perceived control as a precondition to the optimal execution of efficacious behaviors – “if people approach situations as largely uncontrollable, they are likely to exercise their efficacy weakly and abortively,” whereas, “when people believe the environment is controllable…they are motivated to exercise fully their personal efficacy” (Bandura & Wood, 1989, p.806). Individuals with type 2 diabetes and elevated depressive symptoms report less perceived control over diabetes (Egede & Ellis, 2008; Macrodimitris & Endler, 2001) and greater perceived control is consistently associated with lower A1C (Egede & Ellis, 2008; Macrodimitris & Endler, 2001; Sharry, Moss-Morris, Kendrick, 2011). This relationship may be mediated through improved adherence, as perceived control has also been consistently associated with better diabetes self-management (e.g., Hampson Glasgow, & Toobert, 1990; Skinner & Hampson, 2001). Thus, although evidence supports self-efficacy and perceived control as potential mediators of the distress – diabetes self-management relationship, prior studies have not examined their independent effects. We sought to advance our understanding of the relationships among emotional distress, diabetes treatment adherence, and glycemic control in adults with treated type 2 diabetes by examining direct and indirect pathways linking these variables. We used measures of depressive symptoms and diabetes distress as indicators of emotional distress and evaluated perceived control and self-efficacy as sequential mediators of the relationships between emotional distress, medication adherence and glycemic control.

Efficacy and Reliability of the Continuous Glucose Monitoring System

Abstract: S-19 TIGHT CONTROL OF GLUCOSE has been shown to reduce both microvascular and macrovascular complications of diabetes mellitus,1–3 yet euglycemia is achieved only by a minority of patients.4 Intensive control of blood glucose cannot be achieved without vigilant attention to blood glucose levels.5Consequently, the goal of achieving normoglycemia has stimulated the search for optimal methods of monitoring changes in glucose levels in response to food, exercise, insulin, and antidiabetes medications. When it was first introduced, the technique of self-monitored blood glucose (SMBG) testing of capillary blood via fingerstick represented a major advance in methods of monitoring and improving glycemic control. Now that intensive therapy has become the standard of care for both type 1 and type 2 diabetes, SMBG has been established as a cornerstone of patient management. Current American Diabetes Association (ADA) guidelines recommend SMBG testing at least three to four times each day in patients with type 1 diabetes and at least once a day in patients with type 2 diabetes who cannot be managed with diet and exercise alone.6 Unfortunately, there are many impediments to adequate SMBG practice, including patient education and motivation, as well as improper technique.7,8 But even highly motivated patients who carefully perform frequent fingerstick measurements may miss substantial fluctuations in glucose levels, particularly episodes of nocturnal hypoglycemia. Furthermore, the blood glucose meters that are available today do not consistently achieve either the ADA or the Food and Drug Administration (FDA) goals for meter accuracy.9,10 The recent development of a method for continuously and automatically measuring glucose levels offers a dramatic improvement in the ability to monitor blood glucose—and, thus, intensively manage diabetes. The MiniMed® Continuous Glucose Monitoring System (CGMS, MiniMed Inc., Northridge, CA) is the first commercially available continuous glucose monitor. In this chapter, we summarize the results of a multicenter clinical evaluation of the CGMS, the results of a pilot study demonstrating the efficacy of the CGMS in diabetes management, and the results of a large postmarketing surveillance study confirming the performance of the CGMS during its initial commercial use.