Background The number of type 2 diabetes mellitus (T2DM) patients and related treatment costs are rapidly increasing. Consequentially, more cost-effective and efficient strategies for the treatment of T2DM are needed. One such strategy is improving patients’ self-management. As patients are more and more expected to self-manage their disease, it is important to provide them with suitable self-management support. This way, success of self-management will increase and complications and related costs of T2DM can be reduced. Currently, self-management support is developed mainly from the perspective of health professionals and caregivers, rather than patients. This research focused on gaining a better understanding of patients’ perspectives on self-management and support. Methods Semi-structured interviews, preceded by preparatory assignments, were conducted with ten patients with T2DM treated in Dutch primary care. Results We found that patients experience ‘active’ self-management when recently diagnosed. As time progresses and no problems occur, patients do not experience their disease-related behaviour as self-management. Diabetes has ‘just’ become part of their daily life, now including new routines taking diabetes into account. Conclusions With this knowledge, support solutions can be designed and implemented that better fit the needs, preferences and abilities of patients with T2DM. Electronic supplementary material The online version of this article (10.1186/s12913-019-4384-7) contains supplementary material, which is available to authorized users.

AimTo identify, predict and validate distinct glycaemic trajectories among patients with newly diagnosed type 2 diabetes treated in primary care, as a first step towards more effective patient‐centred care.MethodsWe conducted a retrospective study in two cohorts, using routinely collected individual patient data from primary care practices obtained from two large Dutch diabetes patient registries. Participants included adult patients newly diagnosed with type 2 diabetes between January 2006 and December 2014 (development cohort, n = 10 528; validation cohort, n = 3777). Latent growth mixture modelling identified distinct glycaemic 5‐year trajectories. Machine learning models were built to predict the trajectories using easily obtainable patient characteristics in daily clinical practice.ResultsThree different glycaemic trajectories were identified: (1) stable, adequate glycaemic control (76.5% of patients); (2) improved glycaemic control (21.3% of patients); and (3) deteriorated glycaemic control (2.2% of patients). Similar trajectories could be discerned in the validation cohort. Body mass index and glycated haemoglobin and triglyceride levels were the most important predictors of trajectory membership. The predictive model, trained on the development cohort, had a receiver‐operating characteristic area under the curve of 0.96 in the validation cohort, indicating excellent accuracy.ConclusionsThe developed model can effectively explain heterogeneity in future glycaemic response of patients with type 2 diabetes. It can therefore be used in clinical practice as a quick and easy tool to provide tailored diabetes care.

Aims Limited knowledge exists on the preferences of people with Type 2 diabetes towards diabetes care. Consequently, these care preferences cannot yet be considered in the development of tailored diabetes care approaches. Therefore, this study aimed to assess care preferences and their determinants in people with Type 2 diabetes. Methods A discrete choice experiment was conducted to elicit people's preferences. People with Type 2 diabetes, treated in 30 Dutch primary care practices, were asked to choose repeatedly between two hypothetical diabetes care packages, which differed in six attributes: role division in daily diabetes care planning, lifestyle education method, type of medication management support, consultation frequency, emotional support and time spend on self-management. A mixed-logit model was used to estimate the relative importance of the included attributes. Preference heterogeneity among people with different person-and disease-related characteristics was investigated. Results In total, 288 participants completed the experiment. They preferred to plan their daily diabetes care together with a healthcare provider, to receive individual lifestyle education, medication and emotional support from a healthcare provider, one consultation visit every 3 months and to spend less time on self-management. Participants did not prefer to receive emotional support from a psychologist. Heterogeneity in preferences could partly be explained by differences in sex, education level and glucose-lowering drug use. Conclusion People with Type 2 diabetes show a preference for traditional care models. Emotional support was identified by participants as the most important attribute. It is therefore important to adequately guide them when changes in diabetes care organization are implemented.

Realist evaluation (RE) is an emerging and promising research approach for evaluating integrated care, addressing what works, how, for whom, and in what circumstances. r The rich philosophical foundation of RE, critical realism, can help to systematically unravel an integrated care program's initial theory prior to implementation, as a first step within RE.r RE can be considered a robust methodological asset in integrated care research by facilitating a deeper level of insight into program functioning than traditional forms of evaluation do and by shaping a realistinformed monitoring and evaluation process. Context:The complexity of integrated care and the need for transferable evaluation insights ask for a suitable evaluation paradigm. Realist evaluation (RE), underpinned by the philosophy of critical realism, is a theory-driven approach that addresses what works, how, for whom, and in what circumstances. The current study illustrates the process needed for RE's first step: eliciting the initial program theory (IPT). The TARGET program, a Dutch primary care initiative

AimsTailored, patient-centred innovations are needed in the care for persons with type 2 diabetes mellitus (T2DM), in particular those with insufficient glycaemic control. Therefore, this study sought to assess their biopsychosocial characteristics and explore whether distinct biopsychosocial profiles exist within this subpopulation, which differ in health-related quality of life (HRQoL).MethodsCross-sectional study based on data from The Maastricht Study, a population-based cohort study focused on the aetiology, pathophysiology, complications, and comorbidities of T2DM. We analysed associations and clustering of glycaemic control and HRQoL with 38 independent variables (i.e. biopsychosocial characteristics) in different subgroups and using descriptive analyses, latent class analysis (LCA), and logistic regressions.ResultsIncluded were 840 persons with T2DM, mostly men (68.6%) and with a mean age of 62.6 (±7.7) years. Mean HbA1c was 7.1% (±3.2%); 308 patients (36.7%) had insufficient glycaemic control (HbA1c>7.0% [53 mmol/mol]). Compared to those with sufficient control, these patients had a significantly worse-off status on multiple biopsychosocial factors, including self-efficacy, income, education and several health-related characteristics. Two ‘latent classes’ were identified in the insufficient glycaemic control subgroup: with low respectively high HRQoL. Of the two, the low HRQoL class comprised about one-fourth of patients and had a significantly worse biopsychosocial profile.ConclusionsInsufficient glycaemic control, particularly in combination with low HRQoL, is associated with a generally worse biopsychosocial profile. Further research is needed into the complex and multidimensional causal pathways explored in this study, so as to increase our understanding of the heterogeneous care needs and preferences of persons with T2DM, and translate this knowledge into tailored care and support arrangements.