Diabetes self-management education after pre-selection of patients: design of a randomised controlled trial.

BACKGROUND: Many self-management programs have been developed so far. Their effectiveness varies. The program 'Beyond Good Intentions' (BGI) is based on proactive coping and has proven to be (cost-) effective in achieving reductions in BMI and blood pressure in screen-detected type 2 diabetes patients up until nine months follow-up. However, its long-term effectiveness in people already known with diabetes is lacking. In addition, its (cost-) effectiveness might increase if people who are likely not to be benefit from the program are excluded in a valid way. Therefore it was aimed to investigate the long-term effects of the educational program BGI on cardiovascular risk, quality of life and diabetes self-management behaviour in a pre-selected group of patients known with type 2 diabetes up to 5 years. METHODS: Randomised controlled trial with 2.5 year follow-up. Adults (≤75 years) with a type 2 diabetes duration between 3 months and 5 years will be included. With the use of a self-management screening tool (SeMaS) their potential barriers of self-management due to depression and/or anxiety will be determined. Based on the results of the SeMaS selection patients will be randomised (1:1) to the BGI-group (n = 53) or the control-group (n = 53). In addition to receiving usual care, patients in the BGI-group will follow the 12-week theory-based self-management program and a booster session a few months thereafter. The control-group will receive care as usual. The primary outcome is change in Body Mass Index after 2.5 years follow-up. Secondary outcomes are HbA1c, lipid profile and systolic blood pressure, (diabetes) quality of life, level of physical activity, dietary intake and medication adherence and proactive coping. Cost-effectiveness will be based on total use of health care resources during the entire study period. Difference between groups in change over time will be analysed according to intention-to-treat analysis. CONCLUSIONS: By differentiating between patients who will and those who are likely not to benefit from the educational program, a more (cost-) effective self-management program might be designed, also on the long-run. Trial registration NTR 5330.

Effectiveness of personalised support for self-management in primary care: a cluster randomised controlled trial.

BACKGROUND: Self-management support is an important component of the clinical management of many chronic conditions. The validated Self-Management Screening questionnaire (SeMaS) assesses individual characteristics that influence a patient's ability to self-manage. AIM: To assess the effect of providing personalised self-management support in clinical practice on patients' activation and health-related behaviours. DESIGN AND SETTING: A cluster randomised controlled trial was conducted in 15 primary care group practices in the south of the Netherlands. METHOD: After attending a dedicated self-management support training session, practice nurses in the intervention arm discussed the results of SeMaS with the patient at baseline, and tailored the self-management support. Participants completed a 13-item Patient Activation Measure (PAM-13) and validated lifestyle questionnaires at baseline and after 6 months. Data, including individual care plans, referrals to self-management interventions, self-monitoring, and healthcare use, were extracted from patients' medical records. Multilevel multiple regression was used to assess the effect on outcomes. RESULTS: The PAM-13 score did not differ significantly between the control (n = 348) and intervention (n = 296) arms at 6 months. In the intervention arm, 29.4% of the patients performed self-monitoring, versus 15.2% in the control arm (effect size r = 0.9, P = 0.01). In the per protocol analysis (control n = 348; intervention n = 136), the effect of the intervention was significant on the number of individual care plans (effect size r = 1.3, P = 0.04) and on self-monitoring (effect size r = 1.0, P = 0.01). CONCLUSION: This study showed that discussing SeMaS and offering tailored support did not affect patient activation or lifestyle, but did stimulate patients to self-monitor and use individual care plans.

Dutch diabetes prevalence estimates (DUDE-1).

BACKGROUND: Recent decades have seen a constant upward projection in the prevalence of diabetes. Attempts to estimate diabetes prevalence rates based on relatively small population samples quite often result in underestimation. The aim of the present study was to investigate whether the Dutch diabetes prevalence estimate of 930 000 for 2013, based on a relatively small sample, still holds true when a larger population is studied using actual prevalence data. METHODS: Data were collected from 92 primary care groups, including the total number of people with and without diabetes in 2013. Patients with diabetes were identified using the International Classification of Primary Care codes T90.02 (diabetes mellitus type 2; T2DM), T90.01 (diabetes mellitus type 1) and T90 (diabetes mellitus). Prevalence data were compared with previous estimates made in 2009. Diabetes prevalence was estimated using linear extrapolation. RESULTS: Complete data were available from 67 (73%) care groups, which together provided care for 7 922 403 subjects; 431 396 patients were coded as having diabetes, of whom 406 183 were coded as having T2DM. Based on these results, the extrapolated Dutch diabetes prevalence was 914 387 (5.45%). CONCLUSIONS: The results show that the previous estimate (reported in 2009), which was based on data collected in 2007, resulted in a <2% (~16 000) overestimation in diabetes prevalence in 2013 compared with the analysis presented. These results indicate that no upward adjustment in Dutch diabetes prevalence estimates is necessary. Repeated large-scale monitoring can help develop more accurate prevalence estimates and improve future prevalence predictions.

Association between quality management and performance indicators in Dutch diabetes care groups: a cross-sectional study.

OBJECTIVES: To enhance the quality of diabetes care in the Netherlands, so-called care groups with three to 250 general practitioners emerged to organise and coordinate diabetes care. This introduced a new quality management level in addition to the quality management of separate general practices. We hypothesised that this new level of quality management might be associated with the aggregate performance indicators on the patient level. Therefore, we aimed to explore the association between quality management at the care group level and its aggregate performance indicators. DESIGN: A cross-sectional study. SETTING: All Dutch care groups (n=97). PARTICIPANTS: 23 care groups provided aggregate register-based performance indicators of all their practices as well as data on quality management measured with a questionnaire filled out by 1 or 2 of their quality managers. PRIMARY OUTCOMES: The association between quality management, overall and in 6 domains ('organisation of care', 'multidisciplinary teamwork', 'patient centredness', 'performance management', 'quality improvement policy' and 'management strategies') on the one hand and 3 process indicators (the percentages of patients with at least 1 measurement of glycated haemoglobin, lipid profile and systolic blood pressure), and 3 intermediate outcome indicators (the percentages of patients with glycated haemoglobin below 53 mmol/mol (7%); low-density lipoprotein cholesterol below 2.5 mmol/L; and systolic blood pressure below 140 mm Hg) by weighted univariable linear regression. RESULTS: The domain 'management strategies' was significantly associated with the percentage of patients with a glycated haemoglobin <53 mmol/mol (ß 0.28 (0.09; 0.46) p=0.01) after correction for multiple testing. The other domains as well as overall quality management were not associated with aggregate process or outcome indicators. CONCLUSIONS: This first exploratory study on quality management showed weak or no associations between quality management of diabetes care groups and their performance. It remains uncertain whether this second layer on quality management adds to better quality of care.

Effects of distance learning on clinical management of LUTS in primary care: a randomised trial.

AIM: To determine the effect of a distance learning programme on general practice management of men with lower urinary tract symptoms (LUTS). METHODS: A cluster randomised controlled trial was performed. General practitioners (GPs) were randomised to a distance learning programme accompanied with educational materials or to a control group only receiving mailed clinical guidelines on LUTS. Clinical management was considered as outcome. RESULTS: Sixty-three GPs registered care management of 187 patients older than 50 years attending the practice because of LUTS. The intervention group showed a lower referral rate to a urologist (OR: 0.08 (95% CI: 0.02-0.40)), but no effect on PSA testing or prescription of medication. PSA testing tended to be requested more frequently by intervention group GPs. Secondary analysis showed patients in the intervention group received more educational materials (OR: 75.6 (95% CI: 13.60-419.90)). CONCLUSIONS: The educational programme had impact on clinical management without changing PSA testing. Distance learning is an promising method for continuing education. PRACTICE IMPLICATIONS: Activating distance learning packages are a potentially effective method for improving professional performance. Emotional matters as PSA testing probably need a more complex approach.

Shared care and the management of lower urinary tract symptoms.

OBJECTIVE: To investigate associations between the level of shared care and the clinical management of patients with uncomplicated lower urinary tract symptoms (LUTS). SUBJECTS AND METHODS: A cross-sectional survey study was conducted comprising all urologists and a random selection of general practitioners (GPs) in the Netherlands. Questionnaire responses were obtained from 182 urologists (70%) and 261 GPs (55%). The first part of the questionnaire established the physicians' characteristics and the second the level of familiarity with the national shared-care guidelines, arrangements between urologists and GPs, and the availability of a shared-care prostate clinic. The third part presented a written case of a 50-year-old man with clinical uncomplicated LUTS, and asked questions about diagnostic and therapeutic care. RESULTS: The clinical management of LUTS by GPs and urologists differed, particularly for diagnostic procedures. Only a minority of GPs (8%) and urologists (18%) had a shared-care clinic at their disposal. Such clinics were associated with an increase in tests ordered by the GP, e.g. creatinine levels (odds ratio, OR 3.83) and PSA levels (OR 5.93), and a decrease in choosing a watchful-waiting strategy for patients with mild symptoms (OR 0.24). Furthermore, urologists more often chose surgical intervention for moderate symptoms (OR 9.80). CONCLUSION: A shared-care clinic may lead to a shift in primary care towards the working style of urologists. This healthcare may not be as cost-effective as expected by policy makers. Prospective studies are needed to provide better insight in the health outcomes and efficiency of shared-care clinics.