Jaco Voorham

Effects of a patient oriented decision aid for prioritising treatment goals in diabetes: pragmatic randomised controlled trial.

Objective To assess the effects of a patient oriented decision aid for prioritising treatment goals in diabetes compared with usual care on patient empowerment and treatment decisions. Design Pragmatic randomised controlled trial. Setting 18 general practices in the north of the Netherlands. Participants 344 patients with type 2 diabetes aged ≤65 years at the time of diagnosis and managed in primary care between April 2011 and August 2012: 225 were allocated to the intervention group and 119 to the usual care group. Intervention The intervention comprised a decision aid for people with diabetes, with individually tailored risk information and treatment options for multiple risk factors. The aid was intended to empower patients to prioritise between clinical domains and to support treatment decisions. It was offered to participants before a regular diabetes check-up and to their healthcare provider during the consultation. Four different formats of the decision aid were included for additional explorative analyses. Main outcome measures The primary outcome was the effects on patient empowerment for setting and achieving goals. The secondary outcomes were changes in the prescribing of drugs to regulate glucose, blood pressure, lipids, and albuminuria. Data were collected through structured questionnaires and automated data extraction from electronic health records during six months before and after the intervention. Results Of all intervention participants, 103 (46%) reported to have received the basic elements of the intervention. For the primary outcome analysis, 199 intervention and 107 control patients with sufficient baseline and follow-up data could be included. The mean empowerment score increased 0.1 on a 5 point scale in the overall intervention group, which was not significantly different from that of the control group (mean difference after adjusting for baseline 0.039, 95% confidence interval −0.056 to 0.134). Lipid regulating drug treatment was intensified in 25% of intervention and 12% of control participants with increased cholesterol levels, which did not reach significance when the intervention was compared with the usual care group (odds ratio 2.54, 95% confidence interval 0.89 to 7.23). Prespecified explorative analyses showed that this effect was significant for the printed version of the decision aid in comparison to usual care (3.90, 1.29 to 11.80). No relevant or significant changes were seen for other treatments. Conclusion We found no evidence that the patient oriented treatment decision aid improves patient empowerment by an important amount. The aid was not used to its full extent in a substantial number of participants. Trial registration Dutch trial register NTR1942.

Medication Adherence Affects Treatment Modifications in Patients With Type 2 Diabetes

BACKGROUND Low rates of treatment modification in patients with insufficiently controlled risk factors are common in type 2 diabetes. Although adherence problems are often mentioned in surveys as a reason for not intensifying treatment, observational studies have shown inconclusive results. OBJECTIVE To assess how medication adherence affects treatment modifications for hypertension and hyperglycemia in patients with type 2 diabetes. METHODS This was a cohort study of 11,268 primary care patients with type 2 diabetes in the Netherlands. Inclusion criteria were diagnosis before 2007, ≥1 prescription to antihypertensive or glucose-regulating medication in the preceding 6 months, and a systolic blood pressure level ≥140 mm Hg or glycosylated hemoglobin ≥7% in 2007. Patients on maximal treatment were excluded. Treatment modifications as observed from prescriptions were classified as none, dose increase, dose decrease, class switch, class addition, or class discontinuation. Refill adherence was assessed as medication possession ratio or length of last gap between refills. We performed multilevel multinomial regression analysis to test for associations. RESULTS We included 4980 diabetic patients with elevated blood pressure and 2945 diabetic patients with elevated glycosylated hemoglobin levels. Patients with lower adherence for antihypertensive drugs were more likely to have those medications discontinued (odds ratio [OR] for every 10% lower medication possession ratio =1.22; 95% CI, 1.11-1.33) or the dose decreased (OR = 1.14; CI 1.01-1.28). For glucose-regulating medication, dose increases (OR = 0.92; 95% CI, 0.85-0.98) and medication additions (OR = 0.90; 95% CI, 0.82-0.99) were less likely in patients with lower adherence levels. CONCLUSIONS Low adherence inhibits the intensification of glucose-regulating but not antihypertensive medication in type 2 diabetic patients with insufficiently controlled risk factors in the Netherlands. Adherence problems may lead to diminished or even discontinued antihypertensive treatment.

Cross-sectional versus sequential quality indicators of risk factor management in patients with type 2 diabetes

Background:The fairness of quality assessment methods is under debate. Quality indicators incorporating the longitudinal nature of care have been advocated but their usefulness in comparison to more commonly used cross-sectional measures is not clear. Aims:To compare cross-sectional and sequential quality indicators for risk factor management in patients with type 2 diabetes. Methods:The study population consisted of 1912 patients who received diabetes care from one of 40 general practitioners in The Netherlands. Clinical outcomes, prescriptions, and demographic data were collected from electronic medical records. Quality was assessed for glycemic, blood pressure, and lipid control using indicators focusing on clinical outcomes, and treatment in relation to outcomes. Indicator results were compared with a reference method based on national guidelines for general practice. Results:According to the reference method, 76% of the patients received management as recommended for glycemic control, 58% for blood pressure control, and 67% for lipid control. Cross-sectional indicators looking at patients adequately controlled gave estimates that were 10–25% lower than the reference method. Estimates from indicators focusing on uncontrolled patients receiving treatment were 10–40% higher than the reference method for blood pressure and glycemic control. Sequential indicators focusing on improvement in clinical outcomes or assessing treatment modifications in response to poor control gave results closer to the reference method. Conclusions:Sequential indicators are valuable for estimating quality of risk factor management in patients with diabetes. Such indicators may provide a more accurate and fair judgment than currently used cross-sectional indicators.

Differential effects of comorbidity on antihypertensive and glucose-regulating treatment in diabetes mellitus--a cohort study.

Background Comorbidity is often mentioned as interfering with “optimal” treatment decisions in diabetes care. It is suggested that diabetes-related comorbidity will increase adequate treatment, whereas diabetes-unrelated comorbidity may decrease this process of care. We hypothesized that these effects differ according to expected priority of the conditions. Methods We evaluated the relationship between comorbidity and treatment intensification in a study of 11,248 type 2 diabetes patients using the GIANTT (Groningen Initiative to Analyse type 2 diabetes Treatment) database. We formed a cohort of patients with a systolic blood pressure ≥140 mmHg (6,820 hypertensive diabetics), and a cohort of patients with an HbA1c ≥7% (3,589 hyperglycemic diabetics) in 2007. We differentiated comorbidity by diabetes-related or unrelated conditions and by priority. High priority conditions include conditions that are life-interfering, incident or requiring new medication treatment. We performed Cox regression analyses to assess association with treatment intensification, defined as dose increase, start, or addition of drugs. Results In both the hypertensive and hyperglycemic cohort, only patients with incident diabetes-related comorbidity had a higher chance of treatment intensification (HR 4.48, 2.33–8.62 (p<0.001) for hypertensives; HR 2.37, 1.09–5.17 (p = 0.030) for hyperglycemics). Intensification of hypertension treatment was less likely when a new glucose-regulating drug was prescribed (HR 0.24, 0.06–0.97 (p = 0.046)). None of the prevalent or unrelated comorbidity was significantly associated with treatment intensification. Conclusions Diabetes-related comorbidity induced better risk factor treatment only for incident cases, implying that appropriate care is provided more often when complications occur. Diabetes-unrelated comorbidity did not affect hypertension or hyperglycemia management, even when it was incident or life-interfering. Thus, the observed “undertreatment” in diabetes care cannot be explained by constraints caused by such comorbidity.

A systematic literature review: prescribing indicators related to type 2 diabetes mellitus and cardiovascular risk management

Valid prescribing indicators (PI) are needed for reliable assessment of prescribing quality. The purpose of this study is to describe the validity of existing PI for type 2 diabetes mellitus and cardiovascular risk management.

Do Treatment Quality Indicators Predict Cardiovascular Outcomes in Patients with Diabetes

Background Landmark clinical trials have led to optimal treatment recommendations for patients with diabetes. Whether optimal treatment is actually delivered in practice is even more important than the efficacy of the drugs tested in trials. To this end, treatment quality indicators have been developed and tested against intermediate outcomes. No studies have tested whether these treatment quality indicators also predict hard patient outcomes. Methods A cohort study was conducted using data collected from >10.000 diabetes patients in the Groningen Initiative to Analyze Type 2 Treatment (GIANTT) database and Dutch Hospital Data register. Included quality indicators measured glucose-, lipid-, blood pressure- and albuminuria-lowering treatment status and treatment intensification. Hard patient outcome was the composite of cardiovascular events and all-cause death. Associations were tested using Cox regression adjusting for confounding, reporting hazard ratios (HR) with 95% confidence intervals. Results Lipid and albuminuria treatment status, but not blood pressure lowering treatment status, were associated with the composite outcome (HR = 0.77, 0.67–0.88; HR = 0.75, 0.59–0.94). Glucose lowering treatment status was associated with the composite outcome only in patients with an elevated HbA1c level (HR = 0.72, 0.56–0.93). Treatment intensification with glucose-lowering but not with lipid-, blood pressure- and albuminuria-lowering drugs was associated with the outcome (HR = 0.73, 0.60–0.89). Conclusion Treatment quality indicators measuring lipid- and albuminuria-lowering treatment status are valid quality measures, since they predict a lower risk of cardiovascular events and mortality in patients with diabetes. The quality indicators for glucose-lowering treatment should only be used for restricted populations with elevated HbA1c levels. Intriguingly, the tested indicators for blood pressure-lowering treatment did not predict patient outcomes. These results question whether all treatment indicators are valid measures to judge quality of health care and its economics.

Association Between Performance Measures and Glycemic Control Among Patients With Diabetes in a Community-wide Primary Care Cohort

Background:Performance measures are used for assessing quality of care. Higher performance shown by these measures is expected to reflect better care, but little is known whether they predict better patient outcomes. Objective:To assess the predictive value of performance measures of glucose management on glycemic control, and evaluate the impact of patient characteristics on this association. Research Design:Cohort study (2007–2009). Subjects:A total of 15,454 type 2 diabetes patients (mean age, 66.5 y; 48% male) from the GIANTT cohort. Measures:We included performance measures assessing frequency of HbA1c monitoring, glucose-lowering treatment status, and treatment intensification. Associations between performance and glycemic control were tested using multivariate linear regression adjusted for confounding, reporting estimated differences in HbA1c with 95% confidence intervals (CI). Impact of patient characteristics was examined through interactions. Results:Annual HbA1c monitoring was associated with better glycemic control when compared with no such monitoring (HbA1c −0.29%; 95% CI −0.37, −0.22). This association lost significance in patients with lower baseline HbA1c, older age, and without macrovascular comorbidity. Treatment status was associated with better glycemic control only in patients with elevated baseline HbA1c. Treatment intensification after elevated HbA1c levels was associated with better glycemic control compared with no intensification (HbA1c −0.21; 95% CI −0.26, −0.16). Conclusions:Performance measures of annual HbA1c monitoring and of treatment intensification did predict better patient outcomes, whereas the measure of treatment status did not. Predictive value of annual monitoring and of treatment status varied across patient characteristics, and it should be used with caution when patient characteristics cannot be taken into account.

Is albuminuria screening and treatment optimal in patients with type 2 diabetes in primary care? Observational data of the GIANTT cohort

BACKGROUND Failure of diagnosing and treatment of albuminuria play a role in morbidity and mortality in type 2 diabetes (T2DM). We evaluated guideline adherence and factors associated with albuminuria screening and treatment in T2DM patients in primary care. METHODS Guidelines recommend annual measurement of albuminuria and, if increased, treatment with renin-angiotensin-aldosterone system (RAAS) blockers. We performed a cohort study of T2DM patients managed by 182 Dutch general practitioners (GPs; Groningen Initiative to Analyse Type 2 diabetes Treatment database), and evaluated guideline adherence in the years 2007-2009. We assessed whether demographic, clinical, organizational or provider factors determined guideline adherence with multilevel analyses. RESULTS Data were available for 14 120 T2DM patients [47.6% male, mean age 67.3 ± 11.7 years, median diabetes duration 6 (IQR: 3-10) years]. The albumin-creatinine ratio (ACR) was measured in 45.2% in 2007, 57.4% in 2008 and 56.8% in 2009. Only 23.7% of all patients were measured every year and 21.4% were never measured. The ACR was more often measured in patients <75 years, with a previous ACR measurement, using anti-diabetic medication, and receiving additional care by a diabetes support facility. RAAS treatment was prescribed to 78.4% of patients with prevalent micro/macroalbuminuria, 66.5% with incident micro/macroalbuminuria, 59.3% with normoalbuminuria and 52.1% of those without ACR measurements. In those not treated with RAAS blockers, it was initiated in 14.3, 12.3, 3.0 and 2.3%, respectively. The presence of micro/macroalbuminuria, higher blood pressure, incidence of cardiovascular events and treatment with antihypertensive medication were the determinants of RAAS-treatment initiation. CONCLUSIONS Guideline implementation regarding the management of albuminuria in T2DM patients in primary care should be further improved.

The effect of a patient-oriented treatment decision aid for risk factor management in patients with diabetes (PORTDA-diab): study protocol for a randomised controlled trial

BackgroundTo improve risk factor management in diabetes, we need to support effective interactions between patients and healthcare providers. Our aim is to develop and evaluate a treatment decision aid that offers personalised information on treatment options and outcomes, and is intended to empower patients in taking a proactive role in their disease management. Important features are: (1) involving patients in setting goals together with their provider; (2) encourage them to prioritise on treatments that maximise relevant outcomes; and (3) integration of the decision aid in the practice setting and workflow. As secondary aim, we want to evaluate the impact of different presentation formats, and learn more from the experiences of the healthcare providers and patients with the decision aid.Methods and designWe will conduct a randomised trial comparing four formats of the decision aid in a 2×2 factorial design with a control group. Patients with type 2 diabetes managed in 18 to 20 primary care practices in The Netherlands will be recruited. Excluded are patients with a recent myocardial infarction, stroke, heart failure, angina pectoris, terminal illness, cognitive deficits, >65 years at diagnosis, or not able to read Dutch. The decision aid is offered to the patients immediately before their quarterly practice consultation. The same decision information will be available to the healthcare provider for use during consultation. In addition, the providers receive a set of treatment cards, which they can use to discuss the benefits and risks of different options. Patients in the control group will receive care as usual. We will measure the effect of the intervention on patient empowerment, satisfaction with care, beliefs about medication, negative emotions, health status, prescribed medication, and predicted cardiovascular risk. Data will be collected with questionnaires and automated extraction from medical records in 6 months before and after the intervention.DiscussionThis decision aid is innovative in supporting patients and their healthcare providers to make shared decisions about multiple treatments, using the patient’s data from electronic medical records. The results can contribute to the further development and implementation of electronic decision support tools for the management of chronic diseases.Trial registrationDutch Trial register NTR1942.

Identifying targets to improve treatment in type 2 diabetes; the Groningen Initiative to aNalyse Type 2 diabetes Treatment (GIANTT) observational study

Assessment of quality of cardiometabolic risk management in diabetes in primary care.