9 research outputs found

    Differential Effects of Comorbidity on Antihypertensive and Glucose-Regulating Treatment in Diabetes Mellitus – A Cohort Study

    Get PDF
    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

    Inhaled corticosteroids in COPD and onset of type 2 diabetes and osteoporosis: matched cohort study

    Get PDF
    Some studies suggest an association between onset and/or poor control of type 2 diabetes mellitus and inhaled corticosteroid (ICS) therapy for chronic obstructive pulmonary disease (COPD), and also between increased fracture risk and ICS therapy; however, study results are contradictory and these associations remain tentative and incompletely characterized. This matched cohort study used two large UK databases (1983–2016) to study patients (≥ 40 years old) initiating ICS or long-acting bronchodilator (LABD) for COPD from 1990–2015 in three study cohorts designed to assess the relation between ICS treatment and (1) diabetes onset (N = 17,970), (2) diabetes progression (N = 804), and (3) osteoporosis onset (N = 19,898). Patients had ≥ 1-year baseline and ≥ 2-year outcome data. Matching was via combined direct matching and propensity scores. Conditional proportional hazards regression, adjusting for residual confounding after matching, was used to compare ICS vs. LABD and to model ICS exposures. Median follow-up was 3.7–5.6 years/treatment group. For patients prescribed ICS, compared with LABD, the risk of diabetes onset was significantly increased (adjusted hazard ratio 1.27; 95% CI, 1.07–1.50), with overall no increase in risk of diabetes progression (adjusted hazard ratio 1.04; 0.87–1.25) or osteoporosis onset (adjusted hazard ratio 1.13; 0.93–1.39). However, the risks of diabetes onset, diabetes progression, and osteoporosis onset were all significantly increased, with evident dose–response relationships for all three outcomes, at mean ICS exposures of 500 µg/day or greater (vs. < 250 µg/day, fluticasone propionate–equivalent). Long-term ICS therapy for COPD at mean daily exposure of ≥ 500 µg is associated with an increased risk of diabetes, diabetes progression, and osteoporosis

    Development and initial validation of prescribing quality indicators for patients with chronic kidney disease

    No full text
    BACKGROUND: Quality assessment is a key element for improving the quality of care. Currently, a comprehensive indicator set for measuring the quality of medication treatment in patients with chronic kidney disease (CKD) is lacking. Our aim was to develop and validate a set of prescribing quality indicators (PQIs) for CKD care, and to test the feasibility of applying this set in practice. METHODS: Potential indicators were based on clinical practice guidelines and evaluated using the RAND/UCLA Appropriateness Method. This is a structured process in which an expert panel assesses the validity of the indicators. Feasibility was tested in a Dutch primary care database including >4500 diabetes patients with CKD. RESULTS: An initial list of 22 PQIs was assessed by 12 experts. After changing 10 PQIs, adding 2 and rejecting 8, a final list of 16 indicators was accepted by the expert panel as valid. These PQIs focused on the treatment of hypertension, albuminuria, mineral and bone disorder, statin prescribing and possible unsafe medication. The indicators were successfully applied to measure treatment quality in the primary care database, but for some indicators the number of eligible patients was too small for reliable calculation. Results showed that there was room for improvement in the treatment quality of this population. CONCLUSIONS: We developed a set of 16 PQIs for measuring the quality of treatment in CKD patients, which had sufficient content and face validity as well as operational feasibility. These PQIs can be used to point out priority areas for improvement

    Development and validation of prescribing quality indicators for patients with type 2 diabetes

    No full text
    Aim: Quality indicators are used to measure whether healthcare professionals act according to guidelines, but few indicators focus on the quality of pharmacotherapy for diabetes. The aim of this study was to develop and validate a set of prescribing quality indicators (PQIs) for type 2 diabetes in primary care, and to apply this set in practice. To take into account the stepwise treatment of chronic disease, clinical action indicators were specifically considered. Methods: Potential PQIs were derived from clinical practice guidelines and evaluated using the RAND/UCLA Appropriateness Method, a modified Delphi panel. Thereafter, the feasibility of calculating the PQIs was tested in two large Dutch primary care databases including >80 000 diabetes patients in 2012. Results: 32 PQIs focusing on treatment with glucose, lipid, blood pressure and albuminuria lowering drugs, and on vaccination, medication safety and adherence were assessed by ten experts. After the Delphi panel, the final list of twenty PQIs was tested for feasibility. All PQIs definitions were feasible for measuring the quality of medication treatment using these databases. Indicator scores ranged from 18.8% to 90.8% for PQIs focusing on current medication use, clinical action and medication choice, and from 2.1% to 37.2% for PQIs focusing on medication safety. Discussion and conclusions: Twenty PQIs focusing on treatment with glucose, lipid, blood pressure and albuminuria lowering drugs, and on medication safety in type 2 diabetes were developed, considered valid and operationally feasible. Results showed room for improvement, especially in initiation and intensification of treatment as measured with clinical action indicators

    Do Treatment Quality Indicators Predict Cardiovascular Outcomes in Patients with Diabetes?

    Get PDF
    <p>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.</p><p>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.</p><p>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).</p><p>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.</p>

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

    No full text
    <p>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.</p><p>Guidelines recommend annual measurement of albuminuria and, if increased, treatment with reninangiotensinaldosterone 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 20072009. We assessed whether demographic, clinical, organizational or provider factors determined guideline adherence with multilevel analyses.</p><p>Data were available for 14 120 T2DM patients [47.6 male, mean age 67.3 11.7 years, median diabetes duration 6 (IQR: 310) years]. The albumincreatinine 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.</p><p>Guideline implementation regarding the management of albuminuria in T2DM patients in primary care should be further improved.</p>
    corecore