Is guideline-adherent prescribing associated with quality of life in patients with type 2 diabetes?

BACKGROUND: Guideline-adherent prescribing for treatment of multiple risk factors in type 2 diabetes (T2D) patients is expected to improve clinical outcomes. However, the relationship to Health-Related Quality of Life (HRQoL) is not straightforward since guideline-adherent prescribing can increase medication burden. OBJECTIVES: To test whether guideline-adherent prescribing and disease-specific medication burden are associated with HRQoL in patients with T2D. METHODS: Cross-sectional study including 1,044 T2D patients from the e-VitaDM/ZODIAC study in 2012 in the Netherlands. Data from the diabetes visit, such as laboratory and physical examinations and prescribed medication, and from two HRQoL questionnaires, the EuroQol 5 Dimensions 3 Levels (EQ5D-3L) and the World Health Organization Well-Being Index (WHO-5) were collected. Twenty indicators assessing prescribing of recommended glucose lowering drugs, statins, antihypertensives and renin-angiotensin-aldosterone system (RAAS)-inhibitors and potentially inappropriate drugs from a validated diabetes indicator set were included. Disease-specific medication burden was assessed using a modified version of the Medication Regimen Complexity Index (MRCI). Associations were tested with regression models, adjusting for age, gender, diabetes duration, comorbidity, body mass index and smoking. RESULTS: The mean MRCI was 7.1, the median EQ5D-3L-score was 0.86 and the mean WHO-5 score was 72. Seven indicators included too few patients and were excluded from the analysis. The remaining thirteen indicators focusing on recommended start, intensification, current and preferred use of glucose lowering drugs, statins, antihypertensives, RAAS inhibitors, and on inappropriate prescribing of glibenclamide and dual RAAS blockade were not significantly associated with HRQoL. Finally, also the MRCI was not associated with HRQoL. CONCLUSIONS: We found no evidence for associations between guideline-adherent prescribing or disease-specific medication burden and HRQoL in T2D patients. This gives no rise to refrain from prescribing intensive treatment in T2D patients as recommended, but the interpretation of these results is limited by the cross-sectional study design and the selection of patients included in some indicators.

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

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.

Reducing antibiotic prescriptions for respiratory tract infections in family practice: results of a cluster randomized controlled trial evaluating a multifaceted peer-group-based intervention.

Irrational antibiotic use for respiratory tract infections (RTI) is a major driver of bacterial resistance. The aim of this study was to evaluate the effect of a multifaceted peer-group based intervention aiming to reduce RTI-related antibiotic prescriptions in family practice. This was a cluster randomized controlled trial with pre- and follow-up measurement. The intervention was implemented through PharmacoTherapy Audit Meetings (PTAM) in which family physicians (FPs) and pharmacists collaborate. Four PTAM groups received the intervention consisting of: (1) FP communication skills training, including communication about delayed prescribing; (2) implementation of antibiotic prescribing agreements in FPs' Electronic Prescribing Systems; (3) quarterly feedback figures for FPs. Four other PTAM groups were matched controls. Primary outcome measure was the number of RTI-related antibiotic prescriptions after the intervention, assessed with multilevel linear regression analyses. Total number and number of prescriptions stratified by age (under/over 12 years) were analysed. At baseline, the average total number of RTI-related antibiotic prescriptions per 1,000 patients was 207.9 and 176.7 in the intervention and control PTAM groups, respectively. At follow-up, FPs in both the intervention and control groups prescribed significantly less antibiotics. For adolescents and adults, the drop in number of antibiotic prescription was significantly larger in the intervention groups (-27.8 per 1,000 patients) than the control groups (-7.2 per 1,000 patients; P<0.05). This multifaceted peer-group-based intervention was effective in reducing the number of RTI-related antibiotic prescriptions for adolescents and adults. To affect antibiotic prescribing in children other methods are needed.

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.

Effect of an integrated primary care model on the management of middle-aged and old patients with obstructive lung diseases.

OBJECTIVE: To investigate the effect of a primary care model for COPD on process of care and patient outcome. DESIGN: Controlled study with delayed intervention in control group. SETTING: The GP delegates tasks to a COPD support service (CSS) and a practice nurse. The CSS offers logistic support to the practice through a patient register and recall system for annual history-taking and lung function measurement. It also forms the link with the chest physician for diagnostic and therapeutic advice. The practice nurse's most important tasks are education and counselling. SUBJECTS: A total of 44 practices (n =22 for intervention and n =22 for control group) and 260 of their patients > or = 40 years with obstructive lung diseases. RESULTS: Within the intervention group planned visits increased from 16% to 44% and from 19% to 25% in the control condition (difference between groups p =0.014). Annual lung function measurement rose from 17% to 67% in the intervention and from 11% to 18% in the control group (difference between groups p =0.001). Compared with control, more but not statistically significant smokers received periodic advice to quit smoking (p =0.16). At baseline 41% of the intervention group were using their inhalers correctly and this increased to 54% after two years; it decreased in the control group from 47 to 29% (difference between groups p =0.002). The percentage of patients without exacerbation did not change significantly compared with the control condition. The percentage of the intervention group not needing emergency medication rose from 79% to 84% but decreased in the controls from 81 to 76% (difference between groups p =0.08). CONCLUSION: Combining different disciplines in one model has a positive effect on compliance with recommendations for monitoring patients, and improves the care process and some patient outcomes.

Logistic support service improves processes and outcomes of diabetes care in general practice.

BACKGROUND: Guidelines for type 2 diabetes care in general practice are well known and accepted, but the implementation falls short. OBJECTIVE: To implement these guidelines by introducing a diabetes support service (DSS) to support the care delivered by the GP. METHODS: A controlled, non-randomised study with delayed intervention in the control group; 78 GPs (n=51 for the intervention and n=21 for the control group) in the south of the Netherlands and 613 of their type 2 diabetic patients participated. Data were collected on the frequency, content and results of the check-ups (fasting blood glucose, HbA1c, cholesterol, cholesterol/HDL ratio, triglycerides, creatinine, blood pressure, fundus photography, foot examination, body mass index and smoking status) for 3 years. The year before signing up with the DSS was taken for the pre-measurements and after 2 years of DSS the post-measurements took place. The effect of the DSS was analysed in a mixed model with repeated measurement covariance structure. RESULTS: At baseline the intervention and control group did not differ in control frequency and outcome (HbA1c). After the intervention the percentage of patients that attended four or more quarterly check-ups (with at least testing of fasting blood glucose or HbA1c) increased from 59 to 78%. In contrast, the frequency of check-ups in the control group remained constant. This effect was significant. The HbA1c remained the same in the intervention group while there was a significant deterioration in the HbA1c in the control group. CONCLUSION: Simple logistic support by the DSS proved to have the capacity to implement type 2 diabetes guidelines in general practice.

The feasibility of a primary care model for the management of COPD.

AIMS: To investigate the feasibility of a primary care model to improve the management of COPD. METHODS: An intervention study on 1,497 patients with documented COPD from 22 general practices, involving 11 practice nurses and a COPD Support Service (CSS). Outcome measures included the successful delegation of tasks from general practitioners (GPs) to the CSS and practice nurse, and performance in daily practice according to the model components -- keeping a patient register with a recall system, periodical history taking and lung function measurements, asking diagnostic and therapeutic advice, and performing regular follow-up visits with education and counselling. RESULTS: In the 22 general practices, all components of the model were performed systematically, with the exception of 'asking for diagnostic and therapeutic advice' which occurred in 10 practices only. Of the 1,497 patients, 374 (25%) were treated by chest physicians. Of the remaining patients 88% were included in the primary care model and 12% refused regular follow-up. CONCLUSION: This primary care model for COPD management proved to be very feasible; GPs delegated the tasks, almost all patients were included in the control system, and a large majority of patients accepted follow-up according to the model.