Non-steroidal anti-inflammatory drugs, Cyclooxygenase-2 inhibitors and paracetamol use in Queensland and in the whole of Australia

Background: Cross national drug utilization studies can provide information about different influences on physician prescribing. This is important for medicines with issues around safety and quality of use, like non selective non-steroidal anti-inflammatory drugs (ns-NSAIDs) and cyclooxygenase-2 (COX-2) inhibitors. To enable comparison of prescription medicine use across different jurisdictions with a range of population sizes, data first need to be compared within Australia to understand whether use in a smaller sub-population may be considered as representative of the total use within Australia. The aim of this study was to compare the utilization of non selective NSAID, COX-2 inhibitors and paracetamol between Queensland and Australia

Improving the use of benzodiazepines-Is it possible? A non-systematic review of interventions tried in the last 20 years

Background: Benzodiazepines are often used on a long term basis in the elderly to treat various psychological disorders including sleep disorders, some neurological disorders and anxiety. This is despite the risk of dependence, cognitive impairment, and falls and fractures. Guidelines, campaigns and prescribing restrictions have been used to raise awareness of potentially inappropriate use, however long term use of benzodiazepine and related compounds is currently increasing in Australia and worldwide. The objective of this paper is to explore interventions aimed at improving the prescribing and use of benzodiazepines in the last 20 years

Multinational evaluation of mycophenolic acid, tacrolimus, cyclosporin, sirolimus, and everolimus utilization

Background: Increasing immunosuppressant utilization and expenditure is a worldwide challenge as more people successfully live with transplanted organs. Our aims were to characterize utilization of mycophenolate, tacrolimus, cyclosporin, sirolimus, and everolimus in Australian transplant recipients from 2007 to 2013; to identify specific patterns of usage; and to compare Australian utilization with Norwegian, Danish, Swedish, and the Netherlands use

How accurate and precise are limited sampling strategies in estimating exposure to mycophenolic acid in people with autoimmune disease?

Mycophenolic acid (MPA) is a potent immunosuppressant agent, which is increasingly being used in the treatment of patients with various autoimmune diseases. Dosing to achieve a specific target MPA area under the concentration-time curve from 0 to 12 h post-dose (AUC12) is likely to lead to better treatment outcomes in patients with autoimmune disease than a standard fixed-dose strategy. This review summarizes the available published data around concentration monitoring strategies for MPA in patients with autoimmune disease and examines the accuracy and precision of methods reported to date using limited concentration-time points to estimate MPA AUC12. A total of 13 studies were identified that assessed the correlation between single time points and MPA AUC12 and/or examined the predictive performance of limited sampling strategies in estimating MPA AUC12. The majority of studies investigated mycophenolate mofetil (MMF) rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation of MPA. Correlations between MPA trough concentrations and MPA AUC12 estimated by full concentration-time profiling ranged from 0.13 to 0.94 across ten studies, with the highest associations (r (2) = 0.90-0.94) observed in lupus nephritis patients. Correlations were generally higher in autoimmune disease patients compared with renal allograft recipients and higher after MMF compared with EC-MPS intake. Four studies investigated use of a limited sampling strategy to predict MPA AUC12 determined by full concentration-time profiling. Three studies used a limited sampling strategy consisting of a maximum combination of three sampling time points with the latest sample drawn 3-6 h after MMF intake, whereas the remaining study tested all combinations of sampling times. MPA AUC12 was best predicted when three samples were taken at pre-dose and at 1 and 3 h post-dose with a mean bias and imprecision of 0.8 and 22.6 % for multiple linear regression analysis and of -5.5 and 23.0 % for maximum a posteriori (MAP) Bayesian analysis. Although mean bias was less when data were analysed using multiple linear regression, MAP Bayesian analysis is preferable because of its flexibility with respect to sample timing. Estimation of MPA AUC12 following EC-MPS administration using a limited sampling strategy with samples drawn within 3 h post-dose resulted in biased and imprecise results, likely due to a longer time to reach a peak MPA concentration (t max) with this formulation and more variable pharmacokinetic profiles. Inclusion of later sampling time points that capture enterohepatic recirculation and t max improved the predictive performance of strategies to predict EC-MPS exposure. Given the considerable pharmacokinetic variability associated with mycophenolate therapy, limited sampling strategies may potentially help in individualizing patient dosing. However, a compromise needs to be made between the predictive performance of the strategy and its clinical feasibility. An opportunity exists to combine research efforts globally to create an open-source database for MPA (AUC, concentrations and outcomes) that can be used and prospectively evaluated for AUC target-controlled dosing of MPA in autoimmune diseases

Population pharmacokinetics of fluconazole in critically ill patients receiving continuous venovenous hemodiafiltration - using Monte Carlo Simulations to predict doses for specified pharmacodynamic targets

Fluconazole is a widely used antifungal agent that is extensively reabsorbed in patients with normal renal function. However, its reabsorption can be compromised in patients with acute kidney injury, thereby leading to altered fluconazole clearance and total systemic exposure. Here, we explore the pharmacokinetics of fluconazole in 10 critically ill anuric patients receiving continuous venovenous hemodiafiltration (CVVHDF). We performed Monte Carlo simulations to optimize dosing to appropriate pharmacodynamic endpoints for this population. Pharmacokinetic profiles of initial and steady-state doses of 200 mg intravenous fluconazole twice daily were obtained from plasma and CVVHDF effluent. Nonlinear mixed-effects modeling (NONMEM) was used for data analysis and to perform Monte Carlo simulations. For each dosing regimen, the free drug area under the concentration-time curve (fAUC)/MIC ratio was calculated. The percentage of patients achieving an AUC/MIC ratio greater than 25 was then compared for a range of MIC values. A two-compartment model adequately described the disposition of fluconazole in plasma. The estimate for total fluconazole clearance was 2.67 liters/h and was notably 2.3 times faster than previously reported in healthy volunteers. Of this, fluconazole clearance by the CVVHDF route (CL(CVVHDF)) represented 62% of its total systemic clearance. Furthermore, the predicted efficiency of CL(CVVHDF) decreased to 36.8% when filters were in use >48 h. Monte Carlo simulations demonstrated that a dose of 400 mg twice daily maximizes empirical treatment against fungal organisms with MIC up to 16 mg/liter. This is the first study we are aware of that uses Monte Carlo simulations to inform dosing requirements in patients where tubular reabsorption of fluconazole is probably nonexistent

Consumer involvement in Quality Use of Medicines (QUM) projects – lessons from Australia

BACKGROUND: It is essential that knowledge gained through health services research is collated and made available for evaluation, for policy purposes and to enable collaboration between people working in similar areas (capacity building). The Australian Quality Use of Medicine (QUM) on-line, web-based project database, known as the QUMmap, was designed to meet these needs for a specific sub-section of health services research related to improving the use of medicines. Australia's National Strategy for Quality Use of Medicines identifies the primacy of consumers as a major principle for quality use of medicines, and aims to support consumer led research. The aim of this study was to determine how consumers as a group have been represented in QUM projects in Australia. A secondary aim was to investigate how the projects with consumer involvement fit into Australia's QUM policy framework. METHOD: Using the web-based QUMmap, all projects which claimed consumer involvement were identified and stratified into four categories, projects undertaken by; (a) consumers for consumers, (b) health professionals for consumers, (c) health professionals for health professionals, and (d) other. Projects in the first two categories were then classified according to the policy 'building blocks' considered necessary to achieve QUM. RESULTS: Of the 143 'consumer' projects identified, the majority stated to be 'for consumers' were either actually by health professionals for health professionals (c) or by health professionals for consumers (b) (47% and 40% respectively). Only 12 projects (9%) were directly undertaken by consumers or consumer groups for consumers (a). The majority of the health professionals for consumers (b) projects were directed at the provision of services and interventions, but were not focusing on the education, training or skill development of consumers. CONCLUSION: Health services research relating to QUM is active in Australia and the projects are collated and searchable on the web-based interactive QUMmap. Healthcare professionals appear to be dominating nominally 'consumer focussed' research, with less than half of these projects actively involving the consumers or directly benefiting consumers. The QUMmap provides a valuable tool for policy analysis and for provision of future directions through identification of QUM initiatives

Consumers' experiences and values in conventional and alternative medicine paradigms: a problem detection study (PDS)

Background: This study explored consumer perceptions of complementary and alternative medicine (CAM) and relationships with CAM and conventional medicine practitioners. A problem detection study (PDS) was used. The qualitative component to develop the questionnaire used a CAM consumer focus group to explore conventional and CAM paradigms in healthcare. 32 key issues, seven main themes, informed the questionnaire (the quantitative PDS component - 36 statements explored using five-point Likert scales.

Identification of recruitment and retention strategies for rehabilitation professionals in Ontario, Canada: results from expert panels

<p>Abstract</p> <p>Background</p> <p>Demand for rehabilitation services is expected to increase due to factors such as an aging population, workforce pressures, rise in chronic and complex multi-system disorders, advances in technology, and changes in interprofessional health service delivery models. However, health human resource (HHR) strategies for Canadian rehabilitation professionals are lagging behind other professional groups such as physicians and nurses. The objectives of this study were: 1) to identify recruitment and retention strategies of rehabilitation professionals including occupational therapists, physical therapists and speech language pathologists from the literature; and 2) to investigate both the importance and feasibility of the identified strategies using expert panels amongst HHR and education experts.</p> <p>Methods</p> <p>A review of the literature was conducted to identify recruitment and retention strategies for rehabilitation professionals. Two expert panels, one on <it>Recruitment and Retention </it>and the other on <it>Education </it>were convened to determine the importance and feasibility of the identified strategies. A modified-delphi process was used to gain consensus and to rate the identified strategies along these two dimensions.</p> <p>Results</p> <p>A total of 34 strategies were identified by the <it>Recruitment and Retention </it>and <it>Education </it>expert panels as being important and feasible for the development of a HHR plan for recruitment and retention of rehabilitation professionals. Seven were categorized under the <it>Quality of Worklife and Work Environment </it>theme, another seven in <it>Financial Incentives and Marketing</it>, two in <it>Workload and Skill Mix</it>, thirteen in <it>Professional Development </it>and five in <it>Education and Training</it>.</p> <p>Conclusion</p> <p>Based on the results from the expert panels, the three major areas of focus for HHR planning in the rehabilitation sector should include strategies addressing <it>Quality of Worklife and Work Environment</it>, <it>Financial Incentives and Marketing </it>and <it>Professional Development</it>.</p

Maximum a posteriori bayesian estimation of mycophenolic acid area under the concentration-time curve: Is this clinically useful for dosage prediction yet?

This review seeks to summarize the available data about Bayesian estimation of area under the plasma concentration-time curve (AUC) and dosage prediction for mycophenolic acid (MPA) and evaluate whether sufficient evidence is available for routine use of Bayesian dosage prediction in clinical practice. A literature search identified 14 studies that assessed the predictive performance of maximum a posteriori Bayesian estimation of MPA AUC and one report that retrospectively evaluated how closely dosage recommendations based on Bayesian forecasting achieved targeted MPA exposure. Studies to date have mostly been undertaken in renal transplant recipients, with limited investigation in patients treated with MPA for autoimmune disease or haematopoietic stem cell transplantation. All of these studies have involved use of the mycophenolate mofetil (MMF) formulation of MPA, rather than the enteric-coated mycophenolate sodium (EC-MPS) formulation. Bias associated with estimation of MPA AUC using Bayesian forecasting was generally less than 10%. However some difficulties with imprecision was evident, with values ranging from 4% to 34% (based on estimation involving two or more concentration measurements). Evaluation of whether MPA dosing decisions based on Bayesian forecasting (by the free website service https://pharmaco.chu-limoges.fr) achieved target drug exposure has only been undertaken once. When MMF dosage recommendations were applied by clinicians, a higher proportion (72–80%) of subsequent estimated MPA AUC values were within the 30–60 mg · h/L target range, compared with when dosage recommendations were not followed (only 39–57% within target range). Such findings provide evidence that Bayesian dosage prediction is clinically useful for achieving target MPA AUC. This study, however, was retrospective and focussed only on adult renal transplant recipients. Furthermore, in this study, Bayesian-generated AUC estimations and dosage predictions were not compared with a later full measured AUC but rather with a further AUC estimate based on a second Bayesian analysis. This study also provided some evidence that a useful monitoring schedule for MPA AUC following adult renal transplant would be every 2 weeks during the first month post-transplant, every 1–3 months between months 1 and 12, and each year thereafter. It will be interesting to see further validations in different patient groups using the free website service. In summary, the predictive performance of Bayesian estimation of MPA, comparing estimated with measured AUC values, has been reported in several studies. However, the next step of predicting dosages based on these Bayesian-estimated AUCs, and prospectively determining how closely these predicted dosages give drug exposure matching targeted AUCs, remains largely unaddressed. Further prospective studies are required, particularly in non-renal transplant patients and with the EC-MPS formulation. Other important questions remain to be answered, such as: do Bayesian forecasting methods devised to date use the best population pharmacokinetic models or most accurate algorithms; are the methods simple to use for routine clinical practice; do the algorithms actually improve dosage estimations beyond empirical recommendations in all groups that receive MPA therapy; and, importantly, do the dosage predictions, when followed, improve patient health outcomes