Quality of anticoagulation and use of warfarin-interacting medications in long-term care: A chart review

<p>Abstract</p> <p>Background</p> <p>Maintenance of therapeutic International Normalized Ratio (INR) in the community is generally poor. The supervised environment in long-term care facilities may represent a more ideal setting for warfarin therapy since laboratory monitoring, compliance, dose adjustment, and interacting medications can all be monitored and controlled. The objectives of this study were to determine how effectively warfarin was administered to a cohort of residents in long-term care facilities, to identify the proportion of residents prescribed warfarin-interacting drugs and to ascertain factors associated with poor INR control.</p> <p>Methods</p> <p>A chart review of 105 residents receiving warfarin therapy in five long-term care facilities in Hamilton, Ontario was performed. Data were collected on INR levels, warfarin prescribing and monitoring practices, and use of interacting medications.</p> <p>Results</p> <p>Over a 12 month period (28,555 resident-days, 78.2 resident years) 3065 INR values were available. Residents were within, below and above the therapeutic range 54%, 35% and 11% of the time, respectively. Seventy-nine percent of residents were prescribed at least one warfarin-interacting medication during the period in review. Residents receiving interacting medications spent less time in the therapeutic range (53.0% vs. 58.2%, OR = 0.93, 95% confidence interval 0.88 to 0.97, P = 0.002). Adequacy of anticoagulation varied significantly between physicians (time in therapeutic range 45.9 to 63.9%).</p> <p>Conclusion</p> <p>In this group of long-term care residents, warfarin control was suboptimal. Both prescriber and co-prescription of interacting medications were associated with poorer INR control. Future studies should seek strategies to improve prescriber skill and decrease use of interacting medications.</p

Imputation strategies for missing binary outcomes in cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study.</p> <p>Method</p> <p>We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies.</p> <p>Results</p> <p>The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used.</p> <p>Conclusion</p> <p>When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar.</p

Development and Evaluation of a Psychosocial Intervention for Children and Teenagers Experiencing Diabetes (DEPICTED): a protocol for a cluster randomised controlled trial of the effectiveness of a communication skills training programme for healthcare professionals working with young people with type 1 diabetes

Background Diabetes is the third most common chronic condition in childhood and poor glycaemic control leads to serious short-term and life-limiting long-term complications. In addition to optimal medical management, it is widely recognised that psychosocial and educational factors play a key role in improving outcomes for young people with diabetes. Recent systematic reviews of psycho-educational interventions recognise the need for new methods to be developed in consultation with key stakeholders including patients, their families and the multidisciplinary diabetes healthcare team. Methods/design Following a development phase involving key stakeholders, a psychosocial intervention for use by paediatric diabetes staff and not requiring input from trained psychologists has been developed, incorporating a communication skills training programme for health professionals and a shared agenda-setting tool. The effectiveness of the intervention will be evaluated in a cluster-randomised controlled trial (RCT). The primary outcome, to be measured in children aged 4-15 years diagnosed with type 1 diabetes for at least one year, is the effect on glycaemic control (HbA1c) during the year after training of the healthcare team is completed. Secondary outcomes include quality of life for patients and carers and cost-effectiveness. Patient and carer preferences for service delivery will also be assessed. Twenty-six paediatric diabetes teams are participating in the trial, recruiting a total of 700 patients for evaluation of outcome measures. Half the participating teams will be randomised to receive the intervention at the beginning of the trial and remaining centres offered the training package at the end of the one year trial period. Discussion The primary aim of the trial is to determine whether a communication skills training intervention for specialist paediatric diabetes teams will improve clinical and psychological outcomes for young people with type 1 diabetes. Previous research indicates the effectiveness of specialist psychological interventions in achieving sustained improvements in glycaemic control. This trial will evaluate an intervention which does not require the involvement of trained psychologists, maximising the potential feasibility of delivery in a wider NHS context. Trial registration Current Controlled Trials ISRCTN61568050