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Background: Older people living in the community have a high prevalence of polypharmacy and are vulnerable to adverse drug events. Home Medicines Review (HMR) is a collaborative medication review service involving general practitioners (GPs), accredited clinical pharmacists (ACPs) and patients, which aims to prevent medication-related problems. This study aims to evaluate the implementation of a Computerised Clinical Decision Support System (CCDSS) called G-MEDSS© (Goal-directed Medication Review Electronic Decision Support System) in HMRs to deprescribe anticholinergic and sedative medications, and to assess the effect of deprescribing on clinical outcomes.Methods: This study consists of 2 stages: Stage I - a two-arm parallel-group cluster-randomised clinical trial, and Stage II - process evaluation of the CCDSS intervention in HMR. Community-dwelling older adults living with and without dementia who are referred for HMR by their GP and recruited by ACPs will be included in this study. G-MEDSS is a CCDSS designed to provide clinical decision support for healthcare practitioners when completing a medication review, to tailor care to meet the patients' goals and preferences. The G-MEDSS contains three tools: The Goals of Care Management Tool, The Drug Burden Index (DBI) Calculator©, and The revised Patients' Attitudes Towards Deprescribing (rPATD) questionnaire. The G-MEDSS produces patient-specific deprescribing reports, to be included as part of the ACPs communication with the patient's GP, and patient-specific reports for the patient (or carer). ACPs randomised to the intervention arm of the study will use G-MEDSS to create deprescribing reports for the referring GP and for their patient (or carer) when submitting the HMR report. ACPs in the comparison arm will provide the usual care HMR service (without the G-MEDSS).Outcomes: The primary outcome is reduction in DBI exposure 3 months after HMR ± G-MEDSS intervention between comparison and intervention groups. The secondary outcomes include changes in clinical outcomes (physical and cognitive function, falls, institutionalisation, GP visits, medication adherence and mortality) 3-months after HMR.Discussion: This study is expected to add to the evidence that the combination of CCDSS supporting medication review can improve prescribing and clinical outcomes in older adults.Trial Registration: The trial was registered on the Australian New Zealand Clinical Trials Registry ACTRN12617000895381 on 19th June 2017. [ABSTRACT FROM AUTHOR]

Background Anticoagulants such as warfarin and dabigatran can significantly reduce the risk of stroke in individuals with atrial fibrillation that may lead to increased risk of bleeding, especially in older people. Evidence for bleeding risks with anticoagulants within the context of doses, multimorbidity and impaired renal function in real world setting is lacking. Therefore we aimed to assess and compare real world bleeding risks with warfarin and dabigatran. Secondary analyses involved examining risk of fatal haemorrhages. Methods and results We formed two inception cohorts of propensity score (PS) matched older patients (≥ 65 years), who initiated dabigatran or warfarin between July 2011 and December 2012. A total of 4835 dabigatran users were matched to 4385 warfarin users in dose independent binary PS matching. A dose dependent PS matching resulted in 2383 warfarin, 2153 dabigatran 150 mg and 3395 dabigatran 110 mg users. In the first cohort, compared to warfarin, the hazard ratios (95% confidence intervals) for dabigatran were 0.45 (0.37–0.55) for any haemorrhage; 1.16 (0.87–1.56) for gastrointestinal haemorrhage; and 0.29 (0.09–0.86) for intracerebral haemorrhage. Similar associations were observed in the first 30 days of treatment. In dose dependent matched cohort, the risk of any haemorrhage was lower in individuals receiving dabigatran 110 mg (HR; 95% CI: 0.40 (0.31–0.52)) and 150 mg (HR; 95% CI: 0.29 (0.19–0.41)) compared to warfarin. Conclusions The risk of any haemorrhage and intracerebral haemorrhage was lower in dabigatran users compared to warfarin users. Importantly no increased risk of gastrointestinal haemorrhage was found in dabigatran users. The incidence rates for any haemorrhage were found to be higher in first 30 days of any anticoagulant treatment, but hazard ratios remained similar during the study period. [ABSTRACT FROM AUTHOR]

Background: The association rules method is a novel methodology to ascertain patterns of medication use and combinations associated with adverse drug events., Objectives: The aim of this case-crossover study was to apply the association rules method to ascertain medication combinations contributing to the risk of fractures in older adults., Methods: A nationwide representative sample of New Zealanders aged ≥65 years was sourced from the pharmaceutical collection. The first-time coded diagnosis of fracture was extracted from the National Minimum Dataset. Association rule method is a data mining technique that can be used to quickly traverse big datasets to identify a combination of items that co-occur. The association rules method were applied to identify frequent 11 medication combinations in the case and the control periods (1-14 days as hazard period, with 35-day washout period), and the association of fractures with each frequent medication combination were tested by computing a matched odd ratio (OR) and its 95% CI., Results: We identified a total of 72 184 individuals (mean age 81.5 years) from 2005 to 2014 with incident fracture and exposed to at least 1 medication of interest. The association rules method revealed codeine phosphate (aOR = 11.50, 95% CI, 7.09-15.20, concomitantly with ibuprofen), zopiclone (aOR = 2.34, 95% CI, 1.49-3.67, concomitantly with morphine) and quetiapine (OR = 1.95, 95% CI, 1.28-2.98, concomitantly with zopiclone) were associated with fractures., Conclusion: The association rules method identified medication exposure combinations containing psychotropic medications and codeine are frequently associated with fractures. This novel methodology applied to big data can be an important tool to ascertain medication combinations associated with adverse drug events., (Copyright © 2018 John Wiley & Sons, Ltd.)