Understanding medicines with a propensity to increase the risk of heart failure: Combining existing knowledge with targeted population assessment.

PURPOSE: Existing knowledge of medicines that increase the risk of an adverse event may be corroborated and augmented by population studies specifically assessing the risk associated with the concurrent use of these medicines and use by patients with existing comorbidity. An American Heart Association review recently identified a variety of medicines that may cause or exacerbate heart failure (HF), many with evidence from limited evaluation of population data. We assessed the risk of first-time HF associated with the use of 50 of these medicines by New Zealand's primary care population. METHODS: Case-control study utilising national pharmaceutical use and hospital admissions data 2007-2015; 22,989 patients with first-time HF 2008-2015 were matched with 114 498 control patients. The primary outcome was first-time HF and its association with medicine exposure in the prior 90 days, estimated using conditional logistic regression. We also assessed the risk associated with new use of medicines in the prior month, concurrent use, and in patients with existing comorbidity. RESULTS: Eleven medicines were significantly associated with HF with several other infrequently used medicines providing signals of increased risk. A high risk was associated with the use of salbutamol (adjusted odds ratio 2.63; 95% CI, 2.48-2.78), clozapine (2.70; 2.46-4.98), diltiazem (1.52; 1.44-1.60), indomethacin (2.51; 1.54-4.10), pioglitazone (1.50; 1.16-1.95), and antifungal medicines. New use of medicines and use of medicine combinations increased this risk in many cases. CONCLUSIONS: Our study provides further evidence to inform cautious use of these medicines in patients with HF or at risk of developing HF.

Trends in Outpatient Prescription Medicine Use in New Zealand Children 2010-2015: A National Population-Based Study.

BACKGROUND: Research examining trends in the outpatient prescription medicine use of New Zealand children is limited. OBJECTIVES: Our objective was to provide an overview of prescription medicine use in New Zealand children and assess changing patterns in use from 2010 to 2015. METHODS: We conducted a retrospective cohort study including all New Zealand primary care-registered children aged < 18 years using data from the national pharmaceutical claims database. We calculated the prevalence of use within four age groups in each year by anatomical therapeutic class, therapeutic group and drug. Rate ratios were calculated to compare the prevalence of use in 2010 and 2015. RESULTS: In total, 1,496,026 children with a mean of 2.7 years of potential drug exposure were included. The overall prevalence of drug use was 70% in 2010 and 73% in 2015. In 2015, medicine use was highest in children aged < 2 years (90%) and lowest in children aged 12-17 years (65%). Antibacterials, analgesics, topical corticosteroids, non-steroidal anti-inflammatory drugs (NSAIDs) and antihistamines were the most widely used medicines. The prevalence of use of systemic and topical antibiotics decreased by 2 and 10%, respectively, between 2010 and 2015, but there was increased use of analgesics (10%), NSAIDs (39%), antihistamines (15%) and antinausea and vertigo agents (306%). CONCLUSIONS: Our findings indicate areas for further research focusing on inappropriate prescribing to children and safety issues in children's medicine use. Monitoring changing patterns of use over time is important for the evaluation of effective therapies in children and any potential harmful consequences of prescribing.

A Pharmacoepidemiology Database System for Monitoring Risk Due to the Use of Medicines by New Zealand Primary Care Patients.

INTRODUCTION: The use of large record-linked healthcare databases for drug safety research and surveillance is now accepted practice. New Zealand's standardized national healthcare datasets provide the potential to automate the conduct of pharmacoepidemiological studies to provide rapid validation of medicine safety signals. OBJECTIVES: Our objectives were to describe the methodology undertaken by a semi-automated computer system developed to rapidly assess risk due to drug exposure in New Zealand's population of primary care patients and to compare results from three studies with previously published findings. METHODS: Data from three national databases were linked at the patient level in the automated studies. A retrospective nested case-control design was used to evaluate risk for upper gastrointestinal bleeding (UGIB), acute kidney failure (AKF), and serious arrhythmia associated with individual medicines, therapeutic classes of medicines, and concurrent use of medicines from multiple therapeutic classes. RESULTS: The patient cohort available for each study included 5,194,256 patients registered between 2007 and 2014, with a total of 34,630,673 patient-years at risk. An increased risk for UGIB was associated with non-steroidal anti-inflammatory drugs (NSAIDs) (adjusted odds ratio [AOR] 4.16, 95% confidence interval [CI] 3.90-4.43, p < 0.001) and selective serotonin reuptake inhibitors (AOR 1.39, 95% CI 1.20-1.62, p < 0.001); an increased risk for AKF was associated with NSAIDs (AOR 1.78, 95% CI 1.73-1.83, p < 0.001) and proton pump inhibitors (AOR 1.78, 95% CI 1.72-1.83, p < 0.001); and an increased risk for serious arrhythmia was associated with fluoroquinolones (AOR 1.38, 95% CI 1.26-151, p < 0.001) and penicillins (AOR 1.69, 95% CI 1.61-1.77, p < 0.001). CONCLUSIONS: Automated case-control studies using New Zealand's healthcare datasets can replicate associations of risk with drug exposure consistent with previous findings. Their speed of conduct enables systematic monitoring of risk for adverse events associated with a wide range of medicines.

Atrial fibrillation in New Zealand primary care: Prevalence, risk factors for stroke and the management of thromboembolic risk.

Background Atrial fibrillation is a major risk factor for stroke and heart disease but there is limited information on its prevalence in New Zealand primary care or the treatment provided to manage thromboembolic risk. Our aim was to estimate the prevalence of atrial fibrillation, assess patient risk for thromboembolism and evaluate the appropriateness of risk reduction using antiplatelet and oral anticoagulation therapy. Design A retrospective cohort study utilising electronic medical records for 739,000 patients registered with 170 general practices in 2014. Methods Patient diagnoses and prescriptions from 2010-2014 were analysed to identify patients with atrial fibrillation in 2014 and co-morbidities included in the CHA2DS2-VASc algorithm. Adjusted prevalence of atrial fibrillation by patient demographic group and the proportion of patients following recommended antithrombotic therapy were calculated. Results 12,712 patients were identified with AF (1.72%, 95% confidence interval 1.69%-1.75%). Prevalence was significantly higher for Maori (odds ratio 1.91, 95% confidence interval 1.80-2.03) than Europeans after adjusting for age, sex, deprivation and clinical risk factors. Stroke risk for Maori and Pacific Island patients was higher than for Europeans across all age groups. Of the 10,406 patients (81.9%) at high risk for thromboembolism, 60.5% were using anticoagulants, 24.1% aspirin monotherapy and 15.4% neither anticoagulants nor aspirin. Oral anticoagulants were used by 31.5% of patients at low risk (CHA2DS2-VASc <2). Conclusions Oral anticoagulants are under-utilised in the management of thromboembolic risk in high risk patients with atrial fibrillation. Better promotion of guideline recommendations for the treatment of patients with atrial fibrillation may be required to improve clinician and patient decision-making.

Risk stratification of New Zealand general practice patients for emergency admissions in the next year: adapting the PEONY model for use in New Zealand.

INTRODUCTION Patient-centred case management programmes in general practice are needed for patients at high risk for emergency admissions to hospital. AIM To adapt and assess the Predicting Emergency Admissions Over the Next Year (PEONY) model for use in New Zealand to provide risk stratification of general practice patients aged ≥40 years for emergency hospital admissions in the next year. METHODS A retrospective observational cohort study modelling 2008-2010 hospital utilisation and medicine use was undertaken to estimate for each patient a risk of emergency admissions in 2011. Health care data were integrated from four national data collections relating to general practice patient registers, hospital admissions, pharmacy dispensed medicines, and mortality. Logistic regression was used to estimate coefficients for variables in the model. Model performance was assessed by calculating its positive predictive value (PPV), sensitivity, and specificity at incremental risk thresholds and receiver operating characteristic. RESULTS The patient cohort included 1,409,506 registered patients; 154,892 (11.0%) had an emergency admission in the follow-up year. Patient age, sex, ethnic group, deprivation status, prior emergency admissions and use of medicines for chronic conditions were all strong predictors of admissions in the next year. The model's PPV for the validation dataset was 58.2% for patients with risk ≥ 50%, and the area under its receiver operating curve = 0.72. DISCUSSION The PEONY model provides an effective methodology for stratifying New Zealand general practice patients' risk for future emergency admissions. High-risk patients may benefit from patient-centred case management programs to address risk and reduce unplanned admissions.