bpac^nz Research Publications

Introduction

While a number of developed countries have witnessed a decline in carbon monoxide (CO) deaths and increasing numbers of opioid-related fatalities, it is not known whether these or other trends have occurred in New Zealand. The aim of this study was, therefore, to review deaths due to poisoning in New Zealand, describe the causative substances, and identify any trends.

Methods

Retrospective study reviewing New Zealand’s poison-related death findings recorded in the National Coronial Information System (NCIS) database over the 6-year period 2008–2013.

Results

We identified 1402 poisoning-related deaths recorded in the NCIS database representing a mortality rate of 5.4 deaths/100,000 population per year. The mortality rate due to poisoning was higher in males (6.96/100,000) than females (3.83/100,000). Fatalities peaked in the 40–50-year age group with the highest proportion of intentional deaths occurring in people aged 80–90 years. Pharmaceuticals accounted for 731 fatalities (52%) and chemicals 431 (31%), with multiple exposures occurring in 399 cases (28.5%). While CO was the leading cause of death throughout the period (n = 303, 21.6%), there was a significant reduction in the rate of CO fatalities from 1.69/100,000 population in 2008 to 0.94/100,000 in 2013 (IRR (95% CI) 2013/2008 0.56 (0.37–0.83)). There was, however, no statistically significant change in either the opioid-related death rate or the total number of deaths. Methadone was the leading pharmaceutical cause of fatality and the third most common cause overall, followed by morphine and codeine, with zopiclone and clozapine equally ranked as the sixth most common cause.

Conclusions

While New Zealand has not suffered an “opioid epidemic” and has experienced a significant decline in CO deaths, the overall death rate due to poisoning has remained high. The development of accessible, timely, and relevant toxicovigilance systems would support the early implementation of interventions to reduce the leading causes of fatal poisoning.

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.

Aims

There are significant ethnic disparities in the incidence of various infectious diseases in New Zealand. Antimicrobial stewardship interventions which ignore these disparities may have negative effects on the health of some ethnic groups. We aimed to determine the relationship between ethnicity and community antimicrobial dispensing in New Zealand, to inform the development of antimicrobial stewardship interventions in New Zealand.

Methods

Demographic data on all patients registered with a general practice in New Zealand and on all community pharmacy antibacterial dispensings during 2015 were obtained from national healthcare databases. The rates of dispensing were measured as the number of dispensings per 1,000 population per day and as defined daily doses per 1,000 population per day.

Results

The rate of community antibacterial dispensing for the total population surveyed was 3.01 dispensings per 1,000 population per day, and was 3.49 for Pacific, 3.23 for Māori, 3.02 for European, 2.70 for Middle Eastern, Latin American and African, and 2.35 for Asian people. In all ethnic groups the rate of community antibacterial dispensing increased with increasing socioeconomic deprivation. Seasonal variation in antibacterial dispensing ranged between 34% in Asian people and 24% in European people.

Conclusions

The ethnic disparities in the rates of antibacterial dispensing in New Zealand are consistent with, but less marked than, the ethnic disparities in the incidence of infectious diseases in New Zealand. Improved community-wide understanding of both the benefits and the harms of antibacterial medicines is necessary to support improved antibacterial use in New Zealand in the future.

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.

https://www.heartlungcirc.org/article/S1443-9506(18)30629-2/abstract

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.

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.

Background

Variation in prescription costs between general practices and within practices over time is poorly understood.

Methods

From New Zealand's national health data collections, we extracted dispensed medicines data for 1045 general practices in 2011 and 917 practices continuously existing 2008–11. Using indirect standardization to account for patient demographics and morbidity, a standardized prescribing cost ratio (SPR: the ratio of actual : expected prescription costs) was calculated for each practice in each year. Case studies of three outlier clinics explored reasons for their status.

Results

SPRs ranged from 0.53 to 2.28 (median = 0.98). Of 469 practices with higher than expected costs (SPR > 1.0) in 2011, 204 (43.5%) had a single medicine or therapeutic drug class accounting for >15% of total costs. Case studies contrasted practices with overall pharmaceutical expenditure influenced strongly by a few patients needing high-cost medicines, more patients using medicines in one high-cost therapeutic drug class (antiretrovirals), and high medicine use across all therapeutic drug classes.

Conclusions

Routine data collections can measure inter-practice variation in prescription costs, adjusted for differences in the demography and morbidity profile of each practice's patients. Small groups of patients using high-cost medicines influence general practices' expenditure on pharmaceuticals.

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.

Steadily rising rates of antimicrobial resistance, in a range of common bacterial pathogens, are a major threat to human health in New Zealand in the near future. The single largest contributor to this threat is the high level of antimicrobial consumption in New Zealand. Antimicrobial consumption in New Zealand needs to be reduced if we are to slow the spread of antimicrobial-resistant bacteria. Reporting the per capita antimicrobial consumption within each District Health Board (DHB), in relation to targets for reductions from present levels of consumption, could provide an impetus for DHBs to address this threat to the health of their populations.

Background

Mãori and Pacific children experience poorer outcomes relating to asthma management than other ethnicities.

Aims

To measure recommended treatment and outcomes for asthma in all New Zealand children by age, sex, and ethnic group.

Methods

Children aged < 15 years dispensed ≥2 asthma medicines (N=80,514) were identified from the national pharmaceutical claims database. We measured t he number of children dispensed oral steroids ≥2 times and hospital admissions with a primary diagnosis of asthma and compared asthma treatment s teps and hospitalisation by age and ethnicity.

Results

16.0% of children were dispensed asthma medicines, 9.2% were dispensed medicine ≥2 times, 3.6% of children were hospitalised at least once for a sthma and 98.9% of admissions were acute. Mãori (OR 1.46, 95% CI 1.41 to 1.51) and Pacific children (OR 2.38, 95% CI 2.28 to 2.47) were more likely to remain on the lowest step of treatment. At all steps of treatment, Mãori and Pacific children had higher rates of oral steroid use. In all age groups, more Mãori children (5.1%, OR 1.88, 95% CI 1.73 to 2.04) and Pacific children (5.6%, OR 2.05, 95% CI 1.84 to 2.29) were hospitalised for asthma than children of other ethnicities (2.8%).

Conclusions

Mãori and Pacific children are less likely to have their treatment escalated to a higher step than other children. They are also more likely to use oral steroids to control asthma exacerbations and be admitted to hospital for severe asthma episodes. New Zealand databases can be used to monitor these outcomes.

Background

Examination of clinical data routinely recorded in general practice provides significant opportunities for identifying and quantifying medicine-related adverse events not captured by spontaneous adverse reaction reporting systems. Robust pharmacovigilance methods for detecting and monitoring adverse events due to treatment with new and existing medicines are required to estimate the true extent of adverse events experienced by primary care patients.

Objectives

The aim of the study was to examine evidence of adverse events contained in general practice electronic records and to study observed events related to selective serotonin reuptake inhibitors (SSRIs) as an example of drug-specific pharmaceutical surveillance achievable with these data.

Methods

Electronic clinical records for a cohort of 338 931 patients consulting from 2002 to 2007 were extracted from the patient management systems of 30 primary care clinics in New Zealand. Medical warnings files, prescription records and free text consultation notes were used to identify physician-recorded treatment cautions, including adverse events and medicines they were associated with. A structured chronological analysis of prescriptions, consultation notes and adverse events relating to patients prescribed the SSRI citalopram was undertaken, and included investigating reasons for switching treatment to another SSRI (fluoxetine or paroxetine) as a method for detecting evidence of drug safety signals. We compared the number of adverse events identified for patients at one practice with the number spontaneously reported to New Zealand’s Centre for Adverse Reactions Monitoring (CARM).

Results

During the 6-year study period, 173 478 patients received 4811 561 prescriptions. There were 37 397 allergies, adverse events and other warnings recorded for 24994 patients (7.4%); adverse events relating to 65 different types of drug were reported. Medicines most frequently implicated in adverse event reports were antibacterials, analgesics, antihypertensive medicines, lipid-modifying agents and skin preparations. Citalopram was prescribed for 5612 patients, and 701 adverse events relating to citalopram were identified in the electronic health records of 473 (8.4%) patients. A total of 713 (12.7%) patients changed treatment from citalopram to another SSRI, and 164 reasons for the switch were identified: suspected adverse drug effects for 129 (78.7%), lack of effect for 29 (17.7%) and patient preference for 6 (3.7%). The most common adverse events preceding the switch were anxiety, nausea and headaches. Of the 725 adverse events and medical warnings recorded at one practice, 21 (2.9%) were spontaneously reported to the CARM.

Conclusions

Routinely recorded general practice data provide a wealth of opportunities for monitoring drug safety signals and for other patient safety issues. Medical warning records and consultation notes contain a wealth of information on adverse events but structured search methodologies are often required to identify these.