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Auckland, New Zealand

O'Brien A.,Waitemata District Health Board
International Journal of Geriatric Psychiatry | Year: 2016

Objective: The advent of second-generation antipsychotics (SGAs) in the 1990s brought optimism that neuroleptic-induced tardive dyskinesia (TD) may become relegated to history. Whether or not this is the case remains inconclusive, and this review aims to compare the risk of TD in older adults treated with first-generation antipsychotics (FGAs) versus SGAs. Methods: Relevant papers were sourced via a range of electronic databases, with a date range from 1957 to January 2015. Included studies used both a validated rating scale and research diagnostic criteria to report on the prevalence or incidence of TD in older adults exposed to antipsychotic medications. Results: For FGAs, the prevalence estimate was 53% (95% confidence interval [CI] [39.0, 68.4]) for mild TD and 38% (95% CI [25.9, 50.3]) for probable TD. Incidence estimates for probable TD with FGAs were 23% (95% CI [15.3, 30.6]) at 1 year, 42% (95% CI [24.8, 58.4]) at 2 years and 57% (95% CI [45.3, 69.1]) at 3 years. For SGAs, the incidence estimates at 1 year were 7% (95% CI [4.4, 10.2]) for probable TD and 3% (95% CI [1.5, 4.2]) for persistent TD. Conclusions: The risk of probable TD is more than three times lower in older adults receiving SGAs in comparison with FGAs after 1 year of treatment (23% vs 7%). The risk of persistent TD at 1 year with SGAs is particularly low. Evidence is lacking in regard to the longer-term risk of TD with SGAs, although the rates associated with the prolonged use of FGAs are high. Caution is therefore still required, particularly with the protracted use of both FGAs and SGAs. Copyright © 2015 John Wiley & Sons, Ltd. Source

Pauly R.P.,University of Alberta | Eastwood D.O.,Waitemata District Health Board | Marshall M.R.,University of Auckland
Hemodialysis International | Year: 2015

Interest in home hemodialysis (HD) is high because of the reported benefits and its excellent safety record. However, the potential for serious adverse events (AEs) exists when patients perform HD in their homes without supervision. We review the epidemiology of dialysis-related emergencies during home HD, and present a conceptual and practical framework for the prevention and management of serious AEs for those patients performing home HD. In addition, we describe a formal monitored and iterative quality assurance program, and make suggestions for the future development of safety strategies to mitigate the risk of AEs in home HD. © 2015 International Society for Hemodialysis. Source

Background—In New Zealand, the Ministry of Health frequently uses national elective rates to calculate the number of operations that will be needed each year. Furthermore it uses this to advocate for an increase or decrease in the number of operations per district health board (DHB) accordingly. The idea behind this calculation is that New Zealanders have similar needs whereby the only differences are due to age, gender, ethnicity and New Zealand deprivation (NZDep) distribution among the DHBs. Health survey data in the year 2011/2012 clearly showed that there were huge differences between DHBs for most of the parameters investigated including smoking rates, obesity and overweight rates, physical activity rates, healthy nutrition, cholesterol and hypertensive medication use.10 These factors all work as risks explaining most, if not all, elective operation volumes across each DHB.1,2,6 Hip and knee replacement are strongly linked in literature to obesity.1,2 In addition, these can be linked to almost all other risk factors that are explored in the health survey.10 Angiograph, angioplasty, coronary bypass, cholecystitis and cataracts are linked to almost all the above risk factors.5 In addition, even ones which seem far away from these risk factors, such as prostate and hernias, have shown, through studies, to have a close relationship with the above risk factors.2,3,5,6 If these risk factors have indirect, if not direct effect on the need for operations, and hence the number, and the risk factors vary extensively between DHBs, then why do all DHBs have the same national rate? Standardising the rate by age, gender, ethnicity and NZDep will not address the issue of the discrepancy due to these risk factors. Conclusion—Having a different elective operation rate for each DHB will be more reliable and efficient than having one national rate for all. ©NZMA. Source

Hosking J.E.,University of Auckland | Ameratunga S.N.,University of Auckland | Bramley D.M.,Waitemata District Health Board | Crengle S.M.,University of Auckland
Annals of Surgery | Year: 2011

Objective: To identify interventions for reducing ethnic disparities in the quality of trauma care. Background: Variation in the quality of health care is recognized as an important contributor to ethnic disparities in many domains of health. Although recent articles document ethnic variations in the quality of trauma care in several countries, strategies that address these disparities have received little attention. Methods: Systematic review of intervention studies designed to reduce ethnic disparities in trauma care. Results: Our systematic literature review revealed no evaluations of interventions designed to reduce ethnic disparities in trauma care. A scan of the equivalent literature in other health care settings revealed 3 types of strategies that could serve as promising interventions that warrant further investigation in the trauma care setting: (1) improving cultural competency of service providers, (2) addressing the effects of health literacy on the quality of trauma care, and (3) quality improvement strategies that recognize equity as a key dimension of quality. The trauma coordinator role may help address some aspects relating to these themes although reducing disparities is likely to require broader system-wide policies. Conclusions: The implementation and robust evaluation of strategies designed to reduce ethnic disparities in trauma care are long overdue. Copyright © 2011 by Lippincott Williams & Wilkins. Source

Elley C.R.,University of Auckland | Robinson E.,University of Auckland | Kenealy T.,University of Auckland | Bramley D.,Waitemata District Health Board | Drury P.L.,Auckland Diabetes Center
Diabetes Care | Year: 2010

OBJECTIVE - To derive a 5-year cardiovascular disease (CVD) risk equation from usual-care data that is appropriate for people with type 2 diabetes from a wide range of ethnic groups, variable glycemic control, and high rates of albuminuria in New Zealand. RESEARCH DESIGN AND METHODS - This prospective open-cohort study used primary-care data from 36,127 people with type 2 diabetes without previous CVD to derive a CVD equation using Cox proportional hazards regression models. Data from 12,626 people from a geographically different area were used for validation. Outcome measure was time to first fatal or nonfatal cardiovascular event, derived from national hospitalization and mortality records. Risk factors were age at diagnosis, diabetes duration, sex, systolic blood pressure, smoking status, total cholesterol-to-HDL ratio, ethnicity, glycated hemoglobin (A1C), and urine albumin-to-creatinine ratio. RESULTS - Baseline median age was 59 years, 51% were women, 55% were of non-European ethnicity, and 33% had micro- or macroalbuminuria. Median follow-up was 3.9 years (141,169 person-years), including 10,030 individuals followed for at least 5 years. At total of 6,479 first cardiovascular events occurred during follow-up. The 5-year observed risk was 20.8% (95% CI 20.3-21.3). Risk increased with each 1% A1C (adjusted hazard ratio 1.06 [95% CI 1.05-1.08]), when macroalbuminuria was present (2.04 [1.89-2.21]), and in Indo-Asians (1.29 [1.14-1.46]) and Maori (1.23 [1.14-1.32]) compared with Europeans. The derived risk equations performed well on the validation cohort compared with other risk equations. CONCLUSIONS - Renal function, ethnicity, and glycemic control contribute significantly to cardiovascular risk prediction. Population- appropriate risk equations can be derived from routinely collected data. © 2010 by the American Diabetes Association. Source

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