Avoiding double counting: the effect of bundling hospital events in administrative datasets for the interpretation of rural-urban differences in Aotearoa New Zealand.

BACKGROUND: All publicly funded hospital discharges in Aotearoa New Zealand (NZ) are recorded in the National Minimum Dataset (NMDS). Movement of patients between hospitals (and occasionally within the same hospital) results in separate records (discharge events) within the NMDS and if these consecutive health records are not accounted for hospitalisation (encounters) rates might be overestimated. The aim of this study was to determine the impact of four different methods to bundle multiple discharge events in the NMDS into encounters on the relative comparison of rural and urban Ambulatory Sensitive Hospitalisation (ASH) rates. METHODS: NMDS discharge events with an admission date between July 1 2015 and December 31 2019 were bundled into encounters using either using a) no method, b) an "admission flag", c) a "discharge flag" or d) a date-based method. ASH incidence rates and rate ratios (IRR), the mean total length of stay and the percentage of inter-hospital transfers were estimated for each bundling method. These outcomes were compared across 4 categories of the Geographic Classification for Health (GCH). RESULTS: Compared with no bundling, using the date-based method resulted in an 8.3% reduction (150 less hospitalisations per 100 000 person years) in the estimated incidence rate for ASH in the most rural (R2-3) regions. There was no difference in the interpretation of the rural-urban IRR for any bundling methodology. Length of stay was longer for all bundling methods used. For patients that live in the most rural regions, using a date-based method identified up to twice as many inter-hospital transfers (5.7% vs. 12.4%) compared to using admission flags. CONCLUSION: Consecutive events within hospital discharge datasets should be bundled into encounters to estimate incidence. This reduces the over-estimation of incidence rates and the undercounting of inter-hospital transfers and total length of stay.

Comparison of injury severity scores derived from ICD-10-AM codes with trauma registry derived scores: A study from New Zealand.

INTRODUCTION: Various attempts at automation have been made to reduce the administrative burden of manually assigning Abbreviated Injury Severity (AIS) codes to derive Injury Severity Scores (ISS) in trauma registry data. The accuracy of the resulting measures remains unclear, especially in the New Zealand (NZ) context. The aim of this study was to compare ISS derived from hospital discharge International Classification of Diseases Australian Modification (ICD-10-AM) codes with ISS recorded in the NZ Trauma Registry (NZTR). METHODS: Individuals admitted to hospital and enrolled in the NZTR between 1 December 2016 and 30 November 2018 were included. ISS were calculated using a modified ICD to AIS mapping tool. The agreement between both methods for raw scores was assessed by the Intraclass Correlation Coefficient (ICC), and for categorical scores the Kappa and weighted Kappa index were used. Analysis was conducted by gender, age, ethnicity, and mechanism of injury. RESULTS: 3,156 patients fulfilled the inclusion criteria. The ICC for agreement between the methods was poor (0.40, 95 % CI: 0.37-0.43). The Kappa index indicated slight agreement between both methods when using a cut-off value of 12 (0.06; 95 % CI: 0.01-0.12) and 15 (0.13 6; 95 % CI: 0.09-0.17). CONCLUSION: Although the overall agreement between NZTR-ISS and ICD-ISS was slight, ICD-derived scores may be useful to describe injury patterns and for body region-specific estimations when manually coded ISS are not available.

Rural-urban variation in the utilisation of publicly funded healthcare services: an age-stratified population-level observational study.

AIM: To compare age-stratified public health service utilisation in Aotearoa New Zealand across the rural-urban spectrum. METHODS: Routinely collected hospitalisation, allied health, emergency department and specialist outpatient data (2014-2018), along with Census denominators, were used to calculate utilisation rates for residents in the two urban and three rural categories in the Geographic Classification for Health. RESULTS: Relative to their urban peers, rural Maori and rural non-Maori had lower all-cause, cardiovascular, mental health and ambulatory sensitive (ASH) hospitalisation rates. The age-standardised ASH rate ratios (major cities as the reference, 95% CIs) across the three rural categories were for Maori 0.79 (0.78, 0.80), 0.83 (0.82, 0.85) and 0.80 (0.77, 0.83), and for non-Maori 0.87 (0.86, 0.88), 0.80 (0.78, 0.81) and 0.50 (0.47, 0.53). Residents of the most remote communities had the lowest rates of specialist outpatient and emergency department attendance, an effect that was accentuated for Maori. Allied health service utilisation by those in rural areas was higher than that seen in the major cities. CONCLUSIONS: The large rural-urban variation in health service utilisation demonstrated here is previously unrecognised and in contrast to comparable international data. New Zealand's most remote communities have the lowest rates of health service utilisation despite high amenable mortality rates. This raises questions about geographic equity in health service design and delivery and warrants further in-depth research.

Rural-urban variation in COVID-19 vaccination uptake in Aotearoa New Zealand: Examining the national roll-out.

This study aimed to understand rural-urban differences in the uptake of COVID-19 vaccinations during the peak period of the national vaccination roll-out in Aotearoa New Zealand (NZ). Using a linked national dataset of health service users aged 12+ years and COVID-19 immunization records, age-standardized rates of vaccination uptake were calculated at fortnightly intervals, between June and December 2021, by rurality, ethnicity, and region. Rate ratios were calculated for each rurality category with the most urban areas (U1) used as the reference. Overall, rural vaccination rates lagged behind urban rates, despite early rapid rural uptake. By December 2021, a rural-urban gradient developed, with age-standardized coverage for R3 areas (most rural) at 77%, R2 81%, R1 83%, U2 85%, and U1 (most urban) 89%. Age-based assessments illustrate the rural-urban vaccination uptake gap was widest for those aged 12-44 years, with older people (65+) having broadly consistent levels of uptake regardless of rurality. Variations from national trends are observable by ethnicity. Early in the roll-out, Indigenous Maori residing in R3 areas had a higher uptake than Maori in U1, and Pacific peoples in R1 had a higher uptake than those in U1. The extent of differences in rural-urban vaccine uptake also varied by region.

Comparison of urban and rural mortality rates across the lifespan in Aotearoa/New Zealand: a population-level study.

BACKGROUND: Previous studies undertaken in New Zealand using generic rurality classifications have concluded that life expectancy and age-standardised mortality rates are similar for urban and rural populations. METHODS: Administrative mortality (2014-2018) and census data (2013 and 2018) were used to estimate age-stratified sex-adjusted mortality rate ratios (aMRRs) for a range of mortality outcomes across the rural-urban spectrum (using major urban centres as the reference) for the total population and separately for Maori and non-Maori. Rural was defined according to the recently developed Geographic Classification for Health. RESULTS: Mortality rates were higher overall in rural areas. This was most pronounced in the youngest age group (<30 years) in the most remote communities (eg, all-cause, amenable and injury-related aMRRs (95% CIs) were 2.1 (1.7 to 2.6), 2.5 (1.9 to 3.2) and 3.0 (2.3 to 3.9) respectively. The rural:urban differences attenuated markedly with increasing age; for some outcomes in those aged 75 years or more, estimated aMRRs were <1.0. Similar patterns were observed for Maori and non-Maori. CONCLUSION: This is the first time that a consistent pattern of higher mortality rates for rural populations has been observed in New Zealand. A purpose-built urban-rural classification and age stratification were important factors in unmasking these disparities.

Unmasking hidden disparities: a comparative observational study examining the impact of different rurality classifications for health research in Aotearoa New Zealand.

OBJECTIVES: Examine the impact of two generic-urban-rural experimental profile (UREP) and urban accessibility (UA)-and one purposely built-geographic classification for health (GCH)-rurality classification systems on the identification of rural-urban health disparities in Aotearoa New Zealand (NZ). DESIGN: A comparative observational study. SETTING: NZ; the most recent 5 years of available data on mortality events (2013-2017), hospitalisations and non-admitted hospital patient events (both 2015-2019). PARTICIPANTS: Numerator data included deaths (n=156 521), hospitalisations (n=13 020 042) and selected non-admitted patient events (n=44 596 471) for the total NZ population during the study period. Annual denominators, by 5-year age group, sex, ethnicity (Maori, non-Maori) and rurality, were estimated from Census 2013 and Census 2018. PRIMARY AND SECONDARY OUTCOME MEASURES: Primary measures were the unadjusted rural incidence rates for 17 health outcome and service utilisation indicators, using each rurality classification. Secondary measures were the age-sex-adjusted rural and urban incidence rate ratios (IRRs) for the same indicators and rurality classifications. RESULTS: Total population rural rates of all indicators examined were substantially higher using the GCH compared with the UREP, and for all except paediatric hospitalisations when the UA was applied. All-cause rural mortality rates using the GCH, UA and UREP were 82, 67 and 50 per 10 000 person-years, respectively. Rural-urban all-cause mortality IRRs were higher using the GCH (1.21, 95% CI 1.19 to 1.22), compared with the UA (0.92, 95% CI 0.91 to 0.94) and UREP (0.67, 95% CI 0.66 to 0.68). Age-sex-adjusted rural and urban IRRs were also higher using the GCH than the UREP for all outcomes, and higher than the UA for 13 of the 17 outcomes. A similar pattern was observed for Maori with higher rural rates for all outcomes using the GCH compared with the UREP, and 11 of the 17 outcomes using the UA. For Maori, rural-urban all-cause mortality IRRs for Maori were higher using the GCH (1.34, 95% CI 1.29 to 1.38), compared with the UA (1.23, 95% CI 1.19 to 1.27) and UREP (1.15, 95% CI 1.10 to 1.19). CONCLUSIONS: Substantial variation in rural health outcome and service utilisation rates were identified with different classifications. Rural rates using the GCH are substantially higher than the UREP. Generic classifications substantially underestimated rural-urban mortality IRRs for the total and Maori populations.

Predictors of hospital readmission after trauma: A retrospective cohort study in New Zealand.

INTRODUCTION: Understanding predictors of hospital readmission following major trauma is important as readmissions are costly and some are potentially avoidable. This study describes the incidence of, and sociodemographic, injury-related and treatment-related factors predictive of, hospital readmission related to: a) all-causes, b) the index trauma injury, and c) subsequent injury events in the 30 days and 12 months following discharge for major trauma patients nationally in New Zealand. METHODS: Data from the New Zealand Trauma Registry (NZTR) was linked with Ministry of Health hospital discharge data. Hospital readmissions were examined for all patients entered into the NZTR for an injury event between 1 January and 31 December 2018. Readmissions were examined for the 12-months following the discharge date for participant's index trauma injury. RESULTS: Of 1986 people, 42% had ≥1 readmission in the 12 months following discharge; 15% within 30 days. Seven percent had ≥1 readmission related to the index trauma within 30 days of discharge; readmission was 3.43 (95% CI 1.87, 6.29) times as likely if the index trauma was self-inflicted compared to unintentional, and 1.64 (95% CI 1.15, 2.34) times as likely if the index trauma involved intensive care unit admission. Those admitted to hospital for longer for their index trauma were less likely to be readmitted due to their index trauma injury within 30 days compared to those admitted for 0-1 day. Seventeen percent were readmitted for a subsequent injury event within 12 months, with readmission more likely for older people (>65 years), those with comorbidities, Maori compared with non-Maori and those with higher trauma injury severity. CONCLUSION: A substantial proportion of people are readmitted after discharge for major trauma. Factors identified in this study will be useful to consider when developing interventions to reduce preventable readmissions including those related to the index trauma injury, readmissions from other causes and subsequent injury-related readmissions. Further research specifically examining planned and unplanned readmissions is warranted.

Societal burden of work on injury deaths in New Zealand, 2005-14: An observational study.

Background: Work poses increased risk of injury not only for workers but also for the public, yet the broader impact of work-related injury is not quantified. This study, utilising population data from New Zealand, estimates the societal burden of work-related fatal injury (WRFI) by including bystanders and commuters. Methods: This observational study selected deaths due to unintentional injury, in persons aged 0-84 years using International Classification of Disease external cause codes, matched to coronial records, and reviewed for work-relatedness. Work-relatedness was determined by the decedent's circumstances at the time of the incident: working for pay, profit, in kind, or an unpaid capacity (worker); commuting to or from work (commuter); or a bystander to another's work activity (bystander). To estimate the burden of WRFI, frequencies, percentages, rates, and years-of-life lost (YLL) were estimated. Results: In total 7,707 coronial records were reviewed of which 1,884 were identified as work-related, contributing to 24% of the deaths and 23% of the YLL due to injury. Of these deaths close to half (49%) occurred amongst non-working bystanders and commuters. The overall burden of WRFI was widespread across age, sex, ethnic and deprivation sub-groups. Injury deaths due to machinery (97%) and due to being struck by another object (69%) were predominantly work-related. Interpretation: When utilising a more inclusive definition of work-relatedness the contribution of work to the societal burden of fatal injuries is substantial, conservatively estimated at one quarter of all injury deaths in New Zealand. Other estimates of WRFI likely exclude a similar number of fatalities occurring among commuters and bystanders. The findings, also relevant to other OECD nations, can guide where public health efforts can be used, alongside organisational actions, to reduce WRFI for all those impacted.

Does support received for subsequent injuries differ between Maori and non-Maori? Findings from a cohort study of injured New Zealanders.

AIMS: To examine if differences exist between injured Maori and non-Maori in accessing and receiving support from the Accident Compensation Corporation (ACC) for treatment and rehabilitation of subsequent injuries. METHODS: This cohort study utilised participants' self-reported data from the Prospective Outcomes of Injury Study, and ACC claims data. RESULTS: Approximately one-third of Maori (32%) and non-Maori (35%) who self-reported a subsequent injury had no associated ACC claim. Statistically significant differences in this outcome (i.e., self-reported subsequent injury but no ACC claim) were found between Maori and non-Maori when comparing across occupation type and severity of participants' sentinel injuries. Few differences were observed between Maori and non-Maori in the percentages of ACC claims accepted that compensated various treatments and supports; this was similar for average compensation amounts provided. CONCLUSIONS: Maori and non-Maori who received support from ACC for a sentinel injury prior to sustaining another injury appear to have received equitable ACC compensation for the treatment and rehabilitation of the subsequent injury with two potential exceptions. Further research is needed to determine how generalisable these findings are. Establishing routine systems for collecting data about the support needed, treatment pathways and outcomes once accessing ACC support is vital to ensure positive and equitable injury outcomes for Maori.

Defining rural in Aotearoa New Zealand: a novel geographic classification for health purposes.

AIM: Describe the first specifically designed and validated five-level rurality classification for health purposes in New Zealand that is both data-driven and incorporates heuristic understandings of rurality. METHOD: Our approach involved: (1) defining the purpose and parameters of a proposed five-level Geographic Classification for Health (GCH); (2) developing a quantitative framework; (3) undertaking co-design with the National Rural Health Advisory Group (NRHAG), and extensive consultation with key stakeholders; (4) testing the validity of the five-level GCH and comparing it to previous Statistics New Zealand (Stats NZ) rurality classifications; and (5) describing rural populations and identifying differences in all-cause mortality using the GCH and previous Stats NZ rurality classifications. RESULTS: The GCH is a technically robust and heuristically valid rurality classification for health purposes. It identifies a rural population that is different to the population defined by generic Stats NZ classifications. When applied to New Zealand's Mortality Collection, the GCH estimates a rural mortality rate 21% higher than for residents of urban areas. These rural-urban disparities are masked by the generic Stats NZ classifications. CONCLUSION: The development of the five-level GCH embraces both the technical and heuristic aspects of rurality. The GCH offers the opportunity to develop a body of New Zealand rural health literature founded on a robust conceptualisation of rurality.

Mortality outcomes and inequities experienced by rural Maori in Aotearoa New Zealand.

Background: Previous research identified inequities in all-cause mortality between Maori and non-Maori populations. Unlike comparable jurisdictions, mortality rates in rural areas have not been shown to be higher than those in urban areas for either population. This paper uses contemporary mortality data to examine Maori and non-Maori mortality rates in rural and urban areas. Methods: A population-level observational study using deidentified routinely collected all-cause mortality, amenable mortality and census data. For each level of the Geographic Classification for Health (GCH), Maori and non-Maori age-sex standardised all-cause mortality and amenable mortality incident rates, Maori:Non-Maori standardised incident rate ratios and Maori rural:urban standardised incident rate ratios were calculated. Age and deprivation stratified rates and rate ratios were also calculated. Findings: Compared to non-Maori, Maori experience excess all-cause (SIRR 1.87 urban; 1.95 rural) and amenable mortality (SIRR 2.45 urban; 2.34 rural) and in all five levels of the GCH. Rural Maori experience greater all-cause (SIRR 1.07) and amenable (SIRR 1.13) mortality than their urban peers. Maori and non-Maori all-cause and amenable mortality rates increased as rurality increased. Interpretation: The excess Maori all-cause mortality across the rural: urban spectrum is consistent with existing literature documenting other Maori health inequities. A similar but more pronounced pattern of inequities is observed for amenable mortality that reflects ethnic differences in access to, and quality of, health care. The excess all-cause and amenable mortality experienced by rural Maori, compared to their urban counterparts, suggests that there are additional challenges associated with living rurally. Funding: This work was funded by the Health Research Council of New Zealand (HRC19/488).

Epidemiology of major trauma in New Zealand: a systematic review.

AIM: To describe the incidence and characteristics of major trauma in New Zealand. METHODS: A systematic review based on a MEDLINE search strategy was performed using the databases PubMed, EMBASE, CINAHL and Scopus. Search terms included: "Wounds and Injuries," "Fatal Injuries," "Injury Severity Score," "Major Trauma," "Severe Trauma," "Injury Scale," "Epidemiology," "Incidence," "Prevalence" and "Mortality." Studies published in English up to September 2021 reporting the incidence of major trauma in New Zealand were included. The quality of studies was assessed using the GATE LITETM tool. RESULTS: Thirty-nine studies fulfilled the inclusion criteria. The majority of studies were descriptive observational studies (n=37). The incidence of fatal trauma was highest among those injured from motor vehicle crashes (MVCs) or falls, Maori males and those sustaining head injuries. The incidence of non-fatal major trauma was highest among young Maori males. MVCs and falls were the most common mechanism of injury among trauma patients across all age groups. Length of hospital stay was greatest in patients with the highest Injury Severity Scores. CONCLUSIONS: The incidence of major trauma varies by age, sex and ethnicity. This review highlights the need for further analytical studies that can explore factors that may impact survival from major trauma.

Impact of legislative reform on worker fatalities in New Zealand workplaces: a 30-year retrospective population-level analysis.

OBJECTIVES: To determine the impact of major legislative changes to New Zealand's Occupational Health and Safety (OHS) legislation with the adoption of the Robens model as a means to control occupational risks on the burden and risk of work-related fatal injury (WRFI). METHODS: Population-based comparison of WRFI to workers aged 15-84 years occurring during three periods: before (pre:1985-1992), after legislative reform (post-1:1993-2002) and after subsequent amendment (post-2:2003-2014). Annual age-industry standardised rates were calculated with 95% CI. Multivariable Poisson regression was used to estimate age-adjusted annual percentage changes (APC) for each period, overall and stratified by high-risk industry and occupational groups. RESULTS: Over the 30-year period, 2053 worker deaths met the eligibility criteria. Age-adjusted APC in rates of worker WRFI changed little between periods: pre (-2.8%, 95% CI 0.0% to -5.5%); post-1 (-2.9%, 95% CI -1.3% to -4.5%) and post-2 (-2.9%, 95% CI -1.3% to -4.4%). There was no evidence of differences in slope. Variable trends in worker WRFI were observed for historically high-risk industry and occupational groups. CONCLUSIONS: The rate of worker WRFI decreased steadily over the 30-year period under examination and there was no evidence that this pattern of declining WRFI was substantially altered with the introduction of Robens-styled OHS legislative reforms. Beyond headline figures, historically high-risk groups had highly variable progress in reducing worker WRFI following legislative reform. This study demonstrates the value in including prereform data and high-risk subgroup analysis when assessing the performance of OHS legislative reforms to control occupational risks.

Missing cases of injury death: use of quantitative methods and case reviews to inform future improvements in case definition.

BACKGROUND: Knowledge of fatal injuries is required to inform prevention activities. Where hospital patients with an injury principal diagnosis (PDx) died and were certified to a medical underlying cause of death (UCoD), there is the potential to underestimate injury mortality. We sought to characterise injury/non-injury (NI) mismatches between PDx and UCoD by identifying which subgroups had small/large mismatches, and to understand why mismatches had occurred using informative examples. METHOD: Hospital records (n=10 234) with a PDx of injury were linked to the mortality collection using a unique personal identifier. Percentages UCoD coded to a NI were tabulated, for three follow-up periods and by selected variables. Additionally, we reviewed a sample of 70 records for which there was a mismatch. RESULTS: %NIs were 39%, 66% and 77% for time from injury to death of <1 week, <90 days and <1 year, respectively. Variations in %NI were found for all variables. Illustrative examples of 70 medical UCoD deaths showed that for 12 cases the injury event was unequivocally judged to have resulted in premature death. A further 16 were judged as injury deaths using balance of probability arguments. CONCLUSION: There is variation in rates of mismatch between PDx of injury and UCoD of NI. While legitimate reasons exist for mismatches in certain groups, a material number of injury deaths are not captured using UCoD alone; a new operational definition of injury death is needed. Early solutions are proposed. Further work is needed to investigate operational definitions with acceptable false positive and negative detection rates.

Prevalence and predictors of post-traumatic stress symptoms in 2200 hospitalised and non-hospitalised injured New Zealanders.

OBJECTIVE: Post-traumatic stress disorder following injuries unrelated to mass casualty events has received little research attention in New Zealand. Internationally, most studies investigating predictors of post-injury post-traumatic stress disorder focus on hospitalised patients although most survivors are not hospitalised. We compared the prevalence and predictors of symptoms suggestive of post-traumatic stress disorder 12 months following injury among hospitalised and non-hospitalised entitlement claimants in New Zealand's Accident Compensation Corporation. This government-funded universal no-fault insurance scheme replaced tort-based compensation for injuries in 1974 since when civil litigation (which can bias post-traumatic stress disorder estimates) has been rare. METHODS: A total of 2220 Accident Compensation Corporation claimants aged 18-64 years recruited to the Prospective Outcomes of Injury Study were interviewed at 12 months post-injury to identify symptoms suggestive of post-traumatic stress disorder using the Impact of Events Scale. Multivariable models examined the extent to which baseline sociodemographic, injury, health status and service interaction factors predicted the risk of post-traumatic stress disorder symptoms among hospitalised and non-hospitalised groups. RESULTS: Symptoms suggestive of post-traumatic stress disorder were reported by 17% of hospitalised and 12% of non-hospitalised participants. Perceived threat to life at the time of the injury doubled this risk among hospitalised (adjusted relative risk: 2.0; 95% confidence interval: 1.2-3.2) and non-hospitalised (relative risk: 1.8; 95% confidence interval: 1.2-2.8) participants. Among hospitalised participants, other predictors included female gender, Pacific and 'other' minority ethnic groups, pre-injury depressive symptoms, financial insecurity and perceived inadequacies in healthcare interactions, specifically information and time to discuss problems. Among non-hospitalised survivors, predictors included smoking, hazardous drinking, assault and poor expectations of recovery. CONCLUSION: One in six hospitalised and one in eight non-hospitalised people reported post-traumatic stress disorder symptoms 12 months following injury. Perceived threat to life was a strong predictor of this risk in both groups. Identifying early predictors of post-traumatic stress disorder, regardless of whether the injury required hospitalisation, could help target tailored interventions that can reduce longer-term psychosocial morbidity.

Access to advanced-level hospital care: differences in prehospital times calculated using incident locations compared with patients' usual residence.

Studies estimate that 84% of the USA and New Zealand's (NZ) resident populations have timely access (within 60 min) to advanced-level hospital care. Our aim was to assess whether usual residence (ie, home address) is a suitable proxy for location of injury incidence. In this observational study, injury fatalities registered in NZ's Mortality Collection during 2008-2012 were linked to Coronial files. Estimated access times via emergency medical services were calculated using locations of incident and home. Using incident locations, 73% (n=4445/6104) had timely access to care compared with 77% when using home location. Access calculations using patients' home locations overestimated timely access, especially for those injured in industrial/construction areas (18%; 95% CI 6% to 29%) and from drowning (14%; 95% CI 7% to 22%). When considering timely access to definitive care, using the location of the injury as the origin provides important information for health system planning.

Factors related to absence of toxicological investigation following fatal injury: a retrospective quantitative review of Coronial records in New Zealand.

PURPOSE: The accuracy of cause of death certification is strongly influenced by the quality of post mortem investigations (autopsies). In New Zealand, this can include toxicological investigation at the discretion of the Coroner. Little is known both within New Zealand and internationally about potential selection biases related to Coronial cases not undergoing toxicology investigation. METHODS: A retrospective review of eligible injury-related deaths referred to a Coroner in New Zealand in 2014 was undertaken. Using data collected from the Australasian National Coronial Information System and New Zealand's Mortality Collection, descriptive analyses were undertaken to understand patterns related to toxicology report requests and patterns within toxicology reports. RESULTS: In New Zealand in 2014, 25% of 744 Coronial cases for fatal injury in those under 85 years of age did not have corresponding toxicological reports. Reports were more likely to be absent in females (adjusted Odds Ratio (aOR) 1.7, 95%CI 1.0, 2.7), and in decedents aged under 15 and over 65 years (aOR 11.0 and 4.1 respectively). More than half (56%, 95% CI 45%, 67%) of the deaths due to falls did not receive toxicological investigation. CONCLUSION: Better understanding of selection biases in Coronial processes helps inform policymakers, researchers, and practitioners of the limitations of available toxicological evidence.

Developing the geographic classification for health, a rural-urban classification for New Zealand health research and policy: A research protocol.

INTRODUCTION: Rural-urban health inequities, exacerbated by deprivation and ethnicity, have been clearly described in the international literature. To date, the same inequities have not been as clearly demonstrated in Aotearoa New Zealand despite the lower socioeconomic status and higher proportion of Maori living in rural towns. This is ascribed by many health practitioners, academics and other informed stakeholders to be the result of the definitions of 'rural' used to produce statistics. AIMS: To outline a protocol to produce a 'fit-for-health purpose' rural-urban classification for analysing national health data. The classification will be designed to determine the magnitude of health inequities that have been obscured by use of inappropriate rural-urban taxonomies. METHODS: This protocol paper outlines our proposed mixed-methods approach to developing a novel Geographic Classification for Health. In phase 1, an agreed set of community attributes will be used to modify the new Statistics New Zealand Urban Accessibility Classification into a more appropriate classification of rurality for health contexts. The Geographic Classification for Health will then be further developed in an iterative process with stakeholders including rural health researchers and members of the National Rural Health Advisory Group, who have a comprehensive 'on the ground' understanding of Aotearoa New Zealand's rural communities and their attendant health services. This protocol also proposes validating the Geographic Classification for Health using general practice enrolment data. In phase 2, the resulting Geographic Classification for Health will be applied to routinely collected data from the Ministry of Health. This will enable current levels of rural-urban inequity in health service access and outcomes to be accurately assessed and give an indication of the extent to which older classifications were masking inequities.

Optimising base locations for New Zealand's Helicopter Emergency Medical Services.

Helicopter Emergency Medical Services (HEMS) in New Zealand (NZ) are located at hospitals or airports near the communities they serve. This may result in suboptimal response times. Timely access to advanced hospital care improves critically injured patients' chances of survival. This study optimised the location of HEMS bases in NZ and compared current versus optimal placement on timely access for surrounding populations. Optimal placement of HEMS bases could result in 113,886 additional people (3% of the population) benefiting from access to advanced hospital care within one hour. Optimal placement would especially benefit indigenous Maori as well as deprived and rural communities.

POIS-10 Maori: Outcomes and Experiences in the Decade Following Injury.

Injury-related disability burden extends well beyond two years post-injury, especially for Maori (Indigenous) New Zealanders. Maori also experience greater difficulty accessing health services. This prospective cohort study extension uses mixed-methods and aims to understand and identify factors contributing to long-term experiences and outcomes (positive and negative) at 12 years post-injury for injured Maori and their whanau (families), and explore the barriers and facilitators to whanau flourishing, and access to health and rehabilitation services. Five hundred and sixty-six Maori, who were injured between 2007-2009, participated in the Prospective Outcomes of Injury Study (POIS). Of these, 544 consented to long-term follow up, and will be invited to participate in a POIS-10 Maori interview at 12 years post-injury. We anticipate a 65% follow-up rate (~n = 350). Aligned with the Meihana Model, interviews will collect information about multiple inter-related dimensions. Administrative injury and hospitalisation data up to 12 years post-injury will also be collected. Regression models will be developed to examine predictors of long-term health and disability outcomes, after adjusting for a range of confounders. POIS-10 Maori will identify key points in the injury and rehabilitation pathway to inform future interventions to improve post-injury outcomes for Maori and whanau, and will highlight the support required for Maori flourishing post-injury.