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.

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.

Evaluating the impact of prehospital care on mortality following major trauma in New Zealand: a retrospective cohort study.

BACKGROUND: Injury is a leading cause of death and health loss in New Zealand and internationally. The potentially fatal or severe consequences of many injuries can be reduced through an optimally structured prehospital trauma care system that can provide timely and appropriate care. OBJECTIVE: To investigate the relationship between emergency medical services (EMS) care and survival to hospital for major trauma cases in New Zealand. METHODS: This project is a retrospective cohort study of New Zealand major trauma cases attended by EMS providers over a 2-year period. Outcomes include survival to hospital and survival in hospital for at least 24 hours. The project has three phases: (1) identification of the cohort and assembling a bespoke longitudinal dataset linking EMS, New Zealand Major Trauma Registry and Coronial data; (2) describing the pathways and processes of care to inform an investigation of the relationships between types of EMS care and survival using propensity score modelling to adjust for case-mix differences; (3) assessment of the implications for future practice, policy and research. DISCUSSION: The study findings will help identify opportunities to optimise the delivery of EMS care in New Zealand by informing the development or revision of existing major trauma EMS policies and guidelines, and to provide a baseline for monitoring the impact of future initiatives. Establishing an evidence-base will support a whole-of-system appraisal that could include broader complex variables relating to healthcare services throughout the continuum of trauma care.

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.

Potential survivability of prehospital injury deaths in New Zealand: a cross-sectional study.

INTRODUCTION: Acknowledging a notable gap in available evidence, this study aimed to assess the survivability of prehospital injury deaths in New Zealand. METHODS: A cross-sectional review of prehospital injury death postmortems (PM) undertaken during 2009-2012. Deaths without physical injuries (eg, drownings, suffocations, poisonings), where there was an incomplete body, or insufficient information in the PM, were excluded. Documented injuries were scored using the AIS and an ISS derived. Cases were classified as survivable (ISS <25), potentially survivable (ISS 25-49) and non-survivable (ISS >49). RESULTS: Of the 1796 cases able to be ISS scored, 11% (n=193) had injuries classified as survivable, 28% (n=501) potentially survivable and 61% (n=1102) non-survivable. There were significant differences in survivability by age (p=0.017) and intent (p<0.0001). No difference in survivability was observed by sex, ethnicity, day of week, seasonality or distance to advanced-level hospital care. 'Non-survivable' injuries occurred more commonly among those with multiple injuries, transport-related injuries and aged 15-29 year. The majority of 'survivable' cases were deceased when found. Among those alive when found, around half had received either emergency medical services (EMS) or bystander care. One in five survivable cases were classified as having delays in receiving care. DISCUSSION: In New Zealand, the majority of injured people who die before reaching hospital do so from non-survivable injuries. More than one third have either survivable or potentially survivable injuries, suggesting an increased need for appropriate bystander first aid, timeliness of EMS care and access to advanced-level hospital care.

Preventable injury deaths: identifying opportunities to improve timeliness and reach of emergency healthcare services in New Zealand.

BACKGROUND: Traumatic injury is a leading cause of premature death and health loss in New Zealand. Outcomes following injury are very time sensitive, and timely access of critically injured patients to advanced hospital trauma care services can improve injury survival. OBJECTIVE: This cross-sectional study will investigate the epidemiology and geographic location of prehospital fatal injury deaths in relation to access to prehospital emergency services for the first time in New Zealand. DESIGN AND STUDY POPULATION: Electronic Coronial case files for the period 2008-2012 will be reviewed to identify cases of prehospital fatal injury across New Zealand. METHODS: The project will combine epidemiological and geospatial methods in three research phases: (1) identification, enumeration, description and geocoding of prehospital injury deaths using existing electronic injury data sets; (2) geocoding of advanced hospital-level care providers and emergency land and air ambulance services to determine the current theoretical service coverage in a specified time period and (3) synthesising of information from phases I and II using geospatial methods to determine the number of prehospital injury deaths located in areas without timely access to advanced-level hospital care. DISCUSSION: The findings of this research will identify opportunities to optimise access to advanced-level hospital care in New Zealand to increase the chances of survival from serious injury. The resulting epidemiological and geospatial analyses will represent an advancement of knowledge for injury prevention and health service quality improvement towards better patient outcomes following serious injury in New Zealand and similar countries.

Empirical validation of the New Zealand serious non-fatal injury outcome indicator for 'all injury'.

Our purpose was to empirically validate the official New Zealand (NZ) serious non-fatal 'all injury' indicator. To that end, we aimed to investigate the assumption that cases selected by the indicator have a high probability of admission. Using NZ hospital in-patient records, we identified serious injury diagnoses, captured by the indicator, if their diagnosis-specific survival probability was ≤0.941 based on at least 100 admissions. Corresponding diagnosis-specific admission probabilities from regions in Canada, Denmark and Greece were estimated. Aggregate admission probabilities across those injury diagnoses were calculated and inference made to New Zealand. The admission probabilities were 0.82, 0.89 and 0.90 for the regions of Canada, Denmark and Greece, respectively. This work provides evidence that the threshold set for the official New Zealand serious non-fatal injury indicator for 'all injury' captures injuries with high aggregate admission probability. If so, it is valid for monitoring the incidence of serious injuries.

Towards valid 'serious non-fatal injury' indicators for international comparisons based on probability of admission estimates.

BACKGROUND: Governments wish to compare their performance in preventing serious injury. International comparisons based on hospital inpatient records are typically contaminated by variations in health services utilisation. To reduce these effects, a serious injury case definition has been proposed based on diagnoses with a high probability of inpatient admission (PrA). The aim of this paper was to identify diagnoses with estimated high PrA for selected developed countries. METHODS: The study population was injured persons of all ages who attended emergency department (ED) for their injury in regions of Canada, Denmark, Greece, Spain and the USA. International Classification of Diseases (ICD)-9 or ICD-10 4-digit/character injury diagnosis-specific ED attendance and inpatient admission counts were provided, based on a common protocol. Diagnosis-specific and region-specific PrAs with 95% CIs were calculated. RESULTS: The results confirmed that femoral fractures have high PrA across all countries studied. Strong evidence for high PrA also exists for fracture of base of skull with cerebral laceration and contusion; intracranial haemorrhage; open fracture of radius, ulna, tibia and fibula; pneumohaemothorax and injury to the liver and spleen. Slightly weaker evidence exists for cerebellar or brain stem laceration; closed fracture of the tibia and fibula; open and closed fracture of the ankle; haemothorax and injury to the heart and lung. CONCLUSIONS: Using a large study size, we identified injury diagnoses with high estimated PrAs. These diagnoses can be used as the basis for more valid international comparisons of life-threatening injury, based on hospital discharge data, for countries with well-developed healthcare and data collection systems.

Managing distance and covariate information with point-based clustering.

BACKGROUND: Geographic perspectives of disease and the human condition often involve point-based observations and questions of clustering or dispersion within a spatial context. These problems involve a finite set of point observations and are constrained by a larger, but finite, set of locations where the observations could occur. Developing a rigorous method for pattern analysis in this context requires handling spatial covariates, a method for constrained finite spatial clustering, and addressing bias in geographic distance measures. An approach, based on Ripley's K and applied to the problem of clustering with deliberate self-harm (DSH), is presented. METHODS: Point-based Monte-Carlo simulation of Ripley's K, accounting for socio-economic deprivation and sources of distance measurement bias, was developed to estimate clustering of DSH at a range of spatial scales. A rotated Minkowski L1 distance metric allowed variation in physical distance and clustering to be assessed. Self-harm data was derived from an audit of 2 years' emergency hospital presentations (n = 136) in a New Zealand town (population ~50,000). Study area was defined by residential (housing) land parcels representing a finite set of possible point addresses. RESULTS: Area-based deprivation was spatially correlated. Accounting for deprivation and distance bias showed evidence for clustering of DSH for spatial scales up to 500 m with a one-sided 95 % CI, suggesting that social contagion may be present for this urban cohort. CONCLUSIONS: Many problems involve finite locations in geographic space that require estimates of distance-based clustering at many scales. A Monte-Carlo approach to Ripley's K, incorporating covariates and models for distance bias, are crucial when assessing health-related clustering. The case study showed that social network structure defined at the neighbourhood level may account for aspects of neighbourhood clustering of DSH. Accounting for covariate measures that exhibit spatial clustering, such as deprivation, are crucial when assessing point-based clustering.

The impact of a rural scanner in overcoming urban versus rural disparities in the utilisation of computed tomography.

OBJECTIVE: In 2008, Oamaru Hospital became the second rural hospital in New Zealand to install a computed tomography (CT) scanner. This article assesses the impact of this on local CT scanning rates. DESIGN: Observational: review of radiology department data. SETTING: Rural hospital imaging services. PARTICIPANTS: CT scanning patients residing in Otago region during the study period. INTERVENTIONS: There is no intervention in this observational study. MAIN OUTCOME MEASURES: CT scanning rates and waiting times before and after the introduction of the rural scanner. RESULTS: Prior to the scanner being commissioned, there was a significant urban versus rural disparity in CT utilisation. Residents in the neighbouring urban centre were 1.4 times more likely to access CT (33.2 (95% confidence interval (CI) 32.2-34.2) versus 23.0 (95% CI 21.0-25.1) scans per 1000 residents per annum). Twenty months after the scanner was commissioned, the rate for the rural community had almost doubled to 45.6 (95% CI 43.0-48.2) and was 1.2 times greater than for the urban community. This difference was not sustained, and rural and urban communities had similar CT scanning rates in 2011 and 2012. Mean waiting time for residents in the rural community fell from 21.1 (95% CI 17.1-25.2) days prior to the scanner to 6.7 (95% CI 5.6-7.8) days after the scanner was commissioned. CONCLUSIONS: On-site CT increased the rural scanning rate, corrected the rural-urban disparity and reduced waiting times without apparent over servicing.

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.

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

BACKGROUND AND OBJECTIVES: All publicly funded hospital discharges in Aotearoa New Zealand 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 hospitalization (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 Hospitalization (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 rate ratios (IRRs), the mean total length of stay and the percentage of interhospital transfers were estimated for each bundling method. These outcomes were compared across 4 categories of the Geographic Classification for Health. RESULTS: Compared with no bundling, using the date-based method resulted in an 8.3% reduction (150 less hospitalizations 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 interhospital 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 overestimation of incidence rates and the undercounting of interhospital transfers and total length of stay.

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.

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.

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).

Factors associated with self-reported health among New Zealand military veterans: a cross-sectional study.

OBJECTIVE: To identify factors associated with better or poorer self-reported health status in New Zealand military Veterans. DESIGN: A cross-sectional survey. PARTICIPANTS: The participants of interest were the 3874 currently serving Veterans who had been deployed to a conflict zone, but all Veterans were eligible to participate. STUDY VARIABLES: The EQ-5D-5L, asking about problems across five dimensions (mobility, self-care, usual activities, pain or discomfort and anxiety or depression), with five levels of severity (eg, no, slight, moderate, severe or extreme problems), also containing a Visual Analogue Scale (EQ-VAS) to self-assess health state, scaled from 0 (worst) to 100 (best) imagined health.Hypothetical relationships with better health were positive social support, sleep and psychological flexibility; with poorer health, post-traumatic stress, exposure to psychological trauma, distress and hazardous drinking. RESULTS: The EQ5-D-5L was completed by 1767 Veterans, 1009 serving, a response rate of 26% from that group, 1767 completing the EQ5-D, 1458 who had deployed, 288 who had not and the 21 who did not provide deployment data. Of these, 247 were not used in the analysis due to missing values in one or more variables, leaving 1520 for analysis.A significantly higher proportion of Veterans reported 'any problems' rather than 'no problems' with four EQ-5D dimensions: mobility, self-care, usual activities and pain or discomfort, but no difference in anxiety or depression. Age, length of service, deployment, psychological flexibility and better sleep quality were associated with higher EQ-VAS scores; distress with lower EQ-VAS scores. CONCLUSION: In this sample of New Zealand Veterans, psychological flexibility and good sleep are associated with better self-rated health, and distress and poor sleep with diminished health. These factors might be used as sentinel health indicators in assessing Veteran health status, and cognitive-behavioural therapy encompassing these domains may be useful in improving the health of New Zealand Veterans.

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.

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.

Opportunities to prevent fatalities due to injury: a cross-sectional comparison of prehospital and in-hospital fatal injury deaths in New Zealand.

OBJECTIVE: There is interest in opportunities that lie in the prehospital setting to reduce the substantial burden of fatal injury. This study examines the epidemiology of prehospital and in-hospital fatal injury in New Zealand. METHODS: All deaths registered in 2008-2012 with an underlying cause of death external cause-code V01-Y36 (ICD-10-AM) were identified. The setting of death was determined following linkage to, and review of, hospital discharge data and Coronial records. RESULTS: Of 7,522 injury deaths, 80% occurred in a prehospital setting, with the highest burden relating to males. Within those fatally injured, 25-54-year-olds had a higher risk of prehospital death than 55-84-year-olds (adjusted Relative Risk [aRR] 1.20, 95%CI 1.16, 1.20). Similarly, those injured due to drowning (aRR 1.39, CI 1.26, 1.53) and non-hanging suffocation (aRR 1.31, CI 1.18, 1.45) had a higher risk of prehospital death than those 'struck by/machinery'. CONCLUSION: Prehospital deaths account for four out of five fatal injuries in New Zealand. Of the fatally injured population, the probability of prehospital death differed by age, sex, injury mechanism and intent. Implications for public health: This study highlights the importance of strengthening prevention efforts to reduce the substantive burden of prehospital fatalities in New Zealand.

Access to specialist hospital care and injury survivability: identifying opportunities through an observational study of prehospital trauma fatalities.

BACKGROUND: Of the five million injury deaths that occur globally each year, an estimated 70% occur before the injured person reaches hospital. Although reducing the time from injury to definitive care has been shown to achieve better outcomes for patients, the relationship between injury incident location and access to specialist care has been largely unexplored. OBJECTIVE: To determine the number and distribution of prehospital (on-scene/en route) trauma deaths without timely access to a hospital with surgical and intensive care capabilities, overall and by estimated injury survivability. METHODS: New Zealand's Mortality Collection and Hospital Discharge dataset were used to select prehospital injury deaths in 2009-2012. These records were linked to files held by Australasia's National Coronial Information Service (NCIS) to estimate, for the trauma subset, injury survivability. Using geographical locations of injury for the prehospital trauma fatalities, time from Emergency Medical System call-out to arrival at the closest specialist hospital was estimated. RESULTS: Of 1,752 prehospital trauma fatalities, 14.7% (95%CI 13.0, 16.4) had potentially survivable injuries that occurred in locations without timely access (prehospital phase >60 minutes). More than half (132 of 257) of the potentially survivable prehospital trauma fatalities without timely access died as a result of a motor vehicle traffic crash. Only 10% (95%CI 5.7, 16.0) of prehospital trauma fatalities from falls were estimated to be potentially survivable and without timely access compared to 24.6% (95%CI 18.5, 31.5) of prehospital firearm fatalities. Through using geospatial techniques, "hot spot" locations of potentially survivable injuries without timely access to specialist major trauma hospitals were apparent. CONCLUSION: Approximately 15% of prehospital trauma fatalities in New Zealand that are potentially survivable occur in locations without timely access to advanced level hospital care. Continued emphasis is required on both improving timely access to advanced trauma care, and on primary prevention of serious injuries. Decisions regarding trauma service delivery, a modifiable system-level factor, should consider the geographic distribution of locations of these injury events alongside the resident population distribution.