The Prospective Outcomes of Injury Study aims to identify predictors of disability following injury. Participants were selected from the entitlement claims register of New Zealand's no-fault compensation insurer, the Accident Compensation Corporation, and followed up by interview for 2 years. This report describes changes to intended Prospective Outcomes of Injury Study methods and key characteristics of the cohort, with an emphasis on general health and disability before injury and soon afterwards. There were 2856 injured participants in the first interview, which occurred 3.2 months (median) after injury. The recruitment period was extended to enable inclusion of sufficient Māori participants. At the first interview, most participants were experiencing worse health status and increased disability compared to before injury, despite less than one-third reporting admission to hospital because of their injury. Analysis of outcome predictors related to post-injury function, disability and return-to-work soon after injury and 1 year later is now under way.

Background: Injury outcome studies have tended to collect limited pre-injury characteristics, focus on a narrow range of injury types, predictors and outcomes, and be restricted to high threat to life injuries. We sought to identify the role of pre-injury socio-demographic and health characteristics, injury and injury-related healthcare in determining short-term functional outcomes for a wide range of injuries. Methods: Study participants (aged 18-64 years inclusive) were those in the Prospective Outcomes of Injury Study, a cohort of 2856 persons who were injured and registered with New Zealand's national no-fault injury insurance agency. All information used in this paper was obtained directly from the participants, primarily by telephone interviews, approximately three months after their injury. The functional outcomes of interest were the five dimensions of the EQ-5D plus a cognitive dimension. We initially examined bivariate relationships between our independent measures and the dependent measures. Our multivariate analyses included adjustment for pre-injury EQ-5D status and time between injury and when information was obtained from participants. Results: Substantial portions of participants continued to have adverse outcomes approximately three months after their injury. Key pervasive factors predicting adverse outcomes were: being female, prior chronic illness, injuries to multiple body regions, being hospitalized for injury, self-perceived threat to life, and difficulty accessing health services. Conclusion: Future injury outcome studies should include participants whose injuries are considered 'minor', as judged by acute health service utilization, and also consider a wider range of potential predictors of adverse outcomes.

Background: In New Zealand (NZ), 20% of adults report a disability, of which one-third is caused by injury. No prospective epidemiological studies of predictors of disability following all-cause injury among New Zealanders have been undertaken. Internationally, studies have focused on a limited range of predictors or specific injuries. Although these studies provide useful insights, applicability to NZ is limited given the importance of NZ’s unique macro-social factors, such as NZ’s no-fault accident compensation and rehabilitation scheme, the Accident Compensation Corporation (ACC). Objectives: (1) To quantitatively determine the injury, rehabilitation, personal, social and economic factors leading to disability outcomes following injury in NZ. (2) To qualitatively explore experiences and perceptions of injury-related outcomes in face-to-face interviews with 15 Māori and 15 other New Zealanders, 6 and 12 months after injury. Setting: Four geographical regions within NZ. Design: Prospective cohort study with telephone interviews 1, 4 and 12 months after injury. Participants: 2500 people (including 460 Māori), aged 18–64 years, randomly selected from ACC’s entitlement claims register (people likely to be off work for at least 1 week or equivalent). Data: Telephone interviews, electronic hospital and ACC injury data. Exposures include demographic, social, economic, work-related, health status, participation and/or environmental factors. Outcome measures: Primary: disability (including WHODAS II) and health-related quality of life (including EQ-5D). Secondary: participation (paid and unpaid activities), life satisfaction and costs. Analysis: Separate regression models will be developed for each of the outcomes. Repeated measures outcomes will be modelled using general estimating equation models and generalised linear mixed models.

To reduce the burden on injury survivors and their supporters, factors associated with poor outcomes need to be identified so that timely post-injury interventions can be implemented. To date, few studies have investigated outcomes for both those who were hospitalised and those who were not. To describe the prevalence and to identify pre-injury and injury-related predictors of disability among hospitalised and non-hospitalised people, three months after injury. Participants in the Prospective Outcomes of Injury Study were aged 18–64 years and on an injury entitlement claims register with New Zealand's no-fault injury compensation insurer, following referral by healthcare professionals. A wide range of pre-injury demographic, health and injury-related characteristics were collected at interview. Participants were categorised as ‘hospitalised’ if they were placed on New Zealand's National Minimum Data Set within seven days of the injury event. Injury severity scores (NISS) and 12 injury categories were derived from ICD-10 codes. WHODAS assessed disability. Multivariable analyses examined relationships between explanatory variables and disability. Of 2856 participants, 2752 (96%) had WHODAS scores available for multivariable analysis; 673 were hospitalised; 2079 were not. Disability was highly prevalent among hospitalised (53.6%) and non-hospitalised (39.4%) participants, three-months after injury. In both groups, pre-injury disability, obesity and higher injury severity were associated with increased odds of post-injury disability. A range of other factors were associated with disability in only one group: e.g. female, ≥2 chronic conditions and leg fracture among hospitalised; aged 35–54 years, trouble accessing healthcare, spine or lower extremity sprains/dislocations and assault among non-hospitalised. Disability was highly prevalent among both groups yet, with a few exceptions, factors associated with disability were not common to both groups. Where possible, including a range of injured people in studies, hospitalised and not, will increase understanding of the burden of disability in the sub-acute phase.

Most studies investigating disability outcomes following injury have examined hospitalised patients. It is not known whether variables associated with disability outcomes are similar for injured people who are not hospitalised. This paper compares the prevalence of disability 24 months after injury for participants in the Prospective Outcomes of Injury Study who were hospitalised and those non-hospitalised, and also seeks to identify pre-injury and injury-related predictors of disability among hospitalised and non-hospitalised participants. Participants, aged 18–64 years, were recruited from an injury claims register managed by New Zealand’s no-fault injury compensation insurer after referral by health care professionals. A wide range of pre-injury socio-demographic, health and psychosocial characteristics were collected, as well as injury-related characteristics; outcome is assessed using the WHODAS. Multivariable models estimating relative risks of disability for hospitalised and non-hospitalised participants were developed using Poisson regression methods. Of 2856 participants, analyses were restricted to 2184 (76%) participants for whom both pre-injury and 24 month WHODAS data were available. Of these, 25% were hospitalised. In both hospitalised and non-hospitalised groups, 13% experience disability (WHODAS≥10) 24 months after injury; higher than pre-injury (5%). Of 28 predictor variables, seven independently placed injured participants in the hospitalised group at increased risk of disability 24 months after injury; eight in the non-hospitalised. Only four predictors (pre-injury disability, two or more pre-injury chronic conditions, pre-injury BMI≥30 and trouble accessing healthcare services) were common to both the hospitalised and non-hospitalised groups. There is some evidence to suggest that among the hospitalised group, Māori have higher risk of disability relative to non-Māori. At 24 months considerable disability is borne, equally, by hospitalised and non-hospitalised groups. However, predictors of disability are not necessarily consistent between the hospitalised and non-hospitalised groups, suggesting caution in generalising results from one group to the other.

Objectives Despite significant international interest in the economic impacts of health inequities, few studies have quantified the costs associated with unfair and preventable ethnic/racial health inequities. This Indigenous-led study is the first to investigate health inequities between Māori and non-Māori adults in New Zealand (NZ) and estimate the economic costs associated with these differences. Design Retrospective cohort analysis. Quantitative epidemiological methods and ‘cost-of-illness’ (COI) methodology were employed, within a Kaupapa Māori theoretical framework. Setting Data for 2003–2014 were obtained from national data collections held by NZ government agencies, including hospitalisations, mortality, outpatient and primary care consultations, laboratory and pharmaceutical usage and accident claims. Participants All adults in NZ aged 15 years and above who had engagement with the health system between 2003 and 2014 (deidentified). Primary and secondary outcome measures Rates of ‘potentially avoidable’ hospitalisations and mortality as well as ‘excess or underutilisation’ of healthcare were calculated, as the difference between actual rates for Māori and the rate expected if Māori had the same rates as non-Māori. These differences were then quantified using COI methodology to estimate the financial cost of ethnic inequities. Results In this conservative estimate, health inequities between Māori and non-Māori adults cost NZ$863.3 million per year. Direct costs of NZ$39.9 million per year included costs from ambulatory sensitive hospitalisations and outpatient care, with cost savings from underutilisation of primary care. Indirect costs of NZ$823.4 million per year came from years of life lost and lost wages. Conclusions Indigenous adult health inequities in NZ create significant direct and indirect costs. The ‘cost of doing nothing’ is predominantly borne by Indigenous communities and society. The net cost of adult health inequities to the government conceals substantial savings to the government from underutilisation of primary care and accident/injury care.