PT - JOURNAL ARTICLE AU - S Derrett AU - J Langley AU - B Hokowhitu AU - S Ameratunga AU - P Hansen AU - G Davie AU - E Wyeth AU - R Lilley TI - Prospective outcomes of injury study AID - 10.1136/ip.2009.022558 DP - 2009 Oct 01 TA - Injury Prevention PG - e3--e3 VI - 15 IP - 5 4099 - http://injuryprevention.bmj.com/content/15/5/e3.short 4100 - http://injuryprevention.bmj.com/content/15/5/e3.full SO - Inj Prev2009 Oct 01; 15 AB - 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.