Prospective outcomes of injury study. Issue 5 (5th October 2009)

• Record Type: Journal Article
• Authors: Derrett, S; Langley, J; Hokowhitu, B; Ameratunga, S; Hansen, P; Davie, G; Wyeth, E; Lilley, R
• Is Part Of: Injury prevention. Volume 15:Issue 5(2009)
• Page Start: e3
• Page End: e3
• Publication Date: 2009-10-05
• Subjects: Children's accidents -- Prevention -- Periodicals; Accidents -- Prevention -- Periodicals; 617.1
• DOI: 10.1136/ip.2009.022558
• Languages: English
• ISSNs: 1353-8047

Abstract

Abstract : 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.