Domestic violence and injuries: prevalence and patterns—a pilot database study to identify suspected cases in a UK major trauma centre. Issue 5 (25th May 2022)

• Record Type: Journal Article
• Authors: Garbett, Hollie; Carter, Ben; Gregory, Alison; Cramer, Helen; Lewis, Natalia V; Morgan, Karen; Thompson, Julian; Feder, Gene; Braude, Philip
• Is Part Of: Injury prevention. Volume 28:Issue 5(2022)
• Page Start: 429
• Page End: 433
• Publication Date: 2022-05-25
• Subjects: trauma systems -- multiple injury -- older people -- home; Children's accidents -- Prevention -- Periodicals; Accidents -- Prevention -- Periodicals; 617.1
• DOI: 10.1136/injuryprev-2021-044481
• Languages: English
• ISSNs: 1353-8047

Abstract

Abstract : Background: Victim-survivors of domestic violence and abuse (DVA) present to secondary care with isolated injuries to the head, limb or face. In the UK, there are no published studies looking at the relationship of significant traumatic injuries in adults and the relationship to DVA. The primary objective was to assess the feasibility of using a tailored search method to identify cases of suspected DVA in the national audit database for trauma. The secondary objective was to assess the association of DVA with clinical characteristics. Methods: We undertook a single-centre retrospective observational cohort pilot study. Data were analysed from the local Trauma and Audit Research Network (TARN) database. The 'Scene Description' field in the database was searched using a tailored search strategy. Feasibility was evaluated with notes review and assessed by the PPV and prevalence. Secondary objectives used a logistic regression in Excel. Results: This method of identifying suspected cases of DVA from the TARN database is feasible. The PPV was 100%, and the prevalence of suspected DVA in the study period was 3.6 per 1000 trauma discharges. Of those who had experienced DVA, 52.7% were male, median age 43 (IQR: 33–52) and mortality 5.5%. Subgroup analysis of older people demonstrated longer hospital stay (p=0.17) and greater likelihood of admission to intensive care (OR 2.60, 95% CI 0.48 to 14.24). Conclusion: We have created a feasible methodology to identify suspected DVA-related injuries within the TARN database. Future work is needed to further understand this relationship on a national level.