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G77(P) Improving the recognition of domestic violence in an urban emergency department
  1. S Timmis1,
  2. C Olimpio2,
  3. G Hann3,
  4. J Daniels3
  1. 1Paediatrics and Child Health, University College London, London, UK
  2. 2Accident and Emergency Department, North Middlesex University Hospital, London, UK
  3. 3Department of Paediatrics, North Middlesex University Hospital, London, UK


Aim Domestic violence (DV), substance misuse and psychiatric disorders are major risk factors that substantially increase the likelihood of child abuse or neglect. DV is common but rates of detection are low among emergency professionals, who are often the first port of call for victims. Our project aimed to improve awareness and recognition of DV in an urban emergency department.

Methods A retrospective notes audit of women aged 16–65 years presenting with injury or assault was conducted over two, two-month periods (1st phase and 2nd phase), with detailed analysis of patient notes done in two two-week sampling frames during each phase. Between these two phases a diagnostic algorithm was introduced to remind clinicians to consider DV and inquire about children at home. Training sessions for emergency staff were organised. The algorithm was inserted into the notes in the form of stickers by the triage nurse. Clinicians attending the injured women would then complete the algorithm and make the appropriate DV and child protection referrals.

Results 743 eligible patient notes were reviewed. 373 women presented to the emergency department with injury or assault in the 1st phase and 370 in the 2nd phase. There was an initial low uptake of the algorithm and barriers to its use were identified via staff questionnaire. This resulted in supplementary training sessions and email reminders. Although overall comparison between the 1st and 2nd phases of data collection showed no significant increase in the identification of DV, after addressing staff concerns, there was a significant increase in the use of the algorithm in the last 2 weeks of the 2nd phase with the diagnosis of DV increasing from 5 to 10% (p ≤ 0.048). 31% of women identified with DV in the 2nd phase had children, which were then referred to social care.

Conclusion The use of a diagnostic algorithm together with regular staff training sessions has the potential to increase identification of DV. This will not only help protect vulnerable women but also their children, and offers the opportunity for early support and referral to the appropriate services.

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