Screening for Predictors of Post-Traumatic Stress Disorder following Major Trauma: SPIRAL-P Project
Haysom, S., University of Otago, Dunedin, New Zealand Ameratunga, S., Counties Manukau Health, Auckland, New Zealand Hawke, S., Counties Manukau Health, Auckland, New Zealand Henshall, K., Counties Manukau Health, Auckland, New Zealand Herman, J.A., Waitemata District Health Board, Auckland, New Zealand MacCormick, A., University of Auckland and Counties Manukau Health, Auckland, New Zealand
Introduction: Post-traumatic stress disorder (PTSD) is a disabling condition that affects over a fifth of patients following major trauma. The use of automated risk assessment tools that draw on data captured in electronic records can identify hospitalised trauma patients at increased risk of PTSD and initiate an equity-focused clinical support pathway across the recovery trajectory.
Aim: We investigated the extent to which the 10 factors in the PTSD prediction model developed by Russo and colleagues (2013) are documented in electronic records of patients admitted following major trauma to Middlemore Hospital.
Methods: We retrospectively reviewed the clinical records of all major trauma patients discharged from Middlemore Hospital in the middle month of each quarter in 2019. Using a standardised data collection instrument, we identified the proportion of records with data on the 10 PTSD predictors.
Results: Among the 76 patients who met study eligibility criteria (median age 46 years), 73% were male, and 34%, 9%, 15%, and 27% identified as Māori, Pasifika, Asian, and NZ European, respectively (prioritised ethnicity). All records documented information on gender, ethnicity and ICU admission. Most also noted the presence (or absence) of an intentional injury (96%), current/past psychiatric disorder (96%), alcohol/drug use problems (92%), and tobacco use (82%). Fewer records documented patients’ socioeconomic status (31%) and prior inpatient hospitalisation (27%), and none reported PTSD history.
Conclusion: High proportions of electronic records of trauma patients capture data on seven of 10 factors in the PTSD risk prediction tool. Greater efforts are required to eliminate missing information, particularly relating to tobacco use, socioeconomic status, prior hospitalisation and PTSD history. This would help implement an electronic PTSD risk assessment tool within a comprehensive equity-focused care pathway to identify and manage patients who can benefit from early interventions.
References: Russo J, Katon W, Zatzick D. General hospital psychiatry. 2013;35(5):485-91.