We conducted a single-center registry-based retrospective cohort study. We used data from the Karolinska University Hospital trauma registry, which reports to the Swedish National Trauma Registry, [16] as well as the hospital’s local trauma care quality database. The content of the trauma registry has been previously described [17]. From 2017 and onwards the trauma care quality database includes all patients in the trauma registry as well as the results of the morbidity and mortality review, including identified OFI. We linked the trauma registry and trauma care quality database using personal identification numbers and extracted factors potentially associated with OFI.

All major trauma patients in the greater metropolitan area of Stockholm are triaged to the Karolinska University Hospital in Solna, which is equivalent to a level one trauma center according to the criteria set by the American College of Surgeons [18]. The hospital has direct access to radiology, intervention, surgery, intensive care and consultants in all associated specialties [19, 20]. All trauma patients presenting to Karolinska University Hospital are included in a morbidity and mortality screening process that combines individual review by specialized nurses and audit filters, shown in Table 1. Patients identified as having a high potential for OFIs are discussed in multidisciplinary conferences. Examples of potential OFIs identified in this screening process include the need for more senior members assisting the trauma team or need for additional emergency operating rooms, which are then categorised into broader categories such as lack of resources and logistics. The multidisciplinary conferences take place every six to eight weeks and last about one hour. During the conferences, an average of ten patient cases are reviewed by experienced specialists from all the disciplines and professions involved in trauma care. The presence or absence of OFI is a consensus decision among all participants of the conference and is recorded in the trauma care quality database.

The trauma registry includes all patients admitted with trauma team activation, regardless of Injury Severity Score (ISS), as well as patients admitted without trauma team activation but found to have an ISS of more than 9. We included all patients who had been included in the morbidity and mortality screening process between January 1, 2017 and June 1, 2021. We excluded patients who were younger than 15 years and patients who were dead on arrival.

The outcome was the presence of OFI, as decided by the morbidity and mortality conference. An OFI is any failure of care including, but not limited to, any potentially preventable or preventable death, delay in treatment, clinical judgment error, missed diagnosis and technical error as decided by the mortality and morbidity conference. The study outcome is binary with the levels “Yes - At least one OFI identified” and “No - No OFI identified”.

We selected factors from the trauma registry, based on the locally used audit filters (Table 1), standard epidemiological factors and factors registered in the Swedish National Trauma Registry. The categorical factors were sex, survival after 30 days, highest hospital care level, Glasgow Coma Scale (GCS), respiratory rate, systolic blood pressure, working hours, weekend, time from arrival at the hospital until first computed tomography (CT) and if the patient was intubated. We also included the continuous factors age and ISS, and categorised these using standard cutoffs.

In the trauma registry, both systolic blood pressure and respiratory rate are registered as either a continuous value or a Revised Trauma Score category [21]. We converted the continuous values of systolic blood pressure and respiratory rate, if registered, and GCS score into the corresponding Revised Trauma Score category. If the patient was intubated and missing values for respiratory rate and GCS score, prehospital pre-intubation values were used.

The factor highest hospital care level, defined as the highest level of in-hospital care the patient being admitted to, is divided into five categories: emergency department, general ward, operating theatre, high dependency unit and critical care unit. The category emergency department means that the patient was not admitted, but was either discharged from or died in the emergency department. The category general ward is all wards with no further monitoring. The category operating theatre is assigned to patients who undergo surgery but who are not admitted to a high dependency or critical care unit post-operatively. High dependency units are wards with more extensive monitoring. Patients with multi-organ failure or who require mechanical ventilation are admitted to critical care units.

Factors denoting if the patient arrived at the hospital during working hours were included, defined as between 8.00 a.m. and 5 p.m., or during a weekend, defined as Saturday or Sunday.

A complete case analysis was conducted after handling missing values in systolic blood pressure, respiratory rate, and GCS score as described above. We present sample characteristics using descriptive statistics. Bivariable logistic regression was used to determine unadjusted associations and multivariable logistic regression to determine adjusted associations between patient and process factors and OFI. We present odds ratios (OR) with associated 95% confidence intervals. A significance level of 5% was used. The programming language R was used for all analyses [22]. All statistical analysis was first done on synthetic data and later implemented on the data collected from the trauma registry and the trauma care quality database to ensure objectivity.