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Background: Triage is essential for efficient and effective delivery of care in emergency centers (ECs) where numerous patients present simultaneously with varying acuity of conditions. Implementing EC triage systems provides a method of recognizing which patients may require admission and are at higher risks for poor health outcomes. Rwanda is experiencing increased demand for emergency care; however, triage has not been well-studied. The University Teaching Hospital of Kigali (UTH-K) is an urban tertiary care health center utilizing a locally modified South African Triage Score (mSATS) that classifies patients into five color categories. Our study evaluated the utility of the mSATS tool at UTH-K. Methods: UTH-K implemented mSATS in April 2013. All patients aged 15 years or older from August 2015 to July 2016 were eligible for inclusion in the database. Variables of interest included demographic information, mSATS category, patient case type (trauma or medical), disposition from the ED and mortality. Results: 1438 cases were randomly sampled; the majority were male (61.9%) and median age was 35 years. Injuries accounted for 56.7% of the cases while medical conditions affected 43.3%. Admission likelihood significantly increased with higher triage color category for medical patients (OR: Yellow = 3.61, p

Introduction: Although emergency medicine (EM) training programmes have begun to be introduced in low- and middle-income countries (LMICs), minimal data exist on their effects on patient-centered outcomes in such settings. This study evaluated the impact of EM training and associated systems implementation on mortality among patients treated at the University Teaching Hospital-Kigali (UTH-K). Methods: At UTH-K an EM post-graduate diploma programme was initiated in October 2013, followed by a residency-training programme in August 2015. Prior to October 2013, care was provided exclusively by general practice physicians (GPs); subsequently, care has been provided through mutually exclusive shifts allocated between GPs and EM trainees. Patients seeking Emergency Centre (EC) care during November 2012–October 2013 (pre-training) and August 2015–July 2016 (post-training) were eligible for inclusion. Data were abstracted from a random sample of records using a structured protocol. The primary outcomes were EC and overall hospital mortality. Mortality prevalence and risk differences (RD) were compared pre- and post-training. Magnitudes of effects were quantified using regression models to yield adjusted odds ratios (aOR) with 95% confidence intervals (CI). Results: From 43,213 encounters, 3609 cases were assessed. The median age was 32 years with a male predominance (60.7%). Pre-training EC mortality was 6.3% (95% CI 5.3–7.5%), while post-training EC mortality was 1.2% (95% CI 0.7–1.8%), constituting a significant decrease in adjusted analysis (aOR = 0.07, 95% CI 0.03–0.17; p

Introduction: Injuries account for 10% of the global burden of disease, resulting in approximately 5.8 million deaths annually. Trauma registries are an important tool in the development of a trauma system; however, limited resources in low- and middle-income countries (LMIC) make the development of high-quality trauma registries challenging. We describe the development of a LMIC trauma registry based on a robust retrospective chart review, which included data derived from prehospital, emergency centre and inpatient records. Methods: This paper outlines our methods for identifying and locating patients and their medical records using pragmatic and locally appropriate record linkage techniques. A prehospital database was queried to identify patients transported to University Teaching Hospital – Kigali, Rwanda from December 2012 through February 2015. Demographic information was recorded and used to create a five-factor identification index, which was then used to search OpenClinic GA, an online open source hospital information system. The medical record number and archive number obtained from OpenClinic GA were then used to locate the physical medical record for data extraction. Results: A total of 1668 trauma patients were transported during the study period. 66.7% were successfully linked to their medical record numbers and archive codes. 94% of these patients were successfully linked to their medical record numbers and archive codes were linked by four or five of the five pre-set identifiers. 945 charts were successfully located and extracted for inclusion in the trauma registry. Record linkage and chart extraction took approximately 1256 h. Conclusion: The process of record linkage and chart extraction was a resource-intensive process; however, our unique methodology resulted in a high linkage rate. This study suggests that it is feasible to create a retrospective trauma registry in LMICs using pragmatic and locally appropriate record linkage techniques.

Introduction: Injury accounts for 9.6% of the global mortality burden, disproportionately affecting those living in low- and middle-income countries. In an effort to improve trauma care in Rwanda, the Ministry of Health developed a prehospital service, Service d’Aide Médicale Urgente (SAMU), and established an emergency medicine training program. However, little is known about patients receiving prehospital and emergency trauma care or their outcomes. The objective was to develop a linked prehospital–hospital database to evaluate patient characteristics, mechanisms of injury, prehospital and hospital resource use, and outcomes among injured patients receiving acute care in Kigali, Rwanda. Methods: A retrospective cohort study was conducted at University Teaching Hospital – Kigali, the primary trauma centre in Rwanda. Data was included on all injured patients transported by SAMU from December 2012 to February 2015. SAMU’s prehospital database was linked to hospital records and data were collected using standardised protocols by trained abstractors. Demographic information, injury characteristics, acute care, hospital course and outcomes were included. Results: 1668 patients were transported for traumatic injury during the study period. The majority (77.7%) of patients were male. The median age was 30 years. Motor vehicle collisions accounted for 75.0% of encounters of which 61.4% involved motorcycles. 48.8% of patients sustained injuries in two or more anatomical regions. 40.1% of patients were admitted to the hospital and 78.1% required surgery. The overall mortality rate was 5.5% with nearly half of hospital deaths occurring in the emergency centre. Conclusion: A linked prehospital and hospital database provided critical epidemiological information describing trauma patients in a low-resource setting. Blunt trauma from motor vehicle collisions involving young males constituted the majority of traumatic injury. Among this cohort, hospital resource utilisation was high as was mortality. This data can help guide the implementation of interventions to improve trauma care in the Rwandan setting.