Describing the most common presenting complaints, their priority and corresponding diagnoses at Khayelitsha Emergency Centre

Master Thesis


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Introduction Emergency centres have to be equipped to provide high-quality care to a number of undifferentiated patients with varying acuity of illness. This study aimed to identify the most common presenting complaints and corresponding linked diagnoses, in total and for each category of the South African Triage Scale (SATS) at Khayelitsha Emergency Centre (EC). Methods A retrospective, cross-sectional, chart review was used. The sample consisted of patients who presented to Khayelitsha EC in January and June 2015. Charts were reviewed via the Electronic Content Management system. Data were collected on demographic profile, triage priority, presenting symptoms at triage, and ICD-10 diagnosis. Results 4006 of 4928 charts that were reviewed were suitable for inclusion. Triage acuity was 28.0% (n=1123) green, 34.2% (n=1372) yellow, 25.7% (n=1030) orange and 3.5% (n=141) red. The most common presenting complaints were trauma (10.3%) and pain (10.1%); the majority of these patients presented in the yellow and green triage categories. The most common diagnosis made in the EC was pneumonia (7.0%) - most frequently presenting as shortness of breath (8.7%) and cough (5.6%). Medical conditions presented with a higher acuity at triage. Presenting complaints documented at triage and those reported by clinicians correlated an acceptable 70.1% of cases (r=0.71). Diarrhoea and vomiting were the predominant symptoms in summer whereas shortness of breath and cough were more frequent in winter. Triage acuity was similar for both months. Conclusion Individual symptoms presented with varying priority and resulted in a variety of eventual diagnoses which showed differences across categories. Presenting complaints provide granularity to otherwise undifferentiated triage priorities. Future research should focus on time-in-motion work to determine the mean clinical care time each of these complaints require. This should allow a calculation of the mean clinical care time for each triage priority. In turn this can be turned into a calculation for optimal staffing.