Introduction
Triage allows prioritisation of the most severely ill in emergency centres that face a complex and growing burden of disease. The presenting symptom is an independent variable that informs acuity and directs resource allocation. This study describes the most common presenting complaints and linked diagnoses, in total and for each category of the South African Triage Scale (SATS) at Mitchell’s Plain Emergency Centre
Methods
A retrospective, cross-sectional, chart review was used. The sample consisted of patients who presented to Mitchell’s Plain 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 on EC disposition.
Results
3434 of 4335 charts that were reviewed were suitable for inclusion. Triage acuity was 13.8% (n=475) green, 41.0% (n=1409) yellow, 32.5% (n=1116) orange and 4.3% (n=148) red. Trauma (9.7%) and abdominal pain (8.6%) were the most common presenting complaints- the majority of these were triaged as yellow cases. The most common diagnosis made was pneumonia (3.4%) – most frequently presenting as shortness of breath (14.4%). High acuity complaints were predominantly medical. Triage and clinicians report of the main complaint correlated in 74.3% of cases (r=0.7). The majority of patients and highest proportion of high priority patients presented on Mondays and Saturdays.
Conclusion
Mitchell’s Plain EC has complex caseload with a significant burden of trauma presentations related to interpersonal violence and penetrating assault. Respiratory and gastrointestinal symptoms due to infections were common across triage acuities, and cardiac or neuropsychiatric complications of chronic diseases presented frequently in high priority categories. Describing these presentations and their linked characteristic diagnoses will allow for further research into clinical flow pathways between arrival and disposition. Staffing requirements may be determined by linking these pathways to reality based time frames.
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/31680 |
Date | 23 April 2020 |
Creators | Naidoo, Antoinette Vanessa |
Contributors | Bruijns, Stevan |
Publisher | Faculty of Health Sciences, Division of Emergency Medicine |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Master Thesis, Masters, MPhil |
Format | application/pdf |
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