An analysis of the Afrikaans telephonic descriptors of cardiac arrest in a Western Cape Emergency Control centre

Master Thesis


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Introduction: Out of Hospital Cardiac Arrest (OHCA) is a time-sensitive emergency which requires prompt identification and emergency care in order to reduce morbidity and mortality. The first step in recognising OHCA is rapid identification by the emergency dispatch centre. Identification of such patients remains challenging in South Africa due to multiple languages and widely differing levels of education. This study aimed to identify the key descriptors (words and phrases) of OHCA used by callers speaking Afrikaans when contacting the emergency dispatch centre of the Western Cape Provincial Emergency Medical Services (WC-EMS). Methodology: Computer-aided dispatch (CAD) data with a corresponding “patient unresponsive” incident type were drawn for a 12 month period (January – December 2018). Corresponding patient care records were extracted to verify OHCA. The original voice recordings between the caller and emergency call taker at the time of the emergency were extracted and transcribed verbatim. Transcriptions were subjected to inductive, qualitative content analysis to the manifest level. Descriptors of OHCA in Afrikaans calls were coded, categorised and quantified. Results: A total of 729 confirmed OHCA cases were identified, of which 36 (5%) were in Afrikaans and eligible for analysis. Following content analysis, 83 distinct codes in six categories were identified. The most prevalent categories were descriptors related to Respiratory Effort (apnoea and difficulty in breathing; 30.1%) (30.1%), Clinical Features (related to the eyes, mouth and body temperature; 20.4%) and Cardiac Activity (pulselessness; 16.8%). Conclusion Afrikaans Callers within the Western Cape province of South Africa use consistent descriptors when requesting and ambulance for OHCA. Future studies should focus on describing descriptors for other languages commonly spoken in the province, and to develop and validate telephonic OHCA recognition algorithms.