An analysis of the descriptors of acute myocardial infarction used by South Africans when calling for an ambulance from a private emergency call centre

INTRODUCTION: Acute myocardial infarction (AMI) is a time sensitive emergency. In resource limited settings, prompt identification and management of patients experiencing AMI in the pre-hospital setting may minimise the negative consequences associated with overburdened emergency medical and hospital services. Expedited care thus, in part, relies on the dispatch of appropriate pre-hospital medical providers by emergency medical dispatchers. Identification of these patients in call centres is challenging due to a highly diverse South African society, with multiple languages, cultures, and levels of education. The aim of this study was therefore, to describe the terms used by members of the South African public when calling for an ambulance for patients suffering an AMI. METHODS: In this qualitative study, we performed content analysis to identify keywords and phrases that callers used to describe patients who were experiencing an advanced life support (ALS) paramedic-diagnosed AMI. Using the unique case reference number of randomly selected AMI cases, original voice recordings between the caller and emergency medical dispatcher at the time of the emergency were extracted and transcribed verbatim. Descriptors of AMI were identified, coded and categorised using content analysis, and quantified. RESULTS: Of the 50 randomly selected calls analysed, 5 were not conducted in English. The descriptors used by callers were found to fall into three categories; Pain: Thorax, No pain: Thorax and Ill- health. The code that occurred most often was no pain, heart related (n = 16; 23.2%), followed by the code describing pain in the chest (n = 15; 21.7%). CONCLUSION: South African callers use a consistent set of descriptors when requesting an ambulance for a patient experiencing an AMI. The most common of these are non-pain descriptors related to the heart. These descriptors may ultimately be used in developing validated algorithms to assist dispatch decisions. In this way, we hope to expedite the correct level of care to these time- critical patients and prevent the unnecessary dispatch of limitedly available ALS paramedics to inappropriate cases.