The lay descriptors of out-of-hospital cardiac arrest in the Western Cape province, South Africa

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Abstract

Introduction

Out-of-Hospital Cardiac Arrest (OHCA) is a time-sensitive emergency requiring prompt identification and emergency care to reduce morbidity and mortality. The first step in managing OHCA is rapid identification by the emergency dispatch centre. Identification of these 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 in the Western Cape when contacting the provincial Emergency Medical Services' emergency call centre.

Methodology

Computer-aided dispatch 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 isiXhosa, English and Afrikaans calls were coded, categorised, and quantified.

Results

A total of 729 confirmed OHCA cases were identified, of which 38 (5.2%) Afrikaans, 24 (3.3%) isiXhosa and a random sample of 50 (6.8%) English calls were transcribed. Following content analysis, five distinct categories were identified. The most prevalent categories were descriptors related to ill health (medical history and suspected diagnosis; 35.5%), level of consciousness (unresponsive; 18.6%) and cardiac activity (pulselessness and suspected death; 17.2%).

Conclusion

The vast majority of callers within the Western Cape province of South Africa use consistent descriptors across languages when requesting an ambulance for OHCA. Future studies should focus on the development and validation of OHCA recognition algorithms, based on these findings.

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Most cited references 29

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Qualitative research explores complex phenomena encountered by clinicians, health care providers, policy makers and consumers. Although partial checklists are available, no consolidated reporting framework exists for any type of qualitative design. To develop a checklist for explicit and comprehensive reporting of qualitative studies (in depth interviews and focus groups). We performed a comprehensive search in Cochrane and Campbell Protocols, Medline, CINAHL, systematic reviews of qualitative studies, author or reviewer guidelines of major medical journals and reference lists of relevant publications for existing checklists used to assess qualitative studies. Seventy-six items from 22 checklists were compiled into a comprehensive list. All items were grouped into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. Duplicate items and those that were ambiguous, too broadly defined and impractical to assess were removed. Items most frequently included in the checklists related to sampling method, setting for data collection, method of data collection, respondent validation of findings, method of recording data, description of the derivation of themes and inclusion of supporting quotations. We grouped all items into three domains: (i) research team and reflexivity, (ii) study design and (iii) data analysis and reporting. The criteria included in COREQ, a 32-item checklist, can help researchers to report important aspects of the research team, study methods, context of the study, findings, analysis and interpretations.

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Three approaches to qualitative content analysis.

Hsiu-Fang Hsieh, Sarah Shannon (2016)

Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.