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Telephonic description of sepsis among callers to an emergency dispatch centre in South Africa.
Stassen, Willem; Larsson, Eric; Wood, Courtney; Kurland, Lisa.
Affiliation
  • Stassen W; Department of Emergency Medical Care, University of Johannesburg, South Africa.
  • Larsson E; Division of Emergency Medicine, F51-62, Old Main Building Groote Schuur Hospital, University of Cape Town, Observatory, South Africa, 7925.
  • Wood C; School of Medical Sciences, Ó¦rebro University, Sweden.
  • Kurland L; Department of Emergency Medical Care, University of Johannesburg, South Africa.
Afr J Emerg Med ; 10(2): 64-67, 2020 Jun.
Article in En | MEDLINE | ID: mdl-32612910
INTRODUCTION: Sepsis is an acute, life-threatening condition caused by a dysregulated systemic response to infection. Early medical intervention such as antibiotics and fluid resuscitation can be life-saving. Diagnosis or suspicion of sepsis by an emergency call-taker could potentially improve patient outcome. Therefore, the aim was to determine the keywords used by callers to describe septic patients in South Africa when calling a national private emergency dispatch centre. METHODS: A retrospective review of prehospital patient records was completed to identify patients with sepsis in the prehospital environment. A mixed-methods design was employed in two-sequential phases. The first phase was qualitative. Thirty cases of sepsis were randomly selected, and the original call recording was extracted. These recordings were transcribed verbatim and subjected to content analysis to determine keywords of signs and symptoms telephonically. Once keywords were identified, an additional sample of sepsis cases that met inclusion and exclusion criteria were extracted and listened to. The frequency of each of the keywords was quantified. RESULTS: Eleven distinct categories were identified. The most prevalent categories that were used to describe sepsis telephonically were: gastrointestinal symptoms (40%), acute altered mental status (35%), weakness of the legs (33%) and malaise (31%). At least one of these four categories of keywords appeared in 86% of all call recordings. CONCLUSION: It was found that certain categories appeared in higher frequencies than others so that a pattern could be recognised. Utilising these categories, telephonic recognition algorithms for sepsis could be developed to aid in predicting sepsis over the phone. This would allow for dispatching of the correct level of care immediately and could subsequently have positive effects on patient outcome.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Afr J Emerg Med Year: 2020 Document type: Article Affiliation country: South Africa Country of publication: Netherlands

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Qualitative_research Language: En Journal: Afr J Emerg Med Year: 2020 Document type: Article Affiliation country: South Africa Country of publication: Netherlands