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Telephonic description of sepsis among callers to an emergency dispatch centre in South Africa
Department of Emergency Medical Care, University of Johannesburg, South Africa; Division of Emergency Medicine, F51-62, Old Main Building Groote Schuur Hospital, University of Cape Town, Observatory, South Africa.
School of Medical Sciences, Örebro University, Örebro, Sweden.
Department of Emergency Medical Care, University of Johannesburg, South Africa.
Örebro University, School of Medical Sciences.ORCID iD: 0000-0003-3290-4111
2020 (English)In: African Journal of Emergency Medicine, ISSN 2211-419X, Vol. 10, no 2, p. 64-67Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 10, no 2, p. 64-67
Keywords [en]
Emergency medical services, Emergency medical dispatch, Sepsis
National Category
Anesthesiology and Intensive Care
Identifiers
URN: urn:nbn:se:oru:diva-84515DOI: 10.1016/j.afjem.2020.01.002ISI: 000542931700005PubMedID: 32612910Scopus ID: 2-s2.0-85078895156OAI: oai:DiVA.org:oru-84515DiVA, id: diva2:1455519
Available from: 2020-07-27 Created: 2020-07-27 Last updated: 2024-01-16Bibliographically approved

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