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An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality
Inefficient EMS systems can lead to delays in accessing urgent medical care and increased mortality for critically ill or injured patients. In the Nelson Mandela Bay district of South Africa's Eastern Cape province, the public EMS system struggles to meet its own response time targets. In addition t...
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| Format: | Thesis |
| Language: | English |
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Department of Statistical Sciences
2025
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| _version_ | 1867613332581646336 |
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| access_status_str | Open Access |
| author | Cope, Sky |
| author2 | Silal, Sheetal |
| author_browse | Cope, Sky Silal, Sheetal |
| author_facet | Silal, Sheetal Cope, Sky |
| author_sort | Cope, Sky |
| collection | Thesis |
| description | Inefficient EMS systems can lead to delays in accessing urgent medical care and increased mortality for critically ill or injured patients. In the Nelson Mandela Bay district of South Africa's Eastern Cape province, the public EMS system struggles to meet its own response time targets. In addition to long response times, staff and vehicles are not always allocated efficiently, as highly-skilled personnel and specialised vehicles are frequently used for responding to low priority or planned patient transport calls. This decreases the quality of medical care provided to the most critically ill patients. The aim of this research is to improve patient outcomes in Nelson Mandela Bay's under resourced public EMS system, which serves the majority of the local population, including those who are unable to afford private EMS. It therefore has the potential to improve access to EMS for the most underprivileged communities, and enhance healthcare equity in the re gion. To achieve this, the research provides decision-makers in the Eastern Cape Department of Health (ECDoH) with a set of evidence-based recommendations for reducing response times, and improving the efficiency of staff and vehicle allocations. These recommendations are sen sitive to the resource-limited nature of the setting, and prioritises interventions that do not require additional staff or vehicles. The EMS system was modelled using an agent-based simulation model, which enables multiple sources of variation in the system to be explicitly accounted for, and nuanced scenarios to be investigated. The model was built and validated using anonymised EMS call data, a smaller dataset of precise response times, and travel time estimates from Google Maps. A key finding of this research is that the median response time of Priority 1 calls can be reduced to below the 30 minute target by implementing changes to dispatching, rerouting and prioritisation behaviour alone, and without increasing resources. These improvements come at the expense of substantial increases in median response times for lower priority calls, but these increases can be counteracted by moderately scaling up the number of staff employed. Improving the accuracy of dispatchers in triaging calls was identified as a particularly effective method of reducing response times, without considerable increases to response times for other call types. A number of policy recommendations were formulated based on these results. These will be presented to management in the Eastern Cape Department of Health, aiming to guide policy interventions for Nelson Mandela Bay's EMS system. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/40846 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:34:27.383Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/40846 An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality Cope, Sky Silal, Sheetal Emergency Medical Services agent-based modelling simulation modelling operations research Inefficient EMS systems can lead to delays in accessing urgent medical care and increased mortality for critically ill or injured patients. In the Nelson Mandela Bay district of South Africa's Eastern Cape province, the public EMS system struggles to meet its own response time targets. In addition to long response times, staff and vehicles are not always allocated efficiently, as highly-skilled personnel and specialised vehicles are frequently used for responding to low priority or planned patient transport calls. This decreases the quality of medical care provided to the most critically ill patients. The aim of this research is to improve patient outcomes in Nelson Mandela Bay's under resourced public EMS system, which serves the majority of the local population, including those who are unable to afford private EMS. It therefore has the potential to improve access to EMS for the most underprivileged communities, and enhance healthcare equity in the re gion. To achieve this, the research provides decision-makers in the Eastern Cape Department of Health (ECDoH) with a set of evidence-based recommendations for reducing response times, and improving the efficiency of staff and vehicle allocations. These recommendations are sen sitive to the resource-limited nature of the setting, and prioritises interventions that do not require additional staff or vehicles. The EMS system was modelled using an agent-based simulation model, which enables multiple sources of variation in the system to be explicitly accounted for, and nuanced scenarios to be investigated. The model was built and validated using anonymised EMS call data, a smaller dataset of precise response times, and travel time estimates from Google Maps. A key finding of this research is that the median response time of Priority 1 calls can be reduced to below the 30 minute target by implementing changes to dispatching, rerouting and prioritisation behaviour alone, and without increasing resources. These improvements come at the expense of substantial increases in median response times for lower priority calls, but these increases can be counteracted by moderately scaling up the number of staff employed. Improving the accuracy of dispatchers in triaging calls was identified as a particularly effective method of reducing response times, without considerable increases to response times for other call types. A number of policy recommendations were formulated based on these results. These will be presented to management in the Eastern Cape Department of Health, aiming to guide policy interventions for Nelson Mandela Bay's EMS system. 2025-01-30T14:00:26Z 2025-01-30T14:00:26Z 2024 2025-01-30T12:52:35Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/40846 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Emergency Medical Services agent-based modelling simulation modelling operations research Cope, Sky An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| thesis_degree_str | Master's |
| title | An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| title_full | An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| title_fullStr | An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| title_full_unstemmed | An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| title_short | An agent-based model of the emergency medical services system in Nelson Mandela Bay municipality |
| title_sort | agent based model of the emergency medical services system in nelson mandela bay municipality |
| topic | Emergency Medical Services agent-based modelling simulation modelling operations research |
| url | http://hdl.handle.net/11427/40846 |
| work_keys_str_mv | AT copesky anagentbasedmodeloftheemergencymedicalservicessysteminnelsonmandelabaymunicipality AT copesky agentbasedmodeloftheemergencymedicalservicessysteminnelsonmandelabaymunicipality |