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Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa
Background – Clinical deterioration is a worldwide concern and is associated with increased mortality, hospital stay, and incidence of adverse events. CD also occurs in the pre-hospital setting though few studies describe its occurrence as well as the factors it is associated with, and no evidence c...
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| Format: | Thesis |
| Language: | English English |
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Division of Emergency Medicine
2025
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| _version_ | 1867613279934742528 |
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| access_status_str | Open Access |
| author | Jooste, Wayne |
| author2 | Stassen, Willem |
| author_browse | Jooste, Wayne Stassen, Willem |
| author_facet | Stassen, Willem Jooste, Wayne |
| author_sort | Jooste, Wayne |
| collection | Thesis |
| description | Background – Clinical deterioration is a worldwide concern and is associated with increased mortality, hospital stay, and incidence of adverse events. CD also occurs in the pre-hospital setting though few studies describe its occurrence as well as the factors it is associated with, and no evidence currently exists that describes its occurrence within the South African context. CD is deemed to be preventable, and although several tools exist to detect early CD, no published evidence was found about validated pre-hospital CD prediction tools. Aim - This study aimed to perform a data-archive analysis with the purpose of describing the occurrence of clinical deterioration during ambulance transportation in adult patients within the South African context. Through classification and regression analysis it also sought to determine the variables associated with the occurrence of CD, with the goal of developing a pre-hospital clinical deterioration prediction tool. Methods – A data archive analysis was done on physiological parameters and other factors recorded by pre-hospital practitioners of patients during ambulance transportation. A NEWS and MEES score were calculated on physiological parameter trends to observe for the occurrence of CD on 89193 patients. Data from the analysis was subsequently used for the creation of a pre-hospital clinical deterioration prediction tool through binomial regression and Chi-square Automatic Interaction Detector classification. Results – A CD deterioration rate of 15.7% was observed in this sample, with numerous corelating variables. A Chi-Squared Automatic Interaction Detection as well as binomial regression analysis was performed on significant logistic and clinical variables revealing significant predictive ability. Medical oxygen administration (OR 3.38, 95% CI 3.22-3.55, P-value 0.000) and high clinical risk (OR 2.42, 95% CI 2.26- 2.59, p-value 0.000) emerged as the most significant predictors for CD amongst others, while senior crew qualification ECP (OR 0.7, 95% CI 0.64-0.77, p-value 0.000) emerged as 30% protective against CD compared to the reference category BAA. These results indicate that there is a significant increase in probability of CD should a patient be of high acuity and receive medical oxygen for example, as well as a decrease in probability of CD should the patient be treated by higher qualified providers. The regression analysis was followed by a pre-hospital clinical deterioration prediction tool development, where these variables amongst others were included into a composite score. The score subtracted more points as the qualification of the treating provider increased or if it was a primary case. The score added points should it have been a trauma case, medical oxygen was administered, inotropic support was provided, analgesia or sedation was provided, or of the patients had increase in level of acuity. Each variable had its own score value depending on its OR for CD, ultimately revealing a percentage for probability of CD. Conclusion The aim of the study was to develop a pre-hospital clinical deterioration prediction tool through retrospective data-archive analysis, and regression. Multiple logistic and clinical variables were identified that are significant predictors for CD in the pre hospital setting and were ultimately included into a composite score. This tool can practically be implemented into the call centre of an emergency medical service during information gathering for inter-facility transfers, or in an electronic patient report form by a pre-hospital provider. Despite its limitations, we believe this tool could lead to early identification of pre-hospital CD and early implementation of CD mitigation strategies, ultimately improving patient safety and outcomes. We recommend a validation study to be performed in the future. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/40997 |
| institution | University of Cape Town (South Africa) |
| language | English eng |
| last_indexed | 2026-06-10T12:33:37.862Z |
| 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 | Division of Emergency Medicine |
| publisherStr | Division of Emergency Medicine |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/40997 Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa Jooste, Wayne Stassen, Willem van der Berg, Johannes Hendrik Medicine Background – Clinical deterioration is a worldwide concern and is associated with increased mortality, hospital stay, and incidence of adverse events. CD also occurs in the pre-hospital setting though few studies describe its occurrence as well as the factors it is associated with, and no evidence currently exists that describes its occurrence within the South African context. CD is deemed to be preventable, and although several tools exist to detect early CD, no published evidence was found about validated pre-hospital CD prediction tools. Aim - This study aimed to perform a data-archive analysis with the purpose of describing the occurrence of clinical deterioration during ambulance transportation in adult patients within the South African context. Through classification and regression analysis it also sought to determine the variables associated with the occurrence of CD, with the goal of developing a pre-hospital clinical deterioration prediction tool. Methods – A data archive analysis was done on physiological parameters and other factors recorded by pre-hospital practitioners of patients during ambulance transportation. A NEWS and MEES score were calculated on physiological parameter trends to observe for the occurrence of CD on 89193 patients. Data from the analysis was subsequently used for the creation of a pre-hospital clinical deterioration prediction tool through binomial regression and Chi-square Automatic Interaction Detector classification. Results – A CD deterioration rate of 15.7% was observed in this sample, with numerous corelating variables. A Chi-Squared Automatic Interaction Detection as well as binomial regression analysis was performed on significant logistic and clinical variables revealing significant predictive ability. Medical oxygen administration (OR 3.38, 95% CI 3.22-3.55, P-value 0.000) and high clinical risk (OR 2.42, 95% CI 2.26- 2.59, p-value 0.000) emerged as the most significant predictors for CD amongst others, while senior crew qualification ECP (OR 0.7, 95% CI 0.64-0.77, p-value 0.000) emerged as 30% protective against CD compared to the reference category BAA. These results indicate that there is a significant increase in probability of CD should a patient be of high acuity and receive medical oxygen for example, as well as a decrease in probability of CD should the patient be treated by higher qualified providers. The regression analysis was followed by a pre-hospital clinical deterioration prediction tool development, where these variables amongst others were included into a composite score. The score subtracted more points as the qualification of the treating provider increased or if it was a primary case. The score added points should it have been a trauma case, medical oxygen was administered, inotropic support was provided, analgesia or sedation was provided, or of the patients had increase in level of acuity. Each variable had its own score value depending on its OR for CD, ultimately revealing a percentage for probability of CD. Conclusion The aim of the study was to develop a pre-hospital clinical deterioration prediction tool through retrospective data-archive analysis, and regression. Multiple logistic and clinical variables were identified that are significant predictors for CD in the pre hospital setting and were ultimately included into a composite score. This tool can practically be implemented into the call centre of an emergency medical service during information gathering for inter-facility transfers, or in an electronic patient report form by a pre-hospital provider. Despite its limitations, we believe this tool could lead to early identification of pre-hospital CD and early implementation of CD mitigation strategies, ultimately improving patient safety and outcomes. We recommend a validation study to be performed in the future. 2025-02-21T09:39:27Z 2025-02-21T09:39:27Z 2024 2025-02-21T09:37:36Z Thesis / Dissertation Masters MSc http://hdl.handle.net/11427/40997 en eng application/pdf Division of Emergency Medicine Faculty of Health Sciences University of Cape Town |
| spellingShingle | Medicine Jooste, Wayne Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| thesis_degree_str | Master's |
| title | Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| title_full | Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| title_fullStr | Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| title_full_unstemmed | Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| title_short | Development of a clinical deterioration prediction tool for adult patients during ambulance transportation in South Africa |
| title_sort | development of a clinical deterioration prediction tool for adult patients during ambulance transportation in south africa |
| topic | Medicine |
| url | http://hdl.handle.net/11427/40997 |
| work_keys_str_mv | AT joostewayne developmentofaclinicaldeteriorationpredictiontoolforadultpatientsduringambulancetransportationinsouthafrica |