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Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa
In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of providers is to task-share: roles traditionally filled by clinicians are shared with lay workers who have received task-specific training. Separately...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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The African Field Epidemiology Network
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325458/ https://www.ncbi.nlm.nih.gov/pubmed/34381531 http://dx.doi.org/10.11604/pamj.2021.38.387.20557 |
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author | Lamanna, Camillo |
author_facet | Lamanna, Camillo |
author_sort | Lamanna, Camillo |
collection | PubMed |
description | In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of providers is to task-share: roles traditionally filled by clinicians are shared with lay workers who have received task-specific training. Separately, there has been much recent interest in the possible implications of artificial intelligence (AI) on healthcare. This paper proposes that, by combining the task-sharing model with AI, it is possible to design an Emergency Unit (EU) that shares the tasks currently undertaken by physicians and nurses with lay providers, with the activities of lay providers guided and supervised by AI. The proposed model would free emergency care clinicians to focus on higher-acuity and complex cases while AI-supervised routine care is provided by lay providers. The paper outlines the model for such an implementation and considers the potential benefits to patient care, as well as considering the risks, costs, effect on providers, and ethical questions. The paper concludes that AI and healthcare workers can operate as a team, with significant potential to augment human resources for health in sub-Saharan Africa. |
format | Online Article Text |
id | pubmed-8325458 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The African Field Epidemiology Network |
record_format | MEDLINE/PubMed |
spelling | pubmed-83254582021-08-10 Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa Lamanna, Camillo Pan Afr Med J Essay In sub-Saharan Africa, there is a significant unmet need for emergency care, with a shortage of trained providers. One model to increase the number of providers is to task-share: roles traditionally filled by clinicians are shared with lay workers who have received task-specific training. Separately, there has been much recent interest in the possible implications of artificial intelligence (AI) on healthcare. This paper proposes that, by combining the task-sharing model with AI, it is possible to design an Emergency Unit (EU) that shares the tasks currently undertaken by physicians and nurses with lay providers, with the activities of lay providers guided and supervised by AI. The proposed model would free emergency care clinicians to focus on higher-acuity and complex cases while AI-supervised routine care is provided by lay providers. The paper outlines the model for such an implementation and considers the potential benefits to patient care, as well as considering the risks, costs, effect on providers, and ethical questions. The paper concludes that AI and healthcare workers can operate as a team, with significant potential to augment human resources for health in sub-Saharan Africa. The African Field Epidemiology Network 2021-04-20 /pmc/articles/PMC8325458/ /pubmed/34381531 http://dx.doi.org/10.11604/pamj.2021.38.387.20557 Text en Copyright: Camillo Lamanna et al. https://creativecommons.org/licenses/by/4.0/The Pan African Medical Journal (ISSN: 1937-8688). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Essay Lamanna, Camillo Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title | Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title_full | Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title_fullStr | Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title_full_unstemmed | Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title_short | Task-sharing with artificial intelligence: a design hypothesis for an Emergency Unit in sub-Saharan Africa |
title_sort | task-sharing with artificial intelligence: a design hypothesis for an emergency unit in sub-saharan africa |
topic | Essay |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325458/ https://www.ncbi.nlm.nih.gov/pubmed/34381531 http://dx.doi.org/10.11604/pamj.2021.38.387.20557 |
work_keys_str_mv | AT lamannacamillo tasksharingwithartificialintelligenceadesignhypothesisforanemergencyunitinsubsaharanafrica |