Relevance of healthcare analytics in Singapore during COVID-19 and beyond
When COVID-19 struck in 2020, Singapore responded swiftly with containment and mitigation measures to curb community spread. Underlying the city-state’s quick public health response was an all-of-government approach characterised by decisive actions, rigorous surveillance, and prompt adaptation. Add...
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sg-smu-ink.cases_coll_all-14772024-02-21T09:27:38Z Relevance of healthcare analytics in Singapore during COVID-19 and beyond TAN, Kar Way LAM, Sean Shao Wei CHEAH, Sin Mei When COVID-19 struck in 2020, Singapore responded swiftly with containment and mitigation measures to curb community spread. Underlying the city-state’s quick public health response was an all-of-government approach characterised by decisive actions, rigorous surveillance, and prompt adaptation. Additionally, harnessing advanced healthcare technologies, such as artificial intelligence (AI) and data analytics, supported these efforts. Chatbots and automated instant messaging communications, as well as dissemination of information via traditional and social media, helped the public make sense of the uncertainties during the early days of the outbreak. As the pandemic progressed, digital contact tracing and even a robot dog were roped in to complement community surveillance measures as the country fought the war against COVID-19. More importantly, AI-enabled technologies and analytics played a vital role in disease diagnosis and prognosis as well as in supporting the research community in understanding the epidemiology of the novel coronavirus, predicting its evolution, and planning healthcare capacity. In 2023, WHO finally declared the end of COVID-19 as a global health emergency. However, the enduring effects of the pandemic persisted and continued to take a toll on the healthcare sector and on non-COVID-19 patients who had delayed medical care. Part of the burden of endemicity entailed living with the consequences of decisions made to prioritise hospital resources for COVID-19 patients, while non-urgent surgeries were either cancelled or postponed. Addressing the post-pandemic collateral damage became a pressing need. But how? Could AI, data analytics and other advanced technologies contribute to resolving this new healthcare challenge? The case aims to give students a comprehensive understanding of the pandemic's impact on healthcare systems, as well as the strategies for utilising data analytics and AI in managing post-pandemic healthcare challenges. It is recommended for undergraduate and postgraduate classes in business analytics, healthcare analytics, or an information system course 2024-02-01T08:00:00Z text https://ink.library.smu.edu.sg/cases_coll_all/478 https://cmp.smu.edu.sg/case/6016 Case Collection eng Institutional Knowledge at Singapore Management University Technology and Analytics predictive analytics big data AI and Machine Learning public health services COVID Asian Studies Databases and Information Systems Public Health |
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Technology and Analytics predictive analytics big data AI and Machine Learning public health services COVID Asian Studies Databases and Information Systems Public Health TAN, Kar Way LAM, Sean Shao Wei CHEAH, Sin Mei Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
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When COVID-19 struck in 2020, Singapore responded swiftly with containment and mitigation measures to curb community spread. Underlying the city-state’s quick public health response was an all-of-government approach characterised by decisive actions, rigorous surveillance, and prompt adaptation. Additionally, harnessing advanced healthcare technologies, such as artificial intelligence (AI) and data analytics, supported these efforts. Chatbots and automated instant messaging communications, as well as dissemination of information via traditional and social media, helped the public make sense of the uncertainties during the early days of the outbreak.
As the pandemic progressed, digital contact tracing and even a robot dog were roped in to complement community surveillance measures as the country fought the war against COVID-19. More importantly, AI-enabled technologies and analytics played a vital role in disease diagnosis and prognosis as well as in supporting the research community in understanding the epidemiology of the novel coronavirus, predicting its evolution, and planning healthcare capacity.
In 2023, WHO finally declared the end of COVID-19 as a global health emergency. However, the enduring effects of the pandemic persisted and continued to take a toll on the healthcare sector and on non-COVID-19 patients who had delayed medical care. Part of the burden of endemicity entailed living with the consequences of decisions made to prioritise hospital resources for COVID-19 patients, while non-urgent surgeries were either cancelled or postponed. Addressing the post-pandemic collateral damage became a pressing need. But how? Could AI, data analytics and other advanced technologies contribute to resolving this new healthcare challenge?
The case aims to give students a comprehensive understanding of the pandemic's impact on healthcare systems, as well as the strategies for utilising data analytics and AI in managing post-pandemic healthcare challenges. It is recommended for undergraduate and postgraduate classes in business analytics, healthcare analytics, or an information system course |
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text |
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TAN, Kar Way LAM, Sean Shao Wei CHEAH, Sin Mei |
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TAN, Kar Way LAM, Sean Shao Wei CHEAH, Sin Mei |
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TAN, Kar Way |
title |
Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
title_short |
Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
title_full |
Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
title_fullStr |
Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
title_full_unstemmed |
Relevance of healthcare analytics in Singapore during COVID-19 and beyond |
title_sort |
relevance of healthcare analytics in singapore during covid-19 and beyond |
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Institutional Knowledge at Singapore Management University |
publishDate |
2024 |
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https://ink.library.smu.edu.sg/cases_coll_all/478 https://cmp.smu.edu.sg/case/6016 |
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