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.
Inspection copies and teaching notes are available for university faculty. To receive an inspection copy and teaching note, please email cmpshop [at] smu.edu.sg with your registered faculty email ID and a link to your contact information on the faculty directory at your university as verification. An inspection copy and teaching note will then be sent to your faculty email account.
Download Information
SMU Faculty/Staff can download the case & teaching note on iNet with your SMU login ID & Password via the following links:
· Teaching Note (SMU-23-0032TN)
For purchase of the case and supplementary materials via The Case Centre, please access the following links:
For purchase of the case and supplementary materials via Harvard Business Publishing, please access the following links:
Download Information
(Please note you are purchasing the case only.)
Looking for something?
