Can AI Help Improve Acute Care Operations? Investigating the Impact of Virtual Triage Technology Adoption

To choose the appropriate resources for their healthcare needs (primary care (GP) or emergency department (ED)), patients seeking acute care must self-triage based on their own assessments of symptoms and severity. However, as patients typically lack sufficient medical knowledge, self-triage decisions can often be inaccurate. In response, healthcare and technology companies have been developing and deploying AI-powered virtual triage tools designed to help patients make better self-triage decisions. To date, however, the operational implications of such tools have not been assessed. This paper therefore develops a queueing game model to investigate the impact of virtual triage in the acute care setting and potential policies to maximize its efficacy. We find that, due to its decentralized nature, when virtual triage excessively recommends emergency (primary) care, it counterintuitively brings about a decrease in ED (GP) visits. Another important finding is that in an unregulated environment, the adoption of informative virtual triage can worsen system performance, even when the virtual triage recommendation is reasonably accurate. Building on these insights, we identify two sources of inefficiency and propose associated policy actions that can help unlock the potential operational benefits of virtual triage.