Abstract
Collectively, low-and middle-income countries face the grim prospect of being the
reason why global Universal Health Coverage goals might not be achieved. A range of
adverse factors including constraints in infrastructure and inadequate medical equipment,
a critical shortage of skilled workforce, as well as limited financial resources, all combine
to create a formidable set of challenges that prevent low-resourced healthcare facilities
from achieving the set objectives. An accessible, easily implementable and cost-effective
solution is required if these health systems are to be put back on track to delivering
accessible and effective healthcare to their populations.
Digital technologies may have the potential to provide the toolkit required to address
this challenge. In this study, we develop a hospital digital twin for monitoring the
status and performance of a healthcare institution in real time, based on sensor input
and Internet-of-Medical-Things devices, and we interrogate its potential role in aiding
low- and middle-income countries attain Universal Health Coverage. The digital tool
is co-designed with relevant stakeholders in order to ensure the desired attributes are
achieved. We build intelligence into the digital twin through optimisation algorithms and
heuristics that give the digital twin capability for intuitive decision-making. Business
intelligence tools are applied to enable performance measurement for the facility and to
determine effectiveness of the digital twin on operations of the healthcare facility.
Results from the study suggest that digital twin technology may be able to give output
that improves the quality of decision-making in healthcare management. The study
reveals that deeper levels of integration may be achieved across healthcare institutions’
various systems in a cost-effective manner through the use of industrial and systems
engineering tools and techniques. In both development and deployment of the tool,
emphasis is on real-time monitoring, robust data-driven optimisation and intelligent
decision-support. The digital twin proves useful in managing operations and optimising
resource utilisation within health facilities in resource-limited settings. Accordingly,
it is expected that deployment of the developed digital twin model within healthcare
institutions in low-resource settings will lead to higher service levels and better resources
management.
Keywords: Business Process Mapping, Digital Twin, Discrete Event Simulation, Hospital,
Modelling, Optimisation