Abstract:
This thesis adds to the plethora of knowledge on interventions/mechanisms that can be employed to overcome the challenges rocking the healthcare systems in sub-Saharan Africa. Extended waiting time due to overcrowding of patients in hospital waiting rooms, a consequence of few and sparsely located health facilities is negatively impacting provision of quality healthcare services and optimal usage of resources in healthcare facilities. The outpatient and surgical departments are two of the sections where patients constantly experience extended waiting times. This research demonstrates how existing mathematical tools such as integer linear programming, queuing theory and other technologies, such as machine learning and the internet of things can be utilized to uncover and address bottlenecks in the delivery and access to healthcare, with special focus on patient flow process. Through a modelling approach we investigate how sharing of patient load information among health facilities can help to reduce patient waiting time. We propose re-assigning excess patient loads to nearby facilities that have minimal load as a way to control overcrowding and reduce queue abandonment. An Internet of things integrated smart bus system is proposed to aid the movement of patients to less crowded health facilities.
The relationship between patient flow and staff scheduling is investigated using queuing theory. We investigate how the various parameters that govern patient movement in the outpatient can be optimized to improve quality of healthcare delivery and access. Furthermore, using an integer linear programming approach, we study the problem of optimal assignment of operating rooms, under conditions of limited available operating facilities and specialized equipment. This research shows that quality healthcare service defined by low access time and reduced queue abandonment is possible in sub-Saharan Africa region
