The Economic Burden of Hip Fractures among Elderly Patients in Ireland: A Combined Perspective of System Dynamics and Machine Learning

摘要

Population ageing is increasing in a rapid pace worldwide, and especially within developed countries. Extraordinary economic challenges are therefore in prospect with regard to healthcare delivery. In this respect, healthcare executives increasingly need tools that can accurately assess the impacts of the foreseen demographic transition. The paper investigates the economic implications in relation to the incidence of hip fractures among elderly patients in Ireland. A combined approach is adopted that utilises System Dynamics (SD) and machine learning. At the macro-scale level, an SD model is used to produce projections of elderly populations who are susceptible to sustain hip fractures. In addition, the SD model is disaggregated to properly depict the demographic structure of the healthcare system in Ireland. At the micro-scale level, machine learning models are used to make careful predictions on the inpatient length of stay and discharge destinations for simulation-generated patients. The study is claimed to deliver useful insights regarding the potential economic burden on the Irish healthcare system implied by elderly hip-fracture patients. More broadly, we attempt to provide a multi-methodology perspective that combines simulation modeling and machine learning towards increasing the confidence and credibility of the simulation model predictions for decision making purposes.