Investigating Discrete Event Simulation Method to Assess the Effectiveness of Wearable Health Monitoring Devices

Abstract

The current primary care units of the US healthcare system are strained by supply-demand deficiency. Last 12 years have seen a decline in number of US medical students opting for primary care after their medical education. Research studies have recommended solutions targeting, primary care payment reform, investment in primary care infrastructure and organization, and attracting more US medical students to primary care. Such reforms demand expensive implementation plans and might take years to yield benefits. Meanwhile, the generation of baby boomers and the healthcare reform under current US administration (insuring additional 33-43 million patients) may stress out the primary care providers in near future. In this paper, we investigate the usefulness of wearable health monitoring devices, to alleviate primary care patient load. To conduct our study, we adopted the discrete event simulation method to simulate the proposed model and analyze the behaviour of the same in terms of performance measures. We simulated three scenarios with different vital sign measurement time and physician consultation time. In addition we varied the percentage of patient population adopting the wearable device health monitoring (WHMS) program. In all the three scenarios, the WHMS system yielded beneficial results in absorbing more patients and reducing patient denials than the current primary care system irrespective of adoption percentages. However the average patient wait times were sensitive to the adoption percentages. On the whole the simulation results indicated that wearable health monitoring devices could act as a potential solution in reducing the patient load across the primary care system.