Workforce sizing and scheduling in Telemedecine

点击翻译按钮获取中文摘要

Telemedicine is the use of telecommunication and information technology to provide healthcare from adistance. The virtual interaction between the patient and the healthcare expert can be either pre-recorded ordone in real-time. In this interaction, a healthcare expert offers advice on whether it is better for the patient totreat his/her symptoms, wait to see his/her regular doctor, go to a clinic, or go to an emergency room. In thisproject, we collaborate with Dialogue, a Montreal-based start-up that provides progressive and affordablehealthcare, accessible on mobile, for Canadian companies. Dialogue employs different types of healthcareexperts. Although employees work from 8am to 8pm from Monday to Friday, patients can log into the app atany time of the day. Dialogue currently dimensions and schedules the workforce by estimating ratios: numberof chats a nurse can serve per hour/number of patients arriving to the system, number of assistants/number ofnurses. Moreover, the estimate of the number of chats that a healthcare expert can serve per time period doesnot include the level of seniority and the experience of the employee. This planning method often results in theinability to hire an appropriate number of healthcare experts, in a decrease in the service level (i.e. patientsusually wait a long time before being served), and in the over-utilization of nurses as they are usually allocatedto overtime and they are assigned to more patients than they can handle. The objective of this project istherefore to provide Dialogue with a decision-support tool to staff dimensioning and scheduling. This involvesseveral challenges from the modeling and solution perspectives. We face complex work regulations, demandvariability and uncertainty and the length of the planning horizon. In order to address these challenges, wepropose to use a two-stage stochastic programming model. This model will include uncertainty in demands toprovide robust staffing and scheduling decisions that will react, in a better way, to changes in patients'requirements. We believe that the implementation of such a project will contribute to reducing patients' waittime and improving satisfaction. This should also relieve congestion in clinics and hospitals.