Workforce sizing and scheduling in Telemedecine

远程医疗中的劳动力规模和调度

• 批准号: 521813-2017
• 负责人: Lahrichi, Nadia
• 金额: $ 1.82万
• 依托单位: École Polytechnique de Montréal
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639426
• 关键词: Workforce; sizing; scheduling; Telemedecine

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.

远程医疗是利用电信和信息技术从远处提供医疗保健。患者和医疗专家之间的虚拟交互可以是预先录制的，也可以是实时完成的。在这种互动中，医疗保健专家会提供建议，告诉患者是否更好地治疗他/她的症状，等待看他/她的常规医生，去诊所或去急诊室。在这个项目中，我们与Dialogue合作，Dialogue是一家总部位于加拿大的初创公司，为加拿大公司提供渐进的、负担得起的医疗保健，可以通过移动的获得。Dialogue雇佣了不同类型的医疗专家。虽然员工周一至周五从早上8点工作到晚上8点，但患者可以在一天中的任何时间登录该应用程序。对话目前的规模和时间表的劳动力估计比率：聊天数护士每小时可以服务/到达系统的病人人数，助理人数/护士人数。此外，医疗保健专家每个时间段可以提供的聊天数量的估计不包括员工的资历和经验。这种规划方法往往导致无法雇用适当数量的医疗保健专家，降低服务水平（即病人通常等待很长时间才能得到服务），并过度使用护士，因为他们通常被分配加班，他们被分配给更多的病人比他们可以处理。因此，本项目的目标是为对话提供一个决策支持工具，以确定工作人员的规模和时间安排。这涉及到建模和解决方案方面的一些挑战。我们面临着复杂的工作规则、需求的变化和不确定性以及规划范围的长度。为了应对这些挑战，我们建议使用两阶段随机规划模型。该模型将包括需求的不确定性，以提供强大的人员配备和调度决策，从而以更好的方式对患者需求的变化做出反应。我们相信，实施这样一个项目将有助于减少病人的等待时间和提高满意度。这亦应可纾缓诊所和医院的挤迫情况。