Optimizing Multi-Series Patient Scheduling Procedures for Speech-Language Pathology Treatment

不可否认，COVID-19大流行对加拿大医疗系统造成了巨大影响。面临的主要问题之一是过去几年来出现的积压和大量的等待名单;使医疗保健系统恢复到以前的可及性水平的成本将是巨大的。在儿科康复方面，在过去的几年里，等待名单已经膨胀。2019年，安大略有25,000名儿童等待接受自闭症治疗。现在有5万名儿童在等待。在加拿大医疗保健系统的几乎所有部分，需求都大大超过了现有的护理供应。鉴于供需之间的巨大差距，我们必须尽可能有效地利用现有的医疗资源。调度是卫生机构能够控制增加医疗服务的少数几个业务领域之一。KidsAbility的一项分析发现，仅将调度效率提高1%就相当于增加25万美元的临床预算。正如这一分析所表明的，即使是很小的变化也会对加拿大人获得治疗的机会产生重要影响。本提案的目标是开发一个调度优化模型的多系列预约程序有关的多优先级儿科语音语言治疗。该模型将通过与KidsAbility的合作开发。这一模式的成功发展将为目前在等待治疗名单上等待数月甚至数年的数千名患者提供可获得的医疗保健。更重要的是，这项研究将培训急需的高素质人员，以继续在合作伙伴组织和加拿大各地推进这种数据驱动的调度模型。

It is undeniable that the COVID-19 pandemic has impacted the Canadian healthcare system dramatically. One of the main concerns being faced is the backlogs and extensive waitlists that have developed over the last several years; the cost of getting the healthcare system back to its previous level of accessibility will be substantial. In pediatric rehabilitation, waitlists have ballooned over the past few years. In 2019, there were 25,000 children waiting to access autism treatment in Ontario. There are now 50,000 children waiting. In almost all parts of Canada's healthcare system, demand significantly exceeds the available supply of care. Given the wide discrepancy between supply and demand, it is imperative that we are using our existing healthcare resources as effectively as possible.Scheduling is one of the few operational areas where health institutions have control over increasing access to care. An analysis by KidsAbility, the partner organization in this study, found that increasing scheduling efficiency by just 1% is equivalent to adding $250,000 to their clinical budget. As this analysis illustrates, even small changes can have important impacts on Canadians' access to treatment. The goal of this proposal is to develop a scheduling optimization model for multi-series appointment booking procedures pertaining to multi-priority pediatric speech-language treatment. The model will be developed through a partnership with KidsAbility. Successful development of this model will result in accessible health care being provided to thousands of patients who are currently spending months or even years on waitlists for treatment. More importantly, this research would train much needed high-quality personnel to continue advancing such data-driven scheduling models in the partner organization and across Canada.