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

优化言语病理学治疗的多系列患者调度程序

• 批准号: 577629-2022
• 负责人: AboueeMehrizi, HosseinH
• 金额: $ 1.46万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=758127
• 关键词: Optimizing; Multi; Series; Patient; Scheduling; Optimizing; Multi; Series; Patient; Scheduling

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.

不可否认的是，19009年的大流行对加拿大医疗保健系统产生了巨大影响。面临的主要问题之一是过去几年发展的积压和广泛的候补名单。将医疗保健系统恢复到先前的可及性水平的成本将是可观的。在小儿康复中，在过去的几年中，候补名单激怒了。 2019年，有25,000名儿童在安大略省接受自闭症治疗。现在有50,000名儿童在等待。在加拿大医疗保健系统的几乎所有地区，需求大大超过了可用的护理供应。鉴于供求之间的差异很大，我们必须尽可能有效地使用现有的医疗保健资源。Scheduling是卫生机构对增加护理访问权限的少数运营领域之一。这项研究的合作伙伴组织对可儿童的分析发现，提高计划效率仅1％等于在其临床预算中增加25万美元。正如该分析所示，即使是小变化也会对加拿大人获得治疗的机会产生重要影响。该提案的目的是为与多优先性儿科语音语言处理有关的多系列预约预订程序开发计划优化模型。该模型将通过与儿童性的合作伙伴关系开发。该模型的成功开发将导致数千名目前在候补名单上花费数年甚至数年的患者提供治疗的患者。更重要的是，这项研究将培训急需的高质量人员，以继续推进合作伙伴组织和整个加拿大的数据驱动计划模型。