Service Operations Management in the Mental Health Care Sector

精神卫生保健领域的服务运营管理

• 批准号: RGPIN-2021-03499
• 负责人: Rastpour, Amir
• 金额: $ 1.89万
• 依托单位: University of Ontario Institute of Technology
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 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=746432
• 关键词: Service; Operations; Management; Mental; Health

This research will investigate statistical and mathematical models to develop insights into planning and management of waiting lists in general, and mental health care systems in particular. Common operational aspects of mental health services include: 1) a patient (customer) is "assigned" to a clinician (server) to receive treatment services during a random number of visits; 2) psychiatric patients have high no-show rates in their treatment sessions; and 3) psychiatric treatment plans are highly variable in terms of duration and the distribution of their outcomes. Informed by these common aspects, I will investigate methods to forecast demand and waiting time for mental health care services and to shed light on factors that drive exceptionally long waiting times for psychiatric patients. Using the mathematical models, the impacts of operational decisions, for example, capacity cap on the number of patients assigned to a clinicians, and aspects by which patients should be clustered to reduce the variability in waiting times, will be investigated. I will validate my mathematical models using empirical data. At an academic level, this research program will contribute to the fields of operations research, operations management in the health care and service sectors, and psychiatric care planning and management. It will address important issues regarding the modeling of queueing systems with returning heterogeneous customers that are assigned to heterogeneous servers to receive service during a random number of interactions. At a practical level, this research will aid decision makers in the field of mental health care with their planning methods. The need for improvements in management of waiting lists has become even more evident in the context of increased demand for psychiatric care during the current pandemic, due to high levels of stress in family and work settings and extended loneliness. These improvements will be essential for the post-Covid-19 era. Psychiatric patients in particular, and customers receiving service in general, in Canada and elsewhere, will benefit from planning that matches realities more effectively and efficiently.

这项研究将调查统计和数学模型，以发展对一般等候名单的规划和管理，特别是精神卫生保健系统的见解。心理健康服务的常见操作方面包括：1）患者（客户）被“分配”给临床医生（服务器），在随机访问期间接受治疗服务; 2）精神病患者在治疗期间有很高的未出现率; 3）精神病治疗计划在持续时间和结果分布方面存在很大差异。根据这些共同的方面，我将研究预测精神卫生保健服务需求和等待时间的方法，并阐明导致精神病患者等待时间过长的因素。使用的数学模型，业务决策的影响，例如，分配给临床医生的患者数量的能力上限，以及患者应聚类，以减少等待时间的变化方面，将进行调查。我将用经验数据验证我的数学模型。 在学术层面上，该研究计划将有助于运筹学领域，在医疗保健和服务部门的运营管理，以及精神病护理规划和管理。它将解决重要的问题，关于返回异构客户分配到异构服务器接收服务在一个随机数量的交互过程中的建模的嵌入式系统。 在实践层面上，这项研究将有助于决策者在精神卫生保健领域与他们的规划方法。在目前的大流行病期间，由于家庭和工作环境的高度压力以及长期的孤独感，对精神病护理的需求增加，因此，改善等候名单管理的必要性变得更加明显。这些改进对于后COVID-19时代至关重要。在加拿大和其他地方，特别是精神病患者和一般接受服务的客户将受益于更有效和更高效地符合现实的规划。