A paradigm shift in appointment Scheduling: Introducing a decentralized integrated Online booking system

【Author】 Seyedi, Pardis; Eshghi, Kourosh; Carter, Michael W.

【Source】EXPERT SYSTEMS WITH APPLICATIONS

【影响因子】8.665

【Abstract】Long wait times, coordination, and integration are persistent issues in many health systems, hindering effective management of client waitlists and delaying treatment. The traditional approach of independent scheduling at each center does not allow for a coordinated response to demand fluctuations. An Integrated Online Booking system (IOB) for outpatient services is designed in this study, presenting the first central intake-based appointment system integrated with an optimization approach and a novel decentralized and distributed appointment system. This system considers the independence of centers while better responding to demand and improving overall system performance. The optimization component of the IOB system is expanded in this paper to include multiple sites, patient preferences, priorities, and wait time targets. It becomes a large-scale problem as all requests from a geographical region are combined into one stream. A decomposable algorithm based on the Alternating Direction Method of Multipliers (ADMM) is used for this system. The study employs real large-scale MRI data from all hospitals in Ontario, Canada, to demonstrate the effectiveness of the IOB system, providing insights into its potential impact on healthcare operations. The results indicate that the IOB system can outperform common appointment scheduling approaches in terms of reducing patient wait times, balancing utilization rates, improving referral patterns, and enhancing system efficiency. The proposed IOB system can bring added value to the market by speeding up diagnosis and treatment processes while improving the efficiency of healthcare systems. This platform can be considered as Software as a Service (SaaS), providing a scalable and accessible solution for managing appointments across various sectors, and leveraging blockchain technology to ensure secure, transparent, and tamper-proof appointment records. This study provides insights for decision-makers, highlighting the importance of effective scheduling in managing client waitlists during treatment in the healthcare sector, such as elective surgery, home healthcare, physical and mental therapies, and other service industries like education, public consultations, and government services. The IOB system can be integrated with Artificial Intelligence (AI)-based tools and machine learning methods and combined with other service software to optimize appointment scheduling and improve system performance.

【Keywords】Operations research; Appointment scheduling; Decentralized algorithm; Healthcare management; Service Operations Management

【发表时间】2024 DEC 10

【收录时间】2024-08-30

【文献类型】案例研究

【主题类别】

区块链应用-实体经济-医疗领域