School of Management and Economics, Beijing Institute of Technology, Beijing, China.
Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, USA.
Technol Health Care. 2021;29(5):939-953. doi: 10.3233/THC-202623.
Telemedicine is playing an increasingly more important role in disease diagnosis and treatment. The market of telemedicine application is continuously promoted, thus bringing some issues on telemedicine operations management.
We aimed to compare the teleconsultation scheduling performance of newly designed proactive strategy and existing static strategy and explore the decision-making under different conditions.
We developed a discrete-event simulation model based on practical investigation to describe the existing static scheduling strategy of teleconsultation. The static strategy model was verified by comparing it with the historical data. Then a new proactive strategy was proposed, whose average waiting time, variance of waiting time and completed numbers were compared with the static strategy.
The analysis indicated that the proactive strategy performed better than static under the current resource allocation. Furthermore, we explored the impact on the system of both strategies varying arrival rate and experts' shift time.
Under different shift times and arrival rates, the managers of telemedicine center should select different strategy. The experts' shift time had a significant impact on all system performance indicators. Therefore, if managers wanted to improve the system performance to a greater extent, they needed to reduce the shift time as much as possible.
远程医疗在疾病诊断和治疗中发挥着越来越重要的作用。远程医疗应用市场不断推进，由此带来一些远程医疗运营管理方面的问题。
本研究旨在比较新设计的主动策略和现有静态策略的远程咨询调度性能，并探讨不同条件下的决策。
我们基于实际调查开发了一个离散事件模拟模型来描述现有的远程咨询静态调度策略。通过将静态策略模型与历史数据进行比较，验证了其有效性。然后提出了一种新的主动策略，比较了其平均等待时间、等待时间方差和完成数量与静态策略的差异。
分析表明，在当前资源配置下，主动策略的性能优于静态策略。此外，我们还探讨了两种策略在不同到达率和专家轮班时间下对系统的影响。
在不同的轮班时间和到达率下，远程医疗中心的管理者应选择不同的策略。专家轮班时间对所有系统性能指标都有重大影响。因此，如果管理者希望在更大程度上提高系统性能，就需要尽可能减少轮班时间。
