Adaptive Appointment Systems with Patient Preferences

卫生保健系统在动态环境中运行。卫生服务提供者需要在不增加数据收集负担的情况下首先了解这种环境的技术，随后需要以最佳方式对动态输入作出反应的技术。该项目的关键目标是确定时间戳数据是否可以用来可靠地估计动态变化的患者偏好，并确定具有动态偏好信息的预约系统在多大程度上优于具有静态信息的类似系统。这个项目的智力价值包括开发数学技术，用于从计算机化的预约数据推断和更新患者偏好类别，并开发利用这些信息来改善访问和诊所收入的预约控制策略。该项目将加强现有方法并开发新技术，将动态学习纳入非固定环境。更广泛的影响包括(a)从诊所常规收集的数据中识别和更新患者偏好的实用工具，(b)工程教育，以及(c)改进的医疗保健管理实践。该项目将证明在保健管理中使用动态和适应性方法的好处。这些技术可以应用于其他类似的努力，例如，根据部分观察到的患者数据和医生的输入，开发个性化的治疗和健康计划。该项目将部分资助学生的博士研究，并为本科生提供参与研究的机会。此外，在该项目过程中获得的数据集将用于通过专业后课程培训卫生保健专业人员。除了档案期刊出版物和会议报告外，这项研究的结果还将通过在PI的研究网页http://www.me.umn.edu/labs/scorlab/上的帖子以及通过与当地保健服务提供者的互动来传播。

Health care systems operate in a dynamic environment. Health service providers need techniques to first understand this environment, without increasing the data-collection burden, and subsequently techniques to respond to the dynamic inputs in an optimal fashion. The key objective of this project is to determine if time-stamp data can be used to reliably estimate dynamically evolving patient preferences, and to determine the extent to which an appointment system with dynamic preference information can outperform a similar system with static information. Intellectual merits of this project include the development of mathematical techniques for inferring and updating patient-preference categories from computerized appointments data, and developing booking control policies that utilize this information to improve access as well as clinic revenue. The project will enhance existing methods and develop new techniques for incorporating dynamic learning in non-stationary environments.Broader impacts include (a) practical tools for identifying and updating patient preferences from data routinely collected by clinics, (b) engineering education, and (c) improved health care management practices. This project will serve as a proof of concept of the benefits of using dynamic and adaptive methods in health care management. These techniques can be applied in other similar endeavors, for example, in developing individualized treatment and wellness programs based on partially-observed patient data and physician inputs. The project will help to partially fund doctoral studies of a student and provide opportunities for involving undergraduate students in research. Moreover, the data set obtained during the course of this project will be used to train health care professionals through post-professional courses. In addition to archival journal publications and conference presentations, results of this research will be disseminated by postings on the PI's research web page at http://www.me.umn.edu/labs/scorlab/, and by interactions with local health service providers.