Operationalizing Machine Learning and Discrete Event Simulation Models to Improve Clinic Efficiency

运用机器学习和离散事件模拟模型来提高诊所效率

• 批准号: 10664923
• 负责人: Nicole Gray Weiskopf
• 金额: $ 32.73万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10664923
• 关键词: Affect; Ambulatory Care Facilities; Appointment; Books; Childhood; Client satisfaction; Clinic; Clinical; Data; Data Set; Effectiveness; Electronic Health Record; Event; Face; Fast Healthcare Interoperability Resources; Feeling; Glaucoma; Length; Machine Learning; Maps; Methodology; Methods; Modeling; Ophthalmology; Outpatients; Patient Care; Patient Schedules; Patients; Physicians; Production; Provider; Quality of Care; Regulation; Reporting; Research; Resources; Schedule; Testing; Time; Visit; Wait Time; Work; application programming interface; barrier to care; burnout; data access; effectiveness evaluation; electronic health data; follow-up; improved; individual patient; machine learning model; models and simulation; novel; post implementation; predictive modeling; pressure; prospective; tool

PROJECT SUMMARY Physicians often report feeling pressured to see more patients to maintain revenue, while having less available time for patient care. Systematic data-driven methods for efficiently scheduling patients are important as physicians are pressured to see more and more patients. We propose that real time prediction models of patient visit lengths, the likelihood of missing appointments, and of patient wait times will help schedule patients more efficiently. Clinics will be able to safely overbook to avoid empty slots from missed appointments, have guidance for scheduling urgent add-on patients, and provide wait time estimates for patients when there are delays. We will develop methodologies for accessing data needed for these predictions in real time and propose that the integration of these models into workflows will improve scheduling accuracy, patient wait time, and patient satisfaction, while also increasing clinic volumes.

项目总结