公开(公告)号：USD900872S1

公开(公告)日：2020-11-03

申请号：US29661966

申请日：2018-08-31

Applicant: General Electric Company

Designer： Tamas Fixler ,  Mohammed Uddin ,  Jeffrey Terry ,  Andrew Day

公开(公告)号：USD893548S1

公开(公告)日：2020-08-18

申请号：US29674999

申请日：2018-12-27

Applicant: General Electric Company

Designer： Michelle Mbeo ,  Andrew Day

公开(公告)号：US20200066397A1

公开(公告)日：2020-02-27

申请号：US16110703

申请日：2018-08-23

Applicant: General Electric Company

Inventor： Savanoor Rai ,  Bex George Thomas ,  Andrew Day

IPC: G16H40/20 ,  G06Q10/06 ,  G06N99/00

Abstract: Techniques are described that employ a multifactorial, machine-learning based system and prioritization framework for optimizing patient placement to beds at a medical facility. In one embodiment, a computer-implemented is provided that comprises receiving, by a system operatively coupled to a processor, a patient placement request requesting placement of a patient to a hospital bed of the healthcare facility, wherein the request is associated with information identifying a medical service for the patient and a bed type. The method further comprises, selecting, by the system, a placement prioritization model from a set of placement prioritization models based on the medical service and the bed type, and employing, by the system, the prioritization model and state information regarding a current state of the healthcare facility to determine a prioritization score reflective of a priority level of the patient placement request.

公开(公告)号：US20190034579A1

公开(公告)日：2019-01-31

申请号：US16148584

申请日：2018-10-01

Applicant: General Electric Company

Inventor： Andrew Day ,  Christopher Johnson

IPC: G06F19/00 ,  G16H40/20

Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

公开(公告)号：US20160371441A1

公开(公告)日：2016-12-22

申请号：US14746385

申请日：2015-06-22

Applicant: General Electric Company

Inventor： Andrew Day ,  Christopher Johnson

IPC: G06F19/00

CPC classification number: G06F19/327 ,  G06F19/00 ,  G16H40/20

Abstract: Systems, methods, and computer program products that enable system-wide probabilistic forecasting, alerting, optimizing and activating resources in the delivery of care to address both immediate (near real-time) conditions as well as probabilistic forecasted operational states of the system over an interval that is selectable from the current time to minutes, hours and coming days or weeks ahead are provided. There are multiple probabilistic future states that are implemented in these different time intervals and these may be implemented concurrently for an instant in time control, near term, and long term. Those forecasts along with their optimized control of hospital capacity may be independently calculated and optimized, such as for a dynamic workflow direction over the next hour and also a patient's stay over a period of days. In the present application, a probabilistic and conditional workflow reasoning system enabling complex team-based decisions that improve capacity, satisfaction, and safety is provided. A means to consume user(s) judgment, implement control on specific resource assignments and tasks in a clinical workflow is enabled, as is the dynamical and optimal control of the other care delivery assets being managed by the system so as to more probably achieve operating criteria such as throughput, waiting and schedule risk.

Abstract translation: 系统，方法和计算机程序产品，使系统范围内的概率预测，警报，优化和激活资源在提供护理方面处理即时（近实时）条件以及系统的概率预测操作状态 提供从当前时间到分钟，小时和未来几天或几周可选的时间间隔。 在这些不同的时间间隔内实施了多个概率未来状态，这些可能在时间控制，近期和长期的时间上同时实现。 这些预测以及其对医院能力的优化控制可以独立计算和优化，例如在下一个小时的动态工作流方向以及患者在几天内的停留时间。 在本应用中，提供了一个概率和条件工作流推理系统，实现了改进容量，满意度和安全性的基于团队的决策。 消费用户判断，实施对临床工作流程中特定资源分配和任务的控制的手段得以实现，系统管理的其他护理运送资产的动态和最佳控制也可以实现， 诸如吞吐量，等待和进度风险等标准。