System and method for protocol adherence

• US 10,361,000 B2
• Filed: 02/02/2018
• Issued: 07/23/2019
• Est. Priority Date: 09/14/2010
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Johnson, Christopher Donald, Tu, Peter Henry, Bonissone, Piero Patrone, Lizzi, Jr., John Michael, Akbay, Kunter Seref, Yu, Ting, Bufi, Corey Nicholas, Avasarala, Viswanath, Iyer, Naresh Sundaram, Yao, Yi, Patwardhan, Kedar Anil, Gao, Dashan
• Primary Examiner(s): Rao, Anand S
• Application Number:
  US15/887,708
• Publication Number:
  US 20180174682A1
• Time in Patent Office: 536 Days
• Field of Search: 348 77, 348143-160, 348521
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G08B 21/245 Reminder of hygiene compliance policies, e.g. of washing hands
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 30/20 for handling medical images, e.g. DICOM, HL7 or PACS
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 80/00 ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring

Abstract

The system and method disclosed herein provides an integrated and automated workflow, sensor, and reasoning system that automatically detects breaches in protocols, appropriately alarms and records these breaches, facilitates staff adoption of protocol adherence, and ultimately enables the study of protocols for care comparative effectiveness. The system provides real-time alerts to medical personnel in the actual processes of care, thereby reducing the number of negative patient events and ultimately improving staff behavior with respect to protocol adherence.

Claims

1. An apparatus comprising:

a processor and memory configured to implement an augmented state transition network encoding a protocol as a plurality of states corresponding to tasks and transitions between the tasks forming a protocol sequence,

the state transitions based on a probability distribution derived from a model of the protocol sequence associated with at least one of a location, a geometric surface point, or a trajectory of at least one of a monitored person or a monitored object in an area being monitored,

wherein the probability distribution represents a likelihood of deviation for the protocol to be monitored based on the states encoding the protocol, the processor to dynamically determine a protocol task violation based on a deviation from a protocol state and output a report of the deviation,

and

wherein the processor is to determine the protocol state based on i) a first state associated with an agent to perform an action, ii) a second state associated with an object that is a recipient of the action, and iii) a third state associated with an event that associates the action with the object and the agent, the processor to process the protocol state to identify the deviation based on an illegal state transition,

the illegal state transition between states in the augmented transition network based on the probability distribution representing the likelihood of deviation and at least one of a spatial or a temporal relationship between the protocol state and a second state of the augmented transition network.

2. The apparatus of claim 1, wherein the processor is to determine, over a plurality of observations, a pattern of protocol events to measure an object and to orient optical sensors to a geometric zone of the object and generates a notice for at least one of positive reinforcement of protocol compliance or task execution enhancement for protocol compliance to in situ monitoring of a target area including the object.

3. The apparatus of claim 2, wherein the task execution enhancement includes providing in-situ feedback including an alarm for the deviation and a proposed response to address the deviation.

4. The apparatus of claim 1, wherein the protocol includes a continuous function monitoring protocol with respect to a plan to facilitate monitoring of an observed device geometry, the protocol derived from the plan, and tasks derived from the protocol.

5. The apparatus of claim 1, wherein the illegal state transition identifies an anomalous task represented by a message that is converted into at least one of an alert, a pattern analysis, or an invocation of workflow change.

6. The apparatus of claim 1, wherein the processor is to implement a protocol reasoning engine, a task reasoning engine, and a state reasoning engine combining to generate at least one of a process optimization, a geometry analysis, or a policy enforcement.

7. The apparatus of claim 6, wherein each of the protocol reasoning engine, the task reasoning engine, and the state reasoning engine is to subscribe to a topic hosted by an information broker to receive messages published by the information broker.

8. The apparatus of claim 1, wherein the protocol is associated with at least one of a finite state machine, a geometry model, or a plurality of geo-spatial zones associated with at least one of a monitored object or area.

9. The apparatus of claim 1, wherein the processor is to provide artificial intelligence to determine the protocol state.

10. The apparatus of claim 1, wherein an ordered ontology defines the protocol and its elemental state spaces in a particular domain of application.

11. A non-transitory, computer-readable medium including instructions which, when executed by a processor, cause the processor to at least:

implement an augmented state transition network encoding a protocol as a plurality of states corresponding to tasks and transitions between the tasks forming a protocol sequence, the state transitions based on a probability distribution derived from a model of the protocol sequence associated with at least one of a location, a geometric surface point, or a trajectory of at least one of a monitored person or a monitored object in an area being monitored,

wherein the probability distribution represents a likelihood of deviation for the protocol to be monitored based on the states encoding the protocol, the processor to dynamically determine a protocol task violation based on a deviation from a protocol state and output a report of the deviation, and wherein the protocol state is to be determined based on i) a first state associated with an agent to perform an action, ii) a second state associated with an object that is a recipient of the action, and iii) a third state associated with an event that associates the action with the object and the agent,

the processor to process the protocol state to identify the deviation based on an illegal state transition, the illegal state transition between states in the augmented transition network based on the probability distribution representing the likelihood of deviation and at least one of a spatial or a temporal relationship between the protocol state and a second state of the augmented transition network.

12. The computer-readable medium of claim 11, wherein the instructions, when executed, cause the processor to determine, over a plurality of observations, a pattern of protocol events to measure an object and to orient optical sensors to a geometric zone of the object and generates a notice for at least one of positive reinforcement of protocol compliance or task execution enhancement for protocol compliance to in situ monitoring of a target area including the object.

13. The computer-readable medium of claim 12, wherein the task execution enhancement includes providing in-situ feedback including an alarm for the deviation and a proposed response to address the deviation.

14. The computer-readable medium of claim 11, wherein the protocol includes a continuous function monitoring protocol with respect to a plan to facilitate monitoring of an observed device geometry, the protocol derived from the plan, and tasks derived from the protocol.

15. The computer-readable medium of claim 11, wherein the illegal state transition identifies an anomalous task represented by a message that is converted into at least one of an alert, a pattern analysis, or an invocation of workflow change.

16. The computer-readable medium of claim 11, wherein the instructions, when executed, cause the processor to implement a protocol reasoning engine, a task reasoning engine, and a state reasoning engine combining to generate at least one of a process optimization, a geometry analysis, or a policy enforcement.

17. The computer-readable medium of claim 16, wherein each of the protocol reasoning engine, the task reasoning engine, and the state reasoning engine subscribes to a topic hosted by an information broker to receive messages published by the information broker.

18. The computer-readable medium of claim 16, wherein the protocol is associated with at least one of a finite state machine, a geometry model, or a plurality of geo-spatial zones associated with at least one of a monitored object or area.

19. The computer-readable medium of claim 11, wherein the instructions, when executed, cause the processor to implement artificial intelligence to determine the protocol state.

20. The computer-readable medium of claim 11, wherein instructions, when executed, cause the processor to interact with optical sensors to provide feedback for the protocol and associated state spaces in a domain defined by an object geometry.