METHOD TO VIEW SCHEDULE INTERDEPENDENCIES AND PROVIDE PROACTIVE CLINICAL PROCESS DECISION SUPPORT IN DAY VIEW FORM

• US 20090119126A1
• Filed: 02/29/2008
• Published: 05/07/2009
• Est. Priority Date: 11/15/2005
• Status: Active Grant

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Akbay, Kunter Seref, Johnson, Christopher D., Dulgeroglu, Onur Ilkin
• Granted Patent: US 10,157,355 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/063116 Schedule adjustment for a person or group
• CPC Class Codes: G06Q 10/1095 Meeting or appointment
• 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

Abstract

A system and method for use in managing and preparing for scheduled procedures that are characterized as being interdependent and variable. The disclosed method enables schedule risk management and provides a look-ahead capability along with process diagnostics to isolate specific assets and tasks that can be managed to reduce schedule risk. The method facilitates review of upcoming tasks by the process stakeholders for education as to where the schedule risks reside and in an emulation mode for review and improved scheduling going forward. Clinical workflow is integrated such that process stakeholders and assets are directed in such a way as to keep on, reduce delay risk or recover the schedule.

Claims

1. A method for using probabilities to schedule activities in a clinical environment and modify schedules and clinical processes in healthcare delivery, said method comprising:

selecting protocols for execution in a clinical environment, the protocols driven by patient disease state;

quantifying tasks associated with the selected protocols and determining when the tasks are to be executed;

deriving a daily schedule of tasks for the clinical environment to achieve the selected protocols of care;

selecting decision rules to resolve interdependencies with respect to the tasks;

selecting estimated task durations;

monitoring a state of personnel, equipment, and locations involved in the schedule in the clinical environment as the day progresses; and

modifying the schedule based on a) the state of the personnel, equipment, and locations, b) estimated task durations, and c) interdependencies between the personnel, equipment, and location.

2. The method of claim 1, further comprising calculating a schedule risk based on the interdependencies, estimated task durations, and the state of personnel, equipment, and locations.

3. The method of claim 2, wherein the step of calculating further comprises calculating a schedule risk using assumptions derived from an active process feedback and probabilistic historical task durations and at least one of a) a critical path method and b) program evaluation and review techniques.

4. The method of claim 1, further comprising calculating, using a critical path method and program evaluation and review techniques with assumptions derived from an active process feedback and probabilistic historical task durations, at least one of the following probabilities:

a) a probability that a scheduled task will start at a given time;

b) a probability that a scheduled task will end at a given time; and

c) a probability that a whole or a part of the schedule will at least one of start and end as scheduled.

5. The method of claim 1, further comprising calculating, using a critical path method and program evaluation and review techniques with assumptions derived from an active process feedback and probabilistic historical task durations, at least one of the following times in the daily schedule:

a) a time that a scheduled task will start given a desired probability of a start occurring; and

b) a time that a scheduled task will end given a desired probability of an end occurring.

6. The method of claim 1, further comprising generating an alarm based on said monitoring step to alert a user to a predicted schedule risk.

7. The method of claim 6, wherein the alarm further comprises a proposed schedule modification to address the predicted schedule risk.

8. The method of claim 1, further comprising at least one of a) playing the schedule forward and b) replaying the schedule for the day according to at least one of a) how the tasks for the day were scheduled and b) how the tasks for the day actually occurred.

9. The method of claim 1, further comprising providing one or more summary indicators indicating process state in the schedule.

10. The method of claim 1, further comprising at least one of the following scenarios:

a) providing a historical “

what was”

emulation of the schedule;

b) providing a current “

what is”

visualization of the schedule;

c) providing a future “

what will be”

simulation of the schedule; and

d) providing a predictive “

what if”

scenario generation for the schedule, based on the interdependencies, estimated task durations, and the state of personnel, equipment, and locations.

11. The method of claim 10, wherein said modifying step further comprises adjusting the daily schedule based on at least one of scenarios a), b), c), and d).

12. A system for use in planning procedures subject to variation, the system comprising:

a user interface module configured to allow a user to monitor activities and track a schedule of tasks for a given day, said user interface module configured to permit the user to visualize variation of schedule task times, to visualize scheduling opportunities and constraints, and to view schedule risk information with respect to the schedule of tasks for the day; and

a logic engine coupled to said user interface module, said logic engine configured to load the schedule of tasks for a given day, along with decision rules and protocols and to calculate a schedule risk based on a) task interdependencies between personnel, equipment, and location, b) estimated task durations, and c) a state of personnel, equipment, and locations, said logic engine using process feedback from the schedule of tasks along with probabilistic historical data in conjunction with the schedule risk to provide an alert to the user regarding the schedule risk.

13. The system of claim 12, wherein said logic engine, upon user approval via the user interface module, modifies the schedule based on a) the state of the personnel, equipment, and locations, b) estimated task durations, and c) interdependencies between the personnel, equipment, and location.

14. The system of claim 12, wherein said logic engine calculates a schedule risk using assumptions derived from process feedback from the schedule of tasks and probabilistic historical task duration data and at least one of a) a critical path method and b) program evaluation and review techniques.

15. The system of claim 12, wherein said logic engine calculates, using a critical path method and program evaluation and review techniques with assumptions derived from process feedback from the schedule of tasks and probabilistic historical task duration data, at least one of the following probabilities:

a) a probability that a scheduled task will start at a given time;

b) a probability that a scheduled task will end at a given time; and

c) a probability that a whole or a part of the schedule will at least one of start and end as scheduled.

16. The system of claim 12, wherein said logic engine calculates, using a critical path method and program evaluation and review techniques with assumptions derived from process feedback from the schedule of tasks and probabilistic historical task duration data, at least one of the following times in the daily schedule:

a) a time that a scheduled task will start given a desired probability of a start occurring; and

b) a time that a scheduled task will end given a desired probability of an end occurring.

17. The system of claim 12, wherein the alert further comprises a proposed schedule modification to address the schedule risk.

18. The system of claim 12, wherein said logic engine provides an ability, via said user interface module to at least one of play a simulation of the schedule going forward and replay the schedule for the day according to at least one of a) how the tasks for the day were scheduled and b) how the tasks for the day actually occurred.

19. The system of claim 12, wherein said user interface provides one or more summary indicators indicating a status of a scheduled task as well as a state of one or more of the personnel, equipment, and locations in the schedule.

20. The system of claim 12, wherein said logic engine executes at least one of the following scenarios for display via the user interface module:

a) providing a historical “

what was”

emulation of the schedule;

b) providing a current “

what is”

visualization of the schedule;

c) providing a future “

what will be”

simulation of the schedule; and

d) providing a predictive “

what if”

scenario generation for the schedule, based on the interdependencies, estimated task durations, and the state of personnel, equipment, and locations.

21. The system of claim 12, wherein said logic engine provides an ability to record historical schedules and operating results of task activity with respect to time and resource consumption to enable the learning and tuning capability of time allocation and probibalistic coefficients for the system.

22. A computer-readable medium having a set of instructions for execution on a computer, said set of instructions comprising:

a user interface routine for displaying a schedule of tasks for a given day and allowing a user to monitor activities and track the schedule of tasks along with visualization of timing probabilities, schedule risks, and proposed schedule modifications involving times, locations, personnel, and equipment; and

a probabilistic logic routine for calculating, based on a set of decision rules and schedule protocols, a schedule risk based on a) task interdependencies between personnel, equipment, and location;

b) estimated task durations, and c) a state of personnel, equipment, and locations, said probabilistic logic routine using process feedback from the schedule of tasks along with probabilistic historical data in conjunction with the schedule risk to provide an alert to the user regarding the schedule risk.

23. The computer readable medium of claim 22, wherein said probabilistic logic routine, upon user approval via the user interface routine, modifies the schedule based on a) the state of the personnel, equipment, and locations, b) estimated task durations, and c) interdependencies between the personnel, equipment, and location.

24. The computer readable medium of claim 22, wherein said probabilistic logic routine calculates a schedule risk using assumptions derived from process feedback from the schedule of tasks and probabilistic historical task duration data and at least one of a) a critical path method and b) program evaluation and review techniques.

25. The computer readable medium of claim 22, wherein said probabilistic logic routine executes at least one of the following scenarios for display via the user interface routine:

a) providing a historical “

what was”

emulation of the schedule;

b) providing a current “

what is”

visualization of the schedule;

c) providing a future “

what will be”

simulation of the schedule; and

d) providing a predictive “

what if”

scenario generation for the schedule, based on the interdependencies, estimated task durations, and the state of personnel, equipment, and locations.