SYSTEMS, METHODS AND APPARATUSES FOR PREDICTING CAPACITY OF RESOURCES IN AN INSTITUTION

• US 20100198609A1
• Filed: 02/02/2009
• Published: 08/05/2010
• Est. Priority Date: 02/02/2009
• Status: Active Grant

• Current Assignee: Change Healthcare Holdings, LLC (UnitedHealth Group Incorporated)
• Original Assignee: Mckesson Financial Holdings Limited (McKesson Corp.)
• Inventors: Altmann, Michael, Willard, Keith, Mellin, Andrew, Oswald, Kristin, Myers, Mike, Whelchel, Catherine
• Granted Patent: US 8,799,009 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: G06Q 10/00 Administration; Management
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/0637 Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• 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 method, apparatus, system and computer program product are provided for determining one or more current or future conditions regarding capacity and allocation of resources in an institution. The apparatus enables personnel to utilize predictive tools to identify in real-time or in the near future areas of capacity constraints within the institution. The apparatus includes a processor configured to analyze data which includes information associated with the institution. A portion of the data is generated in real-time during an actual time in which events occur. The processor is capable of using at least a portion of the data to identify current conditions or generate one or more predictions regarding conditions to occur in the future that are associated with resources and capacity of the institution. Also, the processor is capable of analyzing results of the predictions and allocating resources of the institution on the basis of the predicted results.

Claims

1. A method comprising:

analyzing data comprising information associated with a health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur;

using at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity;

analyzing one or more results of the predictions and recommending an allocation of at least one of the one or more resources on the basis of the results; and

determining that one of the conditions corresponds to identifying a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; and

determining that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit.

2. The method of claim 1, further comprising utilizing at least one of the levels of congestion to determine whether to assign one or more other individuals to a respective unit.

3. The method of claim 1, further comprising using the portion of the data to determine one or more future conditions associated with the one or more resources.

4. The method of claim 1, wherein identifying comprises determining a number of beds or rooms predicted to be in use at the predetermined time or during the predetermined time period.

5. The method of claim 4, wherein the individuals comprise patients and the one or more units comprise one or more health care units.

6. The method of claim 1, wherein one of the conditions corresponds to one or more levels of congestion relative to at least two units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit, and wherein the method further comprises utilizing at least one of the levels of congestion to determine whether to transfer one or more other individuals from a first unit to a second unit among the two units.

7. The method of claim 6, further comprising:

displaying the congestion relative to the at least two units; and

utilizing one or more indicators that correspond to the one or more levels of congestion and which are associated with visual representations of the at least two units to determine whether to transfer the other individuals from the first unit to the second unit.

8. The method of claim 1, wherein at least one of the predictions comprises predicting a number of persons needed to work within one or more units of the entity for a time in the future;

and

recommend adding or removing one or more identifiers associated with the persons from one or more staff schedules based on at least one of the results of the predictions, the schedules comprise data indicating the time in the future that events are designated to occur.

9. The method of claim 8, further comprising identifying circumstances causing recommendations for changes to the one or more staff schedules and recommending a modification to the one or more staff schedules before the time in the future.

10. An apparatus comprising a processor configured to:

analyze data comprising information associated with a health care entity, wherein at least some of the data is generated in real-time during an actual time in which one or more events occur;

use at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity;

analyze one or more results of the predictions and recommend an allocation of at least one of the one or more resources on the basis of the results;

determine that one of the conditions corresponds to identifying a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; and

determine that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit.

11. The apparatus of claim 10, wherein the processor is further configured to utilize at least one of the levels of congestion to predict whether to assign one or more other individuals to a respective unit.

12. The apparatus of claim 10, wherein the processor is further configured to use the portion of the data to determine one or more future conditions associated with the one or more resources.

13. The apparatus of claim 10, wherein the processor is further configured to identify the number by determining a number of beds or rooms predicted to be in use at the predetermined time or during the predetermined time period in the future.

14. The apparatus of claim 10, wherein the individuals comprise patients and the one or more units comprise one or more health care units.

15. The apparatus of claim 10, wherein the processor is further configured to:

determine, in the future, that one of the conditions corresponds to one or more levels of congestion relative to at least two units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit; and

utilize at least one of the levels of congestion to determine whether to transfer one or more other individuals from a first unit to a second unit among the two units.

16. The apparatus of claim 15, wherein the processor is further configured to:

display the current and future congestion relative to the at least two units and utilize one or more indicators that correspond to the one or more levels of congestion and which are associated with visual representations of the at least two units to determine whether to transfer the other individuals from the first unit to the second unit.

17. The apparatus of claim 10, wherein the processor is further configured to:

determine that at least one of the predictions comprises predicting a number of persons needed to work within one or more units of the entity for a time in the future; and

recommend adding or removing one or more identifiers associated with the persons from one or more staff schedules based on at least one of the results of the predicting, the schedules comprise data indicating the time in the future that events are designated to occur.

18. The apparatus of claim 17, wherein the processor is further configured to:

identify circumstances causing recommendations for changes to the one or more schedules; and

recommend a modification of the one or more staff schedules before the time in the future.

19. A computer program product, the computer program product comprising at least one computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising:

a first executable portion for analyzing data, comprising information associated with an entity, at least some of the data is generated in real-time during an actual time in which one or more events occur;

a second executable portion for using at least a portion of the data to generate one or more predictions regarding one or more conditions to occur in the future that are associated with one or more resources of the entity;

a third executable portion for analyzing one or more results of the predictions and recommending an allocation of one or more resources on the basis of the results;

a fourth executable portion for determining that one of the conditions corresponds to identifying a number of beds or rooms in one or more units of the entity that will be available at a predetermined time or during a predetermined time period in the future; and

a fifth executable portion for determining that another of the conditions corresponds to one or more levels of congestion within one or more units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit.

20. The computer program product of claim 19 further comprising a sixth executable portion for utilizing at least one of the levels of congestion to determine whether to recommend assigning one or more other individuals to a respective unit to meet future patient demand.

21. The computer program product of claim 19, further comprising a sixth executable portion for using the portion of the data to determine one or more current and future conditions associated with the one or more resources.

22. The computer program product of claim 19, wherein identifying comprises determining a number of beds or rooms predicted to be in use at the predetermined time or during the predetermined time period.

23. The computer program product of claim 19, wherein one of the conditions corresponds to one or more current and future levels of congestion relative to at least two units of the entity, the congestion corresponds to a number of individuals assigned to a respective unit, and wherein the computer program product further comprises a sixth executable portion for utilizing at least one of the levels of congestion to determine whether to transfer one or more other individuals from a first unit to a second unit among the two units.

24. The computer program product of claim 23, further comprising:

a seventh executable portion for displaying the congestion relative to the at least two units; and

an eighth executable portion for utilizing one or more indicators that correspond to the one or more levels of congestion and which are associated with visual representations of the at least two units to determine whether to transfer the other individuals from the first unit to the second unit.