Systems and Methods For Healthcare Asset Allocation

• US 20090254360A1
• Filed: 04/02/2008
• Published: 10/08/2009
• Est. Priority Date: 04/02/2008
• Status: Abandoned Application

• Current Assignee: General Electric Company
• Original Assignee: General Electric Company
• Inventors: Choubey, Suresh K.
• Application Number:
  US12/061,452
• Publication Number:
  US 20090254360A1
• 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 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• 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

Certain embodiments of the present invention provide a healthcare asset allocation method including receiving a healthcare asset request, creating a plurality of potential solutions using healthcare asset data, and determining a healthcare asset allocation by applying a genetic algorithm to the plurality of potential solutions using a plurality of genetic algorithm parameters and the healthcare asset request. The healthcare asset data includes data related to assets in a healthcare enterprise.

Claims

1. A healthcare asset allocation method, the method comprising:

receiving a healthcare asset request;

creating a plurality of potential solutions using healthcare asset data, wherein the healthcare asset data comprises data related to assets in a healthcare enterprise; and

determining a healthcare asset allocation by applying a genetic algorithm to the plurality of potential solutions using a plurality of genetic algorithm parameters and the healthcare asset request.

2. The method of claim 1, wherein the plurality of genetic algorithm parameters comprises at least one of an approach type, a crossover rate, a crossover type, a mutation rate, a cost function, a population size, a selection method, and an end condition.

3. The method of claim 1, wherein the step of applying the genetic algorithm comprises:

selecting a portion of the plurality of potential solutions using a cost function;

reproducing at least one new solution using the selected portion;

replacing the plurality of potential solutions with the at least one new solution and the selected portion; and

repeating the selecting, reproducing, and replacing steps until an end condition occurs.

4. The method of claim 3, wherein the reproducing step further comprises:

performing a crossover operation on the selected portion at a crossover rate using a crossover type; and

performing a mutation operation on the selected portion at a mutation rate.

5. The method of claim 4, wherein the crossover rate is 95 percent, and wherein the mutation rate is 2 percent.

6. The method of claim 3, wherein the cost function comprises a distance between a donor department and a requesting department, a transfer cost, a utilization cost, and a facility transfer cost.

7. The method of claim 3, wherein the cost function comprises C_k=Σ

_i=1,n[(X_i−

X_k)²+(Y_i−

Y_k)²]^1/2+C_T+C_U+C_Fik.

8. The method of claim 1, wherein the creating step further comprises retrieving the healthcare asset data from a healthcare asset database component.

9. The method of claim 1, wherein the creating step further comprises specifying the genetic algorithm parameters.

10. The method of claim 1, wherein the plurality of potential solutions comprises 30 potential solutions.

11. The method of claim 1, wherein the healthcare asset data is stored in a healthcare asset database component.

12. The method of claim 1, wherein the method further comprises updating the healthcare asset data using the healthcare asset allocation.

13. An healthcare asset allocation system, the system comprising:

a healthcare asset database component adapted to store healthcare asset data; and

a healthcare asset allocation component adapted to determine a healthcare asset allocation using a genetic algorithm, the stored healthcare asset data, and a plurality of genetic algorithm parameters.

14. The system of claim 13, wherein the system further comprises a user interface component adapted to receive a healthcare asset request, wherein the healthcare asset allocation component is further adapted to use the received healthcare asset request to determine the healthcare asset allocation, and wherein the user interface component is further adapted to display the determined healthcare asset allocation.

15. The system of claim 13, wherein the healthcare asset allocation component is adapted to update the healthcare asset data with the healthcare asset allocation.

16. The system of claim 13, wherein the plurality of genetic algorithm parameters includes at least one of an approach type, a crossover rate, a crossover type, a mutation rate, a cost function, a population size, a selection method, and an end condition.

17. The system of claim 16, wherein the crossover rate is 95 percent, and wherein the mutation rate is 2 percent.

18. The system of claim 16, wherein the cost function comprises C_k=Σ

_i=1,n[(X_i−

X_k)²+(Y_i−

Y_k)²]^1/2+C_T+C_U+C_Fik.

19. The system of claim 16, wherein the selection method is a roulette wheel selection method.

20. A computer-readable medium comprising a set of instructions for execution on a computer, the set of instructions comprising:

a data retrieval routine configured to retrieve healthcare asset data;

a user interface routine configured to receive a healthcare asset request; and

an asset allocation routine configured to determine a healthcare asset allocation using a genetic algorithm, a plurality of genetic algorithm parameters, the healthcare asset request, and the healthcare asset data.