METHOD, APPARATUS AND COMPUTER PROGRAM CODE FOR EVALUATING PERFORMANCE BASED ON PROJECTED RETURN AND ESTIMATED COST

• US 20090138340A1
• Filed: 11/28/2007
• Published: 05/28/2009
• Est. Priority Date: 11/28/2007
• Status: Abandoned Application

• Current Assignee: McKesson Corp.
• Original Assignee: McKesson Corp.
• Inventors: Shewell, John, Borr, Christopher A.
• Application Number:
  US11/946,684
• Publication Number:
  US 20090138340A1
• Time in Patent Office: Days
• US Class Current: 705/11
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/06393 Score-carding, benchmarking or key performance indicator [KPI] analysis
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03

Abstract

A method, apparatus and computer program product are provided for assessing the overall performance of a pharmacy, or similar institution or entity, based on its current implementation of various performance measures. The method, apparatus and computer program product may further provide recommendations for performance measures on which to focus based on the current level of implementation, projected performance impact and feasibility of those performance measures. A method and apparatus are similarly provided for enabling a pharmacy, or similar institution or entity, to compare the pharmacy to other pharmacies based on user-defined parameters.

Claims

1. A method comprising:

receiving a definition of a set of performance measures;

assigning a performance impact parameter to respective performance measures, said performance impact parameter based at least in part on a projected return associated with implementation of the performance measure;

receiving an indication of a current level of implementation associated with respective performance measures; and

evaluating an overall performance based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

2. The method of claim 1, wherein evaluating an overall performance further comprises:

generating a recommendation comprising a prioritized list of one or more performance measures for additional implementation based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

3. The method of claim 2 further comprising:

assigning a feasibility parameter to respective performance measures, said feasibility parameter based at least in part on a cost associated with implementation of the performance measure, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the feasibility parameter associated with respective performance measures.

4. The method of claim 2 further comprising:

identifying one or more interdependencies associated with one or more performance measures of the set of performance measures, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the one or more interdependencies identified.

5. The method of claim 1, wherein the set of performance measures comprises one or more subsets of performance measures and wherein evaluating an overall performance further comprises:

determining a current level of implementation associated with respective subsets of performance measures;

determining an overall performance impact parameter associated with respective subsets; and

identifying at least one of the subsets having the greatest opportunity associated therewith based at least in part on the current level of implementation and the overall performance impact associated with respective subsets.

6. An apparatus comprising:

a processor configured to;

receive a definition of a set of performance measures;

assign a performance impact parameter to respective performance measures, said performance impact parameter based at least in part on a projected return associated with implementation of the performance measure;

receive an indication of a current level of implementation associated with respective performance measures; and

evaluate an overall performance based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

7. The apparatus of claim 6, wherein in order to evaluate an overall performance, the processor is further configured to:

generate a recommendation comprising a prioritized list of one or more performance measures for additional implementation based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

8. The apparatus of claim 7, wherein the processor is further configured to:

assign a feasibility parameter to respective performance measures, said feasibility parameter based at least in part on a cost associated with implementation of the performance measure, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the feasibility parameter associated with respective performance measures.

9. The apparatus of claim 7, wherein the processor is further configured to:

identify one or more interdependencies associated with one or more performance measures of the set of performance measures, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the one or more interdependencies identified.

10. The apparatus of claim 6, wherein the set of performance measures comprises one or more subsets of performance measures and wherein in order to evaluate an overall performance, the processor is further configured to:

determine a current level of implementation associated with respective subsets of performance measures;

determine an overall performance impact parameter associated with respective subsets; and

identify at least one of the subsets having the greatest opportunity associated therewith based at least in part on the current level of implementation and the overall performance impact associated with respective subsets.

11. A 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 receiving a definition of a set of performance measures;

a second executable portion for assigning a performance impact parameter to respective performance measures, said performance impact parameter based at least in part on a projected return associated with implementation of the performance measure;

a third executable portion for receiving an indication of a current level of implementation associated with respective performance measures; and

a fourth executable portion for evaluating an overall performance based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

12. The computer program product of claim 11, wherein the fourth executable portion is further configured to:

generate a recommendation comprising a prioritized list of one or more performance measures for additional implementation based at least in part on the current level of implementation and the performance impact parameter associated with respective performance measures.

13. The computer program product of claim 12, wherein the computer-readable program code portions further comprise:

a fifth executable portion for assigning a feasibility parameter to respective performance measures, said feasibility parameter based at least in part on a cost associated with implementation of the performance measure, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the feasibility parameter associated with respective performance measures.

14. The computer program product of claim 12, wherein the computer-readable program code portions further comprise:

a fifth executable portion for identifying one or more interdependencies associated with one or more performance measures of the set of performance measures, wherein the prioritized list of one or more performance measures for additional implementation is further based at least in part on the one or more interdependencies identified.

15. The computer program product of claim 11, wherein the set of performance measures comprises one or more subsets of performance measures and wherein the fourth executable portion is further configured to:

determine a current level of implementation associated with respective subsets of performance measures;

determine an overall performance impact parameter associated with respective subsets; and

identify at least one of the subsets having the greatest opportunity associated therewith based at least in part on the current level of implementation and the overall performance impact associated with respective subsets.

16. A method comprising:

receiving a value for at least two of a plurality of parameters associated with a first entity;

receiving an indication of one or more of the plurality of parameters to be used in creating a group of one or more entities with which to compare the first entity; and

assembling the group of one or more entities by identifying one or more entities having a value for respective one or more indicated parameters that is different than the value received from the first entity in association with the respective one or more indicated parameters and a value for a remaining one or more of the plurality of parameters not indicated that is the same as the value received from the first entity in association with the respective one or more remaining parameters.

17. The method of claim 16 further comprising:

receiving data associated with the first entity;

generating one or more metrics associated with the first entity based at least in part on the data received; and

comparing the first entity to the one or entities of the assembled group based at least in part on the one or more metrics generated.

18. The method of claim 17, wherein the first entity comprises a pharmacy.

19. The method of claim 18, wherein one of the one or more indicated parameters comprises whether the pharmacy whether uses a centralized or decentralized medication distribution model.

20. The method of claim 18, wherein one of the one or more indicated parameters comprises whether the pharmacy uses an automated medication storage and dispensing device.

21. An apparatus comprising:

a processor configured to;

receive a value for at least two of a plurality of parameters associated with a first entity;

receive an indication of one or more of the plurality of parameters to be used in creating a group of one or more entities with which to compare the first entity; and

assemble the group of one or more entities by identifying one or more entities having a value for respective one or more indicated parameters that is different than the value received from the first entity in association with the respective one or more indicated parameters and a value for a remaining one or more of the plurality of parameters not indicated that is the same as the value received from the first entity in association with the respective one or more remaining parameters.

22. The apparatus of claim 21, wherein the processor is further configured to:

receive data associated with the first entity;

generate one or more metrics associated with the first entity based at least in part on the data received; and

compare the first entity to the one or entities of the assembled group based at least in part on the one or more metrics generated.

23. The apparatus of claim 22, wherein the first entity comprises a pharmacy.

24. The apparatus of claim 23, wherein one of the one or more indicated parameters comprises whether the pharmacy whether uses a centralized or decentralized medication distribution model.

25. The apparatus of claim 23, wherein one of the one or more indicated parameters comprises whether the pharmacy uses an automated medication storage and dispensing device.