Systems and methods for providing insurer risk data

• US 10,346,922 B2
• Filed: 01/06/2015
• Issued: 07/09/2019
• Est. Priority Date: 01/06/2015
• Status: Active Grant

• Current Assignee: Pareto Intelligence LLC (Convey Health Solutions, Inc.)
• Original Assignee: Pareto Intelligence LLC (Convey Health Solutions, Inc.)
• Inventors: Steele, John, Young, Steven
• Primary Examiner(s): Niquette, Robert R
• Assistant Examiner(s): Nguyen, Liz P
• Application Number:
  US14/590,388
• Publication Number:
  US 20160196611A1
• Time in Patent Office: 1,645 Days
• Field of Search: 705 4
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

Included are systems and methods for providing insurer risk data. Some of the methods include receiving insurance data related to an insurer and determining a captured risk score from the insurance data, the captured risk score being determined by a predetermined calculation. Some of the methods include determining a gap risk score from the insurance data, where the gap risk score being determined from a proprietary calculation that is different than the predetermined calculation, and where the gap risk score identifying a second criteria that was not identified in the captured risk score and the qualifies the insurer for an additional compensation. Some of the methods include providing a user interface that includes data related to the captured risk score and the gap risk score.

Claims

1. A method for providing insurer risk data, comprising:

receiving, by a computing device, insurance data related to an insurer, the insurance data including information related to coverage provided by the insurer;

determining, by the computing device, a captured risk score from the insurance data over a dynamic time period, the captured risk score being determined by a predetermined calculation, the captured risk score being related to a risk taken by the insurer for insuring a first patient that qualifies as a high risk patient, based on first criteria, wherein the insurer is qualified for compensation for insuring the first patient, based on the captured risk score;

determining, by the computing device, a gap risk score from the insurance data, the gap risk score being determined from a proprietary calculation that is different than the predetermined calculation, the gap risk score identifying a second criteria that was not identified in the captured risk score and that qualifies the insurer for an additional compensation;

identifying a plurality of diagnostic and demographic dimensions associated with the first patient to identify a population that drives economic value associated with the gap risk score;

applying a user-defined diagnostic and demographic dimension associated with the first patient to a plurality of patients to identify the population that derives economic value associated with the gap risk score;

calculating a member-level economic consequence, based on the population and the gap risk score;

providing, by the computing device, a user interface that includes data related to the captured risk score, the gap risk score, and data related to the economic value

via the user interface, soliciting a user input to commence a campaign comprising an intervention to reduce the gap risk score;

receiving data related to risk gap closure associated with the intervention; and

refining a risk gap targeting algorithm based at least in part on the received data related to the risk gap closure.

2. The method of claim 1, further comprising determining, from the insurance data, a risk gap source distribution for identifying the gap risk score.

3. The method of claim 1, further comprising determining, from the insurance data, the captured risk score and the gap risk score for a plurality of hierarchical condition categories (HCC).

4. The method of claim 1, further comprising determining, from the insurance data, a medical provider performance statistic, associated with a plurality of predetermined medical specialties, based on at least one of the following:

the gap risk score and the captured risk score.

5. The method of claim 1, further comprising determining a financial consequence associated with the gap risk score.

6. The method of claim 5, wherein the financial consequence includes a transfer payment as a percentage of a premium.

7. The method of claim 5, wherein the financial consequence includes an economic value based on at least one of the following:

a pre-risk adjusted (RA) premium, a pre-RA economic value, a transfer amount, a post-RA economic value, and a post-RA premium.

8. The method of claim 5, wherein determining the financial consequence includes calculating an economic contribution of a plurality of members.

9. The method of claim 8, wherein calculating the economic contribution includes calculating the economic contribution utilizing at least one of the following:

the captured risk score and the gap risk score.

10. A system for providing insurer risk data, comprising:

a processor; and

a memory component that is coupled to the processor, the memory component storing logic that, when executed by the processor, causes the system to perform at least the following;

receive insurance data related to an insurer, the insurance data including information related to coverage provided by the insurer;

determine a captured risk score from the insurance data, the captured risk score being determined by a predetermined calculation, the captured risk score being related to a risk taken by the insurer for insuring a first patient that qualifies as a high risk patient, based on first criteria, wherein the insurer is to be compensated for insuring the first patient, based on the captured risk score;

determine a gap risk score from the insurance data, the gap risk score being determined from a proprietary calculation that is different than the predetermined calculation, the gap risk score identifying a second criteria that was not identified in the captured risk score and that qualifies the insurer for an additional compensation;

identify a plurality of diagnostic and demographic dimensions associated with the first patient to identify a population that drives economic value associated with the gap risk score;

calculate a member-level economic consequence, based on the population and the gap risk score;

provide a user interface that includes data related to at least one of the following;

the captured risk score, the gap risk score, and the member-level economic consequence;

via the user interface, solicit a user input to commence a campaign comprising an intervention to reduce the gap risk score;

receive data related to risk gap closure associated with the intervention; and

refine a risk gap targeting algorithm based at least in part on the received data related to the risk gap closure.

11. The system of claim 10, wherein the logic further causes the system to determine, from the insurance data, a risk gap source distribution for identifying the gap risk score.

12. The system of claim 10, wherein the logic further causes the system to determine, from the insurance data, the captured risk score and the gap risk score for a plurality of hierarchical condition categories (HCC).

13. The system of claim 10, wherein the logic further causes the system to determine, from the insurance data, a medical provider performance statistic, associated with a plurality of predetermined medical specialties, based on the gap risk score.

14. The system of claim 10, wherein the member-level economic consequence includes an economic value based on at least one of the following:

a pre-risk adjusted (RA) premium, a pre-RA economic value, a transfer amount, a post-RA economic value, and a post-RA premium.

15. A non-transitory computer-readable medium for providing insurer risk data that includes logic that, when executed by a processor, causes a computing device to perform at least the following:

receive insurance data related to an insurer over a dynamic time period, the insurance data including information related to coverage provided by the insurer;

determine a captured risk score from the insurance data, the captured risk score being determined by a predetermined calculation, the captured risk score being related to a risk taken by the insurer for insuring a first patient that qualifies as a high risk patient based on first criteria, wherein the insurer is to be compensated for insuring the first patient, based on the captured risk score;

determine a gap risk score from the insurance data, the gap risk score being determined from a proprietary calculation that is different than the predetermined calculation, the gap risk score identifying a second criteria that was not identified in the captured risk score and that qualifies the insurer for an additional compensation;

identify a plurality of diagnostic and demographic dimensions associated with the first patient to identify a population that drives economic value associated with the gap risk score;

calculate a member-level economic consequence, based on the population and the gap risk score;

provide a user interface that includes data related to the captured risk score and the gap risk score

via the user interface, solicit a user input to commence a campaign comprising an intervention to reduce the gap risk score;

receive data related to risk gap closure associated with the intervention; and

refine a risk gap targeting algorithm based at least in part on the received data related to the risk gap closure.

16. The non-transitory computer-readable medium of claim 15, wherein the logic further causes the computing device to determine, from the insurance data, a risk gap source distribution for identifying the gap risk score.

17. The non-transitory computer-readable medium of claim 15, wherein the logic further causes the computing device determine, from the insurance data, the captured risk score and the gap risk score for a plurality of hierarchical condition categories (HCC).

18. The non-transitory computer-readable medium of claim 15, wherein the logic further causes the computing device determine, from the insurance data, a medical provider performance statistic, associated with a plurality of predetermined medical specialties, based on the gap risk score.

19. The non-transitory computer-readable medium of claim 15, wherein the financial consequence includes an economic value based on at least one of the following:

a pre-risk adjusted (RA) premium, a pre-RA economic value, a transfer amount, a post-RA economic value, and a post-RA premium.

20. The non-transitory computer-readable medium of claim 15, wherein the logic further causes the computing device to calculate an economic contribution of a plurality of members, wherein calculating the economic contribution includes calculating the economic contribution utilizing at least one of the following:

the captured risk score and the gap risk score.