Automated data integrity auditing system

• US 20030115195A1
• Filed: 01/29/2003
• Published: 06/19/2003
• Est. Priority Date: 03/10/1999
• Status: Active Grant

• Current Assignee: PointRight Inc.
• Original Assignee: LTCQ, Inc.
• Inventors: Fogel, Barry S., Littlehale, Steven B., Kazmer, A. James
• Granted Patent: US 6,957,227 B2
• Time in Patent Office: Days
• US Class Current: 707/3
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

An automated computer-based data integrity auditing system is provided for use in the healthcare industry, financial industry, academic and educational fields, or any other field in which a need exists for monitoring data integrity. Coded data received from a service organization are checked for proper coding and completeness. The coded data are stored in a computer database together with indicators specifying bad data found during the checking step. The stored coded data are processed in a computer to apply at least one data integrity test to a portion of the data. A score is assigned to the tested portion of data based on the data integrity test. Reports are generated by the computer to identify the score together with suggestions for resolving any data integrity and/or coding and completeness problems determined by the system. Real-time reports can also be provided to the organization to assist in coding and entering the data prior to a formal submission to a government agency or the like.

Claims

1. A method for evaluating and scoring the integrity of data provided by an organization, comprising the steps of:

receiving coded data from the organization;

checking the coded data for proper coding and completeness;

storing the coded data in a computer database together with indicators

specifying bad data found during said checking step; and

processing the stored coded data in a computer to;

apply one or more data integrity tests to a portion of data stored in said database that does not have any bad data specified by an indicator;

assign a score to the portion of data based on the data integrity test; and

generate a report that identifies said score together with suggestions for resolving any data validity problems located by said data integrity test.

2. A method in accordance with claim 1 comprising the further step of:

generating a second report that identifies coding and completeness problems identified during said checking step.

3. A method in accordance with claim 2, wherein said second report also provides suggestions for resolving said coding and completeness problems.

4. A method in accordance with claim 3 comprising the further steps of:

generating a third report that identifies individual data integrity issues determined during the data integrity test; and

providing said third report to said organization on a real-time basis.

5. A method in accordance with claim 4, wherein said third report also provides suggestions for resolving said data integrity issues.

6. A method in accordance with claim 1 comprising the further steps of:

applying weights to the results of said data integrity test; and

using said weights to present said score from different perspectives.

7. A method in accordance with claim 6, wherein the weights applied to the results of the data integrity test are based on the likelihood of a plausible excuse for particular data.

8. A method in accordance with claim 1, wherein said report is a real-time report comprising at least one of:

identification of data integrity issues;

options for prevention of data validity problems which include the revision of individual item responses in the data provided and suggested documentation required to explain each data integrity issue that represents unusual clinical circumstances rather than an assessment error;

identification of potential sources of assessment error and potential remedies for said assessment error;

documentation prompts related to at least one of facility-level, chain-level, association-level, and community-level data integrity issues; and

identification of in-service training and process needs.

9. A method in accordance with claim 8, wherein said report further comprises documentation prompts where the entry of valid data results in the generation of a data integrity issue, said documentation prompts indicating documentation to be checked and the required documentation needed to explain the data integrity issue.

10. A method in accordance with claim 8, wherein said report further comprises identification of common sources of error and identification of systematic repairs to correct said errors.

11. A method in accordance with claim 8, wherein the report further comprises identification of at least one of locations, dates, and assessment types giving rise to data integrity issues.

12. A method in accordance with claim 8, wherein said report further comprises identification of facility-level data integrity issues.

13. A method in accordance with claim 8, wherein said report further comprises identification of chain-level data integrity issues.

14. A method in accordance with claim 8, wherein said report further comprises identification of network-level data integrity issues.

15. A method in accordance with claim 8, wherein said report further comprises identification of community-level data integrity issues.

16. A method in accordance with claim 1, wherein the data integrity test is based in part on the prevalence and incidence rates of diagnoses, conditions, and symptoms within a clinical population.

17. A method in accordance with claim 16 where the prevalence and incidence rates are absolute.

18. A method in accordance with claim 16 where the prevalence and incidence rates are relative.

19. A method in accordance with claim 1, wherein the report further comprises:

identification of specific areas of weakness based on repeated data integrity issues, including at least one of processes of assessment, coding, and documentation;

identification of methods of improving data integrity issues in such area(s) of weakness; and

identification of the financial impact of data validity problems on the provider organization.

20. A method in accordance with claim 19, wherein the report further comprises:

identification and dissemination of best practices in assessment and documentation in response to common data validity issues.

21. A method in accordance with claim 19, wherein the report further comprises a notice that a facility'"'"'s excessive rate of a specific item response or combination of specific item responses exceeds a predetermined confidence limit.

22. A method in accordance with claim 19, wherein the report further identifies specific patient populations for the purpose of determining education required at the point of service.

23. A method in accordance with claim 19, wherein the report further identifies specific patient populations for the purpose of determining specific sales channels of goods required by such a patient population.

24. A method in accordance with claim 19, wherein the report further identifies specific patient populations for the purpose of determining a patient referral network.

25. A method in accordance with claim 19, wherein the report further comprises identification of supplies needed by a facility based on the patient population of the facility.

26. A method of calculating the potential impact of data integrity problems on reimbursement, where the reimbursement is based for each individual on a vector of items from a single assessment, comprising the steps of:

for each individual assessment and each data integrity issue involving reimbursement-related items, determining how that data integrity issue could be resolved by revising a single item response;

determining the smallest such change in favor of the payer that would resolve each data integrity issue of an individual assessment in the order that the data integrity issues are listed in the audit system such that no data integrity issues remain to produce an amended data vector that has no data integrity issues and favors the payer;

determining the smallest such change in favor of the organization that would resolve each data integrity issue of an individual assessment in the order that the data integrity issues are listed in the audit system such that no data integrity issues remain to produce an amended data vector that has no data integrity issues and favors the organization; and

calculating reimbursement based on the validity of the original data vector.

27. A method in accordance with claim 26, wherein the step of calculating reimbursement is based on validity of the original data vector.

28. A method in accordance with claim 26, wherein the step of calculating reimbursement is based on validity of the amended data vector that has no data integrity issues and favors the payer.

29. A method in accordance with claim 26, wherein the step of calculating reimbursement is based on validity of the amended data vector that has no data integrity issues and favors the organization.

30. A method in accordance with claim 26, wherein the step of calculating reimbursement is based on an arbitrary rule of the payer for revising payment based on assessments with poor data validity.

31. A method in accordance with claim 26, comprising the further step of aggregating reimbursement across the entire database or a specified subset of the database.

32. A method for assisting facilities in the completion and submission of required regulatory data, comprising the steps of:

checking data provided by the facility for proper coding and completeness in accordance with regulatory requirements;

storing the data in a computer database together with indicators specifying bad data found during said checking step; and

processing the stored data to;

apply one or more data integrity tests to a portion of data stored in said database that does not have any bad data specified by an indicator;

assign a score to the portion of data based on the data integrity test; and

generate and provide to the facility, in real-time, a report that identifies said score together with suggestions for resolving any data validity problems located by said data integrity test;

whereby the facility is able to revise the data in response to said real-time report prior to submission to the regulatory facility.

33. A method in accordance with claim 32 wherein said facility comprises a health care facility and said regulatory data comprises MDS data.

34. A method in accordance with claim 33 wherein said data is provided by said facility in electronic form via a communications channel and said report is provided back to said facility via said communications channel.

35. A method in accordance with claim 32 wherein said data is provided by said facility in electronic form via a communications channel and said report is provided back to said facility via said communications channel.

36. A computer program for assisting facilities in the completion and submission of required regulatory data, said computer program comprising routines for:

checking data provided by the facility for proper coding and completeness in accordance with regulatory requirements;

appending indicators to said data, said indicators specifying bad data found during said checking step;

processing said data to apply one or more data integrity tests to a portion thereof that does not have any bad data specified by an indicator;

assigning a score to the portion of data based on the data integrity test;

generating a report that identifies said score together with suggestions for resolving any data validity problems located by said data integrity test; and

providing said report to the facility on a real-time basis;

whereby the facility is able to revise the data in response to said real-time report prior to submission to the regulatory facility.