Offline Patient Data Verification

• US 20160371435A1
• Filed: 06/18/2015
• Published: 12/22/2016
• Est. Priority Date: 06/18/2015
• Status: Active Application

• Current Assignee: IQVIA, Inc. (IQVIA Holdings, Inc.)
• Original Assignee: IMS Health Incorporated (IQVIA Holdings, Inc.)
• Inventors: Pauletto, Stephan
• Application Number:
  US14/743,398
• Publication Number:
  US 20160371435A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/2365 Ensuring data consistency and integrity
• CPC Class Codes: G06F 16/24564 Applying rules; Deductive queries
• CPC Class Codes: G06F 16/24573 using data annotations, e.g. user-defined metadata
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/273 Asynchronous replication or reconciliation
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass

Abstract

Methods, system, and apparatus for verifying offline patient data. In one aspect, a method includes receiving, from a user, an input specifying field values for one or more data fields, receiving a reference file that specifies (i) one or more database rules for a particular dataset, (ii) for each database rule, a score that reflects the occurrence of the database rule within the particular dataset and a logical expression representing the application of the database rule to the particular dataset, comparing the field values specified by the input to the one or more database rules specified in the reference file, determining a confidence score associated with the received input specifying values for the one or more data fields based at least on comparing the field values specified by the input to the one or more database rules; and providing, for output, the confidence score associated with the received input.

Claims

1. A computer-implemented method comprising:

receiving, from a user, an input specifying field values for one or more data fields;

receiving a reference file that specifies (i) one or more database rules for a particular dataset, (ii) for each database rule, a score that reflects the occurrence of the database rule within the particular dataset and a logical expression representing the application of the database rule to the particular dataset;

comparing the field values specified by the input to the one or more database rules specified in the reference file;

determining a confidence score associated with the received input specifying values for the one or more data fields based at least on comparing the field values specified by the input to the one or more database rules; and

providing, for output, the confidence score associated with the received input.

2. The method of claim 1, wherein receiving the input specifying field values for one or more data fields comprises receiving input that includes identifying patient information.

3. The method of claim 2, wherein the identifying patient information includes at least one of:

first name, last name, date of birth, personal contact number, work contact number, city of residence, state of residence, zip code, driver license number, email address, physical street address, or social security number.

4. The method of claim 1, wherein the confidence score represents a likelihood that the input specifying field values for the one or more data fields includes duplicate data within the particular dataset.

5. The method of claim 1, wherein determining the confidence score associated with the received input specifying values for the one or more data fields comprises comparing the specified values for the one or more data fields to reference statistical data.

6. The method of claim 1, wherein comparing the field values specified by the input to the one or more database rules specified in the reference file comprises:

extracting (i) field values and (ii) record values from the received input specifying field values for the one or more data fields;

comparing the extracted field values against the one or more database rules in a field scope included in the reference file; and

comparing the extracted record values against the one or more database rules in a record scope included in the reference file.

7. The method of claim 1, comprising:

parsing a particular dataset including one or more field values associated with one or more data fields;

determining that at least one of the field values contains duplicate values;

generating one or more duplication rules based at least on the data fields associated with the at least one of the field values containing duplicate values;

for each of the one or more duplications rules, (i) calculating a score representing a number of occurrences of the data fields associated with the at least one of the field values containing duplicate values, and (ii) determining a logical expression representing the application of the duplication rule to the particular dataset ; and

generating a reference file that specifies (i) the one or more duplication rules for the particular dataset, and (ii) for each database rule, the score that reflects the occurrence of the data duplication rule within the particular dataset and the logical expression representing the application of the database rule to the particular dataset.

8. The method of claim 1 comprising:

determining that the value of the confidence score associated with the received input specifying values for the one or more data fields is less than a threshold value;

in response, providing an instruction to a user to submit an additional input specifying different values for the one or more data field; and

determining that the additional input is valid based at least on determining that a second confidence score associated with the received additional input is greater than the threshold value.

9. A system comprising:

one or more computers; and

a non-transitory computer-readable medium coupled to the one or more computers having instructions stored thereon, which, when executed by the one or more computers, cause the one or more computers to perform operations comprising;

receiving, from a user, an input specifying field values for one or more data fields;

receiving a reference file that specifies (i) one or more database rules for a particular dataset, (ii) for each database rule, a score that reflects the occurrence of the database rule within the particular dataset and a logical expression representing the application of the database rule to the particular dataset;

comparing the field values specified by the input to the one or more database rules specified in the reference file;

determining a confidence score associated with the received input specifying values for the one or more data fields based at least on comparing the field values specified by the input to the one or more database rules; and

providing, for output, the confidence score associated with the received input.

10. The system of claim 9, wherein receiving the input specifying field values for one or more data fields comprises receiving input that includes identifying patient information.

11. The system of claim 10, wherein the identifying patient information includes at least one of:

first name, last name, date of birth, personal contact number, work contact number, city of residence, state of residence, zip code, driver license number, email address, physical street address, or social security number.

12. The system of claim 9, wherein the confidence score represents a likelihood that the input specifying field values for the one or more data fields includes duplicate data within the particular dataset.

13. The system of claim 9, wherein determining the confidence score associated with the received input specifying values for the one or more data fields comprises comparing the specified values for the one or more data fields to reference statistical data.

14. The system of claim 9, wherein comparing the field values specified by the input to the one or more database rules specified in the reference file comprises:

extracting (i) field values and (ii) record values from the received input specifying field values for the one or more data fields;

comparing the extracted field values against the one or more database rules in a field scope included in the reference file; and

comparing the extracted record values against the one or more database rules in a record scope included in the reference file.

15. The system of claim 9, comprising:

parsing a particular dataset including one or more field values associated with one or more data fields;

determining that at least one of the field values contains duplicate values;

generating one or more duplication rules based at least on the data fields associated with the at least one of the field values containing duplicate values;

for each of the one or more duplications rules, (i) calculating a score representing a number of occurrences of the data fields associated with the at least one of the field values containing duplicate values, and (ii) determining a logical expression representing the application of the duplication rule to the particular dataset ; and

generating a reference file that specifies (i) the one or more duplication rules for the particular dataset, and (ii) for each database rule, the score that reflects the occurrence of the data duplication rule within the particular dataset and the logical expression representing the application of the database rule to the particular dataset.

16. The system of claim 9 comprising:

determining that the value of the confidence score associated with the received input specifying values for the one or more data fields is less than a threshold value;

in response, providing an instruction to a user to submit an additional input specifying different values for the one or more data field; and

determining that the additional input is valid based at least on determining that a second confidence score associated with the received additional input is greater than the threshold value.

17. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:

receiving, from a user, an input specifying field values for one or more data fields;

receiving a reference file that specifies (i) one or more database rules for a particular dataset, (ii) for each database rule, a score that reflects the occurrence of the database rule within the particular dataset and a logical expression representing the application of the database rule to the particular dataset;

comparing the field values specified by the input to the one or more database rules specified in the reference file;

determining a confidence score associated with the received input specifying values for the one or more data fields based at least on comparing the field values specified by the input to the one or more database rules; and

providing, for output, the confidence score associated with the received input.

18. The device of claim 17, wherein comparing the field values specified by the input to the one or more database rules specified in the reference file comprises:

extracting (i) field values and (ii) record values from the received input specifying field values for the one or more data fields;

comparing the extracted field values against the one or more database rules in a field scope included in the reference file; and

comparing the extracted record values against the one or more database rules in a record scope included in the reference file.

19. The device of claim 17, comprising:

parsing a particular dataset including one or more field values associated with one or more data fields;

determining that at least one of the field values contains duplicate values;

generating one or more duplication rules based at least on the data fields associated with the at least one of the field values containing duplicate values;

for each of the one or more duplications rules, (i) calculating a score representing a number of occurrences of the data fields associated with the at least one of the field values containing duplicate values, and (ii) determining a logical expression representing the application of the duplication rule to the particular dataset ; and

generating a reference file that specifies (i) the one or more duplication rules for the particular dataset, and (ii) for each database rule, the score that reflects the occurrence of the data duplication rule within the particular dataset and the logical expression representing the application of the database rule to the particular dataset.

20. The device of claim 17 comprising:

determining that the value of the confidence score associated with the received input specifying values for the one or more data fields is less than a threshold value;

in response, providing an instruction to a user to submit an additional input specifying different values for the one or more data field; and

determining that the additional input is valid based at least on determining that a second confidence score associated with the received additional input is greater than the threshold value.