DUPLICATION DETECTION IN CLINICAL DOCUMENTATION DURING DRAFTING

• US 20160124613A1
• Filed: 12/31/2014
• Published: 05/05/2016
• Est. Priority Date: 11/03/2014
• Status: Active Grant

• Current Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Original Assignee: Cerner Innovation, Inc. (Oracle Corporation)
• Inventors: FINN, CHRISTOPHER S., KOLM, MARGARET C., O'LARTE, DAVID J., CROOKS, STEVEN S., GIFFORD, THOMAS C., TYLER, JD
• Granted Patent: US 11,250,956 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/1748 De-duplication implemented within the file system, e.g. based on file segments de-duplication techniques in storage systems for the management of data blocks G06F3/0641
• CPC Class Codes: G06F 16/2358 Change logging, detection, and notification replication G06F16/27
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/2477 Temporal data queries
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06F 16/335 Filtering based on additional data, e.g. user or group profiles filtering in web context G06F16/9535, G06F16/9536
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 3/0484 for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range
• CPC Class Codes: G06F 3/04842 Selection of displayed objects or displayed text elements G06F3/0482 takes precedence
• CPC Class Codes: G06F 40/151 Transformation
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06F 40/194 Calculation of difference between files
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 70/00 ICT specially adapted for the handling or processing of medical references

Abstract

Methods, systems, and computer-readable media are provided to detect similarities between two or more clinical documents. It is determined that a clinician is currently inputting data into a first clinical document that is associated with a patient. A selectable option is provided on a user interface into which the clinician is currently inputting the data. An indication is received that the selectable option has been selected by the clinician. An algorithm is applied to identify the second clinical document from a plurality of clinical documents. At least a portion of the inputted data in the first clinical document and at least a portion of data in the second clinical document are transformed to generate a new representation of the first clinical document that indicates the similarities that are potentially inaccurate or inappropriate between the first clinical document and the second clinical document.

Claims

1. One or more computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, perform a method of detecting similarities between two or more clinical documents, the method comprising:

detecting that a clinician is currently inputting data into a first clinical document that is associated with a patient;

providing a selectable option on a user interface into which the clinician is currently inputting the data, wherein the selectable option, if selected, causes an indication of similarities between the first clinical document and a second clinical document to be provided;

receiving an indication that the selectable option has been selected by the clinician;

applying an algorithm to identify the second clinical document from a plurality of clinical documents, wherein the second clinical document is identified to be compared to the first clinical document; and

transforming at least a portion of the inputted data in the first clinical document and at least a portion of data in the second clinical document to generate a new representation of the first clinical document that indicates at least a portion of the similarities between the first clinical document and the second clinical document.

2. The media of claim 1, wherein the algorithm that is applied to identify the second clinical document from the plurality of clinical documents considers:

times associated with the first clinical document and the second clinical document,

an identity of one or more clinicians who authored the first and second clinical documents,

an identity of one or more patients associated with the first and second clinical documents,

a type of the first clinical document, or

contents of the first clinical document.

3. The media of claim 1, wherein the new representation of the first clinical document is editable.

4. The media of claim 1, wherein the new representation of the first clinical document also indicates differences between the first clinical document and the second clinical document.

5. The media of claim 1, wherein the similarities between the first clinical document and the second clinical document are indicated by one of highlighting or underlining.

6. The media of claim 1, wherein the first clinical document and the second clinical document are associated with a same patient or are authored by a same clinician.

7. One or more computer-readable media having computer-executable instructions embodied thereon that, when executed by a computing device, perform a method of detecting similarities between two or more clinical documents, the method comprising:

receiving an indication that a clinician is currently inputting data into a first clinical document;

algorithmically identifying a second clinical document to which at least a portion of the inputted data of the first clinical document is to be compared to detect the similarities, wherein the algorithmically identifying is based on one or more of;

(A) times associated with the first clinical document and the second clinical document,

(B) an identity of one or more clinicians who authored the first and second clinical documents,

(C) an identity of one or more patients associated with the first and second clinical documents,

(D) a type of the first clinical document, or

(E) contents of the first clinical document; and

while the clinician is inputting the data into the first clinical document, displaying indications of the similarities between the data of the first clinical document and data of the second clinical document.

8. The media of claim 7, wherein the first clinical document and the second clinical document are simultaneously displayed on the user interface.

9. The media of claim 7, wherein the clinician can edit the first clinical document while the indications of the similarities between the data of the first clinical document and the data of the second clinical document are displayed on the user interface.

10. The media of claim 7, further comprising receiving an indication of a hover action over one of the indications of the similarities.

11. The media of claim 10, further comprising in response to the hover action, presenting an explanation of a problem associated with the similarity between the data of the first clinical document and the data of the second clinical document corresponding to the hover action.

12. A system for detecting similarities between two or more clinical documents, the system comprising:

one or more processors; and

one or more computer storage media storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to;

determine that a user is currently inputting data into a first clinical document associated with a patient,

from at least one database storing a plurality of clinical documents, identify a second clinical document to which the first clinical document is to be compared,

in real time, compare at least one portion of the first clinical document to at least one comparable portion of the second clinical document, and

dynamically present a real-time similarity indicator that indicates to the user how similar the at least the one portion of the first clinical document is to the at least one comparable portion of the second clinical document.

13. The system of claim 12, wherein the real-time similarity indicator is a score.

14. The system of claim 13, further comprising determining the score represented by the real-time similarity indicator at predetermined intervals of time.

15. The system of claim 12, wherein the real-time similarity indicator is determined based on one or more of,

a text similarity measurement,

a quantity of identical phrases or sentences having temporal patterns,

a quantity of identical phrases or sentences that are statistically improbable to be repeated,

a quantity of identical phrases or sentences having charge-related patterns, or

a quantity of phrases or sentences describing clinical procedures or occurrences that are unlikely to repeat from the first point in time corresponding to the first clinical document to the subsequent point in time corresponding to the second clinical document.

16. The system of claim 15, wherein the temporal patterns reference a particular day or a time of day.

17. The system of claim 15, wherein the charge-related patterns reference details of the clinician'"'"'s visit with the patient.

18. The system of claim 15, wherein the score is further based on identical phrases or sentences that are repeated that occur infrequently with respect to a corpus of clinical documents.

19. The system of claim 12, wherein the real-time similarity indicator changes color based on whether a similarity of the first clinical document when compared to the second clinical document exceeds a predetermined threshold.

20. The system of claim 12, wherein the second clinical document is identified based on one or more of:

times associated with the first clinical document and the second clinical document,

an identity of one or more clinicians who authored the first and second clinical documents,

an identity of one or more patients associated with the first and second clinical documents,

a type of the first clinical document, or

contents of the first clinical document.