SYSTEM AND METHOD TO OBJECTIVELY MEASURE QUALITY ASSURANCE IN ANATOMIC PATHOLOGY

• US 20160239962A1
• Filed: 02/12/2016
• Published: 08/18/2016
• Est. Priority Date: 02/13/2015
• Status: Abandoned Application

• Current Assignee: Prairie Ventures LLC
• Original Assignee: Prairie Ventures LLC
• Inventors: Priebe, Mark L., Markin, Rodney S.
• Application Number:
  US15/042,232
• Publication Number:
  US 20160239962A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06T 2207/10056 Microscopic image
• CPC Class Codes: G06T 2207/30024 Cell structures in vitro; Tissue sections in vitro
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0014 using an image reference approach
• 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: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Techniques are described that facilitate generation of a practice proficiency score related to the quality of a pathology department processes (e.g., quality of/accuracy of pathologist diagnoses, etc.). In one or more implementations, a method may comprise generating an assessment metric based upon a comparison of the first image attribute with a second image attribute. The first image attribute comprises an attribute associated with a digital image representing a specimen. The method also includes receiving a diagnostic confidence metric corresponding to the specimen. The method also includes receiving a diagnostic accuracy metric corresponding to the specimen. The method also includes receiving a turn around time metric corresponding to the specimen. The method also includes receiving a clerical accuracy metric corresponding to the specimen. The method also includes causing a processor to generate a score representing a proficiency corresponding to the specimen. The score is based upon the assessment metric, the diagnostic confidence metric, the diagnostic accuracy metric, the turn around time metric, and the clerical accuracy metric.

Claims

1. A method comprising:

determining, via a processor, a first image attribute of a digital image of a specimen based upon at least one pixel characteristic of the digital image, the digital image captured by an image capture device;

generating an assessment metric based upon a comparison of the first image attribute with a second image attribute provided by a client device;

receiving a diagnostic confidence metric corresponding to the specimen, the diagnostic confidence metric comprising an indication of whether a second review of the specimen occurred;

receiving a diagnostic accuracy metric corresponding to the specimen, the diagnostic accuracy metric comprising an accuracy indication of a diagnosis of the anatomic pathology specimen;

receiving a turn around time metric corresponding to the specimen, the turn around time metric comprising a time ranging from a case accession time to a case sign out time;

receiving a clerical accuracy metric corresponding to the specimen, the clerical accuracy metric comprising a clerical accuracy parameter pertaining to the specimen; and

causing the processor to generate a score representing a proficiency corresponding to the specimen, the score based upon the assessment metric, the diagnostic confidence metric, the diagnostic accuracy metric, the turn around time metric, and the clerical accuracy metric.

2. The method as recited in claim 1, further comprising determining, via a processor, an image quality of the digital image;

causing the image capture device to generate a second digital image of the specimen when the image quality is below a threshold.

3. The method as recited in claim 2, further comprising causing a staining device to apply a stain to the specimen when the image quality is below the threshold.

4. The method as recited in claim 2, wherein determining the image quality further comprises identifying a region of interest of the specimen within the digital image;

and comparing an image characteristics of the region of interest with an image characteristic of the baseline region of interest within a baseline digital image.

5. The method as recited in claim 4, further comprising comparing a hue characteristic of a pixel within the region of interest with a hue characteristic of a pixel within the baseline region of interest.

6. The method as recited in claim 1, further comprising causing the processor to generate an alert;

causing transmission of the alert to a client device, the alert comprising a Uniform Resource Locator link providing access to the score.

7. The method as recited in claim 1, wherein the specimen comprises at least one of an anatomic pathology specimen or a clinical laboratory specimen.

8. A computing device comprising:

a memory operable to store one or more modules; and

a processor communicatively coupled to the memory and operatively coupled to an image capture device, the processor operable to execute the one or more modules to;

determine a first image attribute of a digital image of a specimen based upon at least one pixel characteristic of the digital image, the digital image captured by an image capture device;

generate an assessment metric based upon a comparison of the first image attribute with a second image attribute provided by a client device;

receive a diagnostic confidence metric corresponding to the specimen, the diagnostic confidence metric comprising an indication of whether a second review of the specimen occurred;

receive a diagnostic accuracy metric corresponding to the specimen, the diagnostic accuracy metric comprising an accuracy indication of a diagnosis of the anatomic pathology specimen;

receive a turn around time metric corresponding to the specimen, the turn around time metric comprising a time ranging from a case accession time to a case sign out time;

receive a clerical accuracy metric corresponding to the specimen, the clerical accuracy metric comprising a clerical accuracy parameter pertaining to the specimen; and

generate a score representing a proficiency corresponding to the specimen, the score based upon the assessment metric, the diagnostic confidence metric, the diagnostic accuracy metric, the turn around time metric, and the clerical accuracy metric.

9. The computing device as recited in claim 8, wherein the processor is further operable to execute the one or more modules to determine an image quality of the digital image and causes the image capture device to generate a second digital image of the specimen when the image quality is below a threshold.

10. The computing device as recited in claim 9, wherein the processor is operably coupled to a staining device, the processor further operable to execute the one or more modules to cause the staining device to apply a stain to the specimen when the image quality is below the threshold.

11. The computing device as recited in claim 9, wherein the processor is further operable to execute the one or more modules to identify a region of interest of the specimen within the digital image;

and compare an image characteristics of the region of interest with an image characteristic of the baseline region of interest within a baseline digital image.

12. The computing device as recited in claim 9, wherein the processor is further operable to execute the one or more modules to compare a hue characteristic of a pixel within the region of interest with a hue characteristic of a pixel within the baseline region of interest.

13. The computing device as recited in claim 8, wherein the processor is further operable to execute the one or more modules to generate an alert and cause transmission of the alert to a client device, the alert comprising a Uniform Resource Locator link providing access to the score.

14. The computing device as recited in claim 8, wherein the specimen comprises at least one of an anatomic pathology specimen or a clinical laboratory specimen.

15. A system comprising:

an image capture device;

a client device;

a server configured to communicatively connect to the client device and operatively coupled to the image capture device over a network, the server comprising;

a memory operable to store one or more modules; and

a processor communicatively coupled to the memory, the processor operable to execute the one or more modules to;

determine a first image attribute of a digital image of a specimen based upon at least one pixel characteristic of the digital image, the digital image captured by an image capture device;

generate an assessment metric based upon a comparison of the first image attribute with a second image attribute provided by a client device;

receive a diagnostic confidence metric corresponding to the specimen from the client device, the diagnostic confidence metric comprising an indication of whether a second review of the specimen occurred;

receive a diagnostic accuracy metric corresponding to the specimen from the client device, the diagnostic accuracy metric comprising an accuracy indication of a diagnosis of the anatomic pathology specimen;

receive a turn around time metric corresponding to the specimen from the client device, the turn around time metric comprising a time ranging from a case accession time to a case sign out time;

receive a clerical accuracy metric corresponding to the specimen from the client device, the clerical accuracy metric comprising a clerical accuracy parameter pertaining to the specimen; and

generate a score representing a proficiency corresponding to the specimen from the client device, the score based upon the assessment metric, the diagnostic confidence metric, the diagnostic accuracy metric, the turn around time metric, and the clerical accuracy metric.

16. The system as recited in claim 15, wherein the processor is further operable to execute the one or more modules to determine an image quality of the digital image and causes the image capture device to generate a second digital image of the specimen when the image quality is below a threshold.

17. The system as recited in claim 16, further comprising a staining device, the processor further operable to execute the one or more modules to cause the staining device to apply a stain to the specimen when the image quality is below the threshold.

18. The system as recited in claim 16, wherein the processor is further operable to execute the one or more modules to identify a region of interest of the specimen within the digital image;

and compare an image characteristics of the region of interest with an image characteristic of the baseline region of interest within a baseline digital image.

19. The system as recited in claim 15, wherein the processor is further operable to execute the one or more modules to generate an alert and to cause transmission of the alert to a client device, the alert comprising a Uniform Resource Locator link providing access to the score.

20. The system as recited in claim 15, wherein the specimen comprises at least one of an anatomic pathology specimen or a clinical laboratory specimen.