IP Library Granted Patent US 12,567,500
Granted Patent B2
US 12,567,500 · App. 18/810,172 · Granted Mar 3, 2026

System and method for workflow management and image review

Inventors: Rishi Seth (San Francisco, CA); Matthew Long (San Francisco, CA); Michael Emory (San Francisco, CA); John Zarate (San Francisco, CA)
Assignee: RAD AI, Inc.
G16H40/20G16H10/20G16H30/20
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,567,500
App. No.
18/810,172
Filed
Aug 20, 2024
Granted
Mar 3, 2026
Kind
B2
Art Unit
3622
USPC
705/2
Abstract

A system and method for optimizing radiological workflow management and medical image review is disclosed. A preferred embodiment provides a system interoperable with various RIS and PACS systems and that provides efficient access to information, a dynamic prioritized worklist that constantly changes to address optimize distribution of studies and timely review. The novel system facilitates automated assignment, communication between physicians, technicians and radiologists regarding orders, radiographs, reports and studies. The system analyzes exam data, urgency and pendency times, among other things, to automatically determine an overall priority for each case. Cases are assigned for review in the most efficient time, resulting in optimal turnaround time and improved patient care.

Claims (45)

1 . A method comprising:

improving distribution of radiology studies and efficient review of radiology studies based upon an automated analysis of a user by:

providing an administrative server operatively connected to a network, and a database;

generating a study upon accessing memory, at the administrative server, from an order and a set of images received at the administrative server;

generating a worklist, comprising the study and a study priority of the study;

sending the worklist from the administrative server to a client device of the user, responsive to a study list request from the client device;

providing a graphical user interface (GUI) at the client device, operatively connected to the network, and in communication with the administrative server;

displaying, at the GUI of the client device, a set of icons corresponding to a set of studies of the worklist, the set of icons comprising an icon for the study;

dynamically modifying characteristics of the set of icons on the GUI based upon a reprioritization of the set of studies of the worklist determined based upon a set of priority features;

receiving a study selection from the client device,

sending, from the client device to a PACS, a first API call to display an image associated with the study selection,

activating a dictation device upon sending, from the client device to a dictation device, a second API call to receive and log a dictation file; and

at the administrative server and in coordination with sending the first API call and the second API call:

initiating a pendency clock and an elapsed time clock, and

if the pendency clock reaches a timeout limit, causing a timeout message to be displayed at the client device, automatically closing the selected study at the client device, and storing a pendency time value of the pendency clock and an elapsed time value of the elapsed time clock,

wherein modifying characteristics of the set of icons on the GUI based upon the reprioritization comprises automatically escalating a time elapsed icon, corresponding to the study selection, in the worklist if the elapsed time value reaches a threshold value.

2 . The method of claim 1 , further comprising returning a productivity metric for the user associated with the client device, upon receiving a request for user analytics through the GUI, wherein the productivity metric is determined from a number of studies reviewed within a time period indicated in the request.

3 . The method of claim 1 , further comprising reassigning the study from the user to a second user if the productivity metric for the user does not satisfy a condition.

4 . The method of claim 3 , wherein reassigning the study comprises removing the icon for the study from the GUI of the client device for the user, and positioning the icon for the study at a second GUI of a second client device for the second user.

5 . The method of claim 3 , further comprising reassigning the study based upon an evaluation of study urgency, radiologist availability, radiologist credentialing, and radiologist sub-specialization, determined for a set of users.

6 . The method of claim 1 , further comprising:

determining an elapsed time priority value (ETPV) from the elapsed time value and a modulus, determining a study priority number (SPN) for the study selection from the ETPV, and reordering the icons corresponding to the study list at the GUI based upon the SPV.

7 . The method of claim 6 , wherein generating the study priority number comprises determining: an urgency priority value of the study and a medical severity; and deriving the study priority based on the urgency priority value, the medical severity, and the elapsed time priority value.

8 . The method of claim 7 , wherein determining the physiology priority value comprises retrieving a physiology designation and assigning the physiology priority value based upon the physiology designation.

9 . The method of claim 1 , wherein providing the administrative server comprises providing a management application structured to coordinate communication with RIS systems and PACS systems.

10 . The method of claim 1 , further comprising displaying a set of images on the client device.

11 . The method of claim 10 , wherein the set of images comprises at least one of a set of radiological image types comprising an X-ray image, a CT image, an MRI image, a PET image, a mammography image, a DEXA scan, nuclear medicine imaging, and an ultrasound image.

12 . The method of claim 1 , wherein dynamically modifying positions of the set of icons of on the GUI comprises automatically moving the icon for the study to an updated position on the GUI ahead of the initial position on the GUI, based on the elapsed time.

13 . The method of claim 1 , wherein dynamically modifying characteristics of the set of icons on the GUI comprises modifying positions of the set of icons.

14 . The method of claim 1 , wherein dynamically modifying characteristics of the set of icons on the GUI comprises modifying colors of the set of icons.

15 . A method comprising:

improving distribution of radiology studies and efficient review of radiology studies based upon an automated analysis of a user by:

providing an administrative server operatively connected to a network, and a database;

generating a study, upon accessing memory at the administrative server, from an order and a set of images received at the administrative server;

generating a worklist, comprising the study and a study priority of the study;

sending the worklist from the administrative server to a client device of the user, responsive to a study list request from the client device;

providing a graphical user interface (GUI) at the client device, operatively connected to the network, and in communication with the administrative server;

displaying, at the GUI of the client device, a set of icons corresponding to a set of studies of the worklist;

receiving, at the client device, a selection of the study;

modifying characteristics of the set of icons on the GUI in response to the selection;

locking the study for other users and initiating a pendency clock and an elapsed time clock, and

if the pendency clock reaches a timeout limit, causing a timeout message to be displayed at the client device, automatically closing the study at the client device, and storing a pendency time value of the pendency clock and an elapsed time value of the elapsed time clock,

wherein modifying characteristics of the set of icons on the GUI comprises automatically escalating a time elapsed icon, corresponding to the study, in the worklist if the elapsed time value reaches a threshold value.

16 . The method of claim 15 , further comprising returning a productivity metric for the user associated with the client device, upon receiving a request for user analytics through the GUI, wherein the productivity metric is determined from a number of studies reviewed within a time period indicated in the request.

17 . The method of claim 16 , reassigning the study to a second user if the pendency clock reaches the timeout limit, wherein reassigning the study comprises removing the icon for the study from the GUI of the client device for the user, and positioning the icon for the study at a second GUI of a second client device for the second user.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 21, 2024
From: SETH, RISHI; LONG, MATTHEW; EMORY, MICHAEL; ZARATE, JOHN
To: ADVANCED RADIOLOGY MANAGEMENT, LLC
Reel/Frame 068361/0286 →
PURCHASE AGREEMENT Recorded Aug 21, 2024
From: ADVANCED RADIOLOGY MANAGEMENT, LLC
To: RAD AI, INC.
Reel/Frame 068744/0384 →
Continuity (3)
Continuation 17649213 · Jan 28, 2022
Provisional Application 63199850 · Jan 28, 2021
Related Publication 20240412858A1 · Dec 12, 2024
References Cited (52)
US 7865371B2 · Shen · 2011 [cited by applicant]
US 7889896B2 · Roehrig et al. · 2011 [cited by applicant]
US 7895055B2 · Schneider et al. · 2011 [cited by applicant]
US 8160347B2 · Chaudhuri · 2012 [cited by applicant]
US 8165426B2 · Koenig · 2012 [cited by applicant]
US 8370293B2 · Iwase et al. · 2013 [cited by applicant]
US 8468032B2 · Van Hoe · 2013 [cited by applicant]
US 8924233B2 · Backhaus et al. · 2014 [cited by applicant]
US 9276938B2 · Raizada · 2016 [cited by applicant]
US 9519753B1 · Gerdeman et al. · 2016 [cited by applicant]
US 9558323B2 · Jester et al. · 2017 [cited by applicant]
US 9727935B2 · Esposito · 2017 [cited by applicant]
US 10430549B2 · Backhaus · 2019 [cited by applicant]
US 10764289B2 · Raizada · 2020 [cited by applicant]
US 10937164B2 · Steigauf et al. · 2021 [cited by applicant]
US 11361530B2 · Tahmasebi Maraghoosh et al. · 2022 [cited by applicant]
US 11430563B2 · Hasley · 2022 [cited by examiner]
US 11515020B2 · Vozila · 2022 [cited by examiner]
US 11600377B2 · Volkar et al. · 2023 [cited by applicant]
US 11734333B2 · Innanje et al. · 2023 [cited by applicant]
US 11769584B2 · Sin Kwok Wong et al. · 2023 [cited by applicant]
US 12002570B1 · Hernandez · 2024 [cited by examiner]
US 20060139319A1 · Kariathungal et al. · 2006 [cited by applicant]
US 20070143146A1 · Abraham-Fuchs · 2007 [cited by examiner]
US 20100114597A1 · Shreiber · 2010 [cited by examiner]
US 20110218410A1 · Buisman · 2011 [cited by examiner]
US 20130018674A1 · Bedi et al. · 2013 [cited by applicant]
US 20130132104A1 · Wood-Salomon et al. · 2013 [cited by applicant]
US 20130151284A1 · Cohen-Solal et al. · 2013 [cited by applicant]
US 20140257854A1 · Becker et al. · 2014 [cited by applicant]
US 20140358585A1 · Reiner · 2014 [cited by applicant]
US 20170091399A1 · Jester et al. · 2017 [cited by applicant]
US 20190156921A1 · Kohli et al. · 2019 [cited by applicant]
US 20200265946A1 · Benjamin et al. · 2020 [cited by applicant]
US 20200379620A1 · Horiuchi · 2020 [cited by examiner]
US 20210027884A1 · Wood · 2021 [cited by applicant]
US 20210035680A1 · Chen et al. · 2021 [cited by applicant]
US 20210174941A1 · Mathur et al. · 2021 [cited by applicant]
US 20210182745A1 · Esposito · 2021 [cited by applicant]
WO 2011094639A2 · 2011 [cited by applicant]
WO 2012037049A2 · 2012 [cited by applicant]
WO 2013036842A2 · 2013 [cited by applicant]
WO WO2017184576A1 · 2017 [cited by examiner]
WO 2019104093A1 · 2019 [cited by applicant]
WO 2020030545A1 · 2020 [cited by applicant]
A.A.T. Bui; C. Morioka; J.D.N. Dionisio; D.B. Johnson; U.Sinha; S. Ardekani; R.K. Taira; D.R. Aberle; S. El-Saden; H. Kangarloo, openSourcePACS: An Extendable infrastructure for Med image Management, IEEE Trans on Info … [cited by examiner]
Camorlinga, S. , et al., “Modeling of workflow-engaged networks on radiology transfers across a metro network”, (English), IEEE Transactions on information Technology in Biomedicine (vol. 10, Issue: 2, pp. 275-281), Jul… [cited by applicant]
Chacko, A. K., et al., Virtual radiology environment for the Great Plains Medical Command. [cited by applicant]
Halsted, Mark J., et al., “Design, implementation, and assessment of a radiology workflow management system”, American Journal of Roentgenology 191.2 (2008): 321-327. [cited by applicant]
Juluru, Krishna , et al., “Internet-based radiology order-entry, reporting,and workflow management system for coordinating urgent study requests during off-hours”, American Journal of Roentgenology 184.3 (2005): 1017-10… [cited by applicant]
Law, W. , et al., “ntegrated Automatic Examination Assignment u Reduces Radiologist Interruptions: A 2-Year Cohort Study of 232,022 Examinations”, Journal of imaging Informatics in Medicine, 37(1), 25-30, Jan. 9, 2024 (… [cited by applicant]
Wendler, Thomas , et al., “Workflow management systems in radiology.” Medical Imaging 1998: PACS Design and Evaluation:Engineering and Clinical Issues, International Society for Optics and Photonics, vol. 3339, 1998. [cited by applicant]