EP-4739201-A2 - SYSTEMS AND METHODS FOR LONGITUDINAL TIMELINE PRESENTATION AND PREDICTIVE CLINICAL DECISION SUPPORT

Abstract

Various methods and systems are provided for a longitudinal patient history timeline and predictive clinical decision support system. In one example, a computing device comprising a display screen displays a menu listing one or more electronic medical records (EMRs) of one or more patients, and additionally is configured to display a patient timeline graphical user interface (GUI) accessible from the menu while the one or more EMR systems are in an un-launched state. The patient timeline GUI displays patient data as longitudinal medical history event elements and includes elements representing predicted outcomes generated by one or more artificial intelligence (AI) algorithms based on the patient data and one or more activity items generated from the patient data. The event elements and the predicted outcome elements are selectable to launch respective pop-up windows with additional information relating to the selected element.

Inventors

• UMLAUFT, DEBRA
• VOJTEK, ATTILA
• ÁRPÁD, LEVENTE
• MASINI, MONICA
• NEHF, Kirsten

Assignees

• GE Precision Healthcare LLC

Dates

Publication Date

20260513

Application Date

20240823

Claims (20)

1. 1. A computing device comprising a display screen, the computing device configured to display on the display screen a menu listing one or more electronic medical records (EMRs) of one or more patients, and additionally being configured to display on the display screen a patient timeline graphical user interface (GUI) accessible from the menu, wherein the patient timeline GUI displays, for each patient, patient data as longitudinal medical history events and one or more predicted outcome elements of one or more corresponding parameters of a plurality of parameters of the patient data, the patient data obtained from the one or more EMRs and the one or more predicted outcome elements generated based at least in part on the patient data, wherein each element of the longitudinal medical history events and the one or more predicted outcome elements is selectable to launch a pop-up window with additional information related to the selected element, and wherein the patient timeline GUI is displayed while the one or more EMRs are in an unlaunched state.
2. 2. The computing device of claim 1, wherein the patient data is segmented into the plurality of parameters and each of the plurality of parameters is further segmented into a plurality of event types.
3. 3. The computing device of claim 2, wherein each of the plurality of parameters is displayed in a separate time aligned graph, wherein each time aligned graph displays a respective predicted outcome element corresponding to a parameter displayed within the time aligned graph.
4. 4. The computing device of claim 1, wherein the patient timeline GUI includes a decision support element, the decision support element being selectable to launch a clinical decision support GUI, the clinical decision support GUI being a modification of the patient timeline GUI wherein the clinical decision support GUI is displayed as a side panel of the patient timeline GUI.
5. 5. The computing device of claim 4, wherein the clinical decision support GUI displays, for each patient, one or more activity recommendations as activity items, the one or more activity recommendations being assigned based on the patient data and a first set of rules.
6. 6. The computing device of claim 5, wherein the one or more predicted outcome elements are displayed within the patient timeline GUI in response to selection of one or more activity items within the clinical decision support GUI.
7. 7. The computing device of claim 6, wherein the one or more predicted outcome elements are generated by one or more artificial intelligence (Al) algorithms based on the one or more activity items and the patient data.
8. 8. The computing device of claim 7, wherein the one or more Al algorithms are determined based on a second set of rules.
9. 9. The computing device of claim 5, wherein the one or more activity recommendations comprise recommendations for at least one of future care, future treatment, future intervention, and future screening.
10. 10. The computing device of claim 4, wherein the clinical decision support GUI comprises a plurality of selectable elements, including an outcome prediction element, an accept element, and a cancel element, wherein the outcome prediction element, when selected for a first activity, triggers generation of predicted outcomes for one or more parameters of the patient data based on the first activity, wherein the accept element, when selected for the first activity, triggers inclusion of the first activity to a care plan, and wherein the cancel element, when selected for a second activity, triggers exclusion of the second activity from the care plan.
11. 11. A method for a longitudinal timeline and predictive clinical decision support system, comprising: displaying a menu listing one or more options for retrieving data of one or more patients from a plurality of data repositories of a hospital, the plurality of data repositories including one or more electronic medical record (EMR) systems; displaying a patient timeline graphical user interface (GUI) that displays, for each patient, a plurality of elements indicating a plurality of history events determined from the retrieved data from the one or more EMR systems, the plurality of elements being arranged chronologically; in response to selection of an element of the plurality of elements, modifying the patient timeline GUI to display a clinical decision support GUI that displays one or more activity items, wherein the patient timeline GUI is displayed while the one or more EMR systems are in an unlaunched state; in response to selection of one or more of the one or more activity items, generating predicted outcomes of one or more parameters of the data based on the one or more activity items; and displaying the predicted outcomes as predicted outcome elements within the patient timeline GUI.
12. 12. The method of claim 11, wherein the predicted outcomes of the one or more parameters are generated based on one or more artificial intelligence (Al) algorithms, wherein the one or more Al algorithms are determined based on a second set of rules applied to the data and the one or more activity items.
13. 13. The method of claim 11, wherein the predicted outcomes of a first parameter comprise a first predicted outcome of a no action condition and one or more second predicted outcome of the one or more activity items, wherein predicted outcomes are generated for the one or more activity items in one or more of an independent manner, a cumulative manner, and a time designated manner.
14. 14. The method of claim 11, further comprising displaying within the patient timeline GUI two or more of a first predicted outcome element for each of the one or more activity items, a second predicted outcome element for a no action condition, a third predicted outcome element for a cumulative condition, and a fourth predicted outcome element for a time designated condition, wherein the two or more are displayed within the same time aligned graph at the same time in an overlapping manner.
15. 15. The method of claim 11 , wherein each of the predicted outcome elements is displayed with a respective color corresponding to a status of a trend of a corresponding predicted outcome.
16. 16. A longitudinal patient history timeline system, comprising: one or more processors; and memory storing instructions executable by the one or more processors to: output, for display on a display device, a patient timeline graphical user interface (GUI) that includes, for a patient, a plurality of time aligned graphs indicating patient history events, wherein each graph is generated by applying a first set of rules to a second set of patient data obtained from an electronic medical record database; display within a modification of the patient timeline GUI, an activity recommendation indicating a suggested care measure based on the patient data; generate predicted outcomes of one or more parameters of the set of patient data based at least in part on the suggested care measure; and display, within one or more of the plurality of time aligned graphs, predicted outcome elements corresponding to the predicted outcomes for each of one or more corresponding parameters.
17. 17. The longitudinal patient history timeline system of claim 16, wherein one or more of the predicted outcome elements for each of the one or more corresponding parameters are selectable to launch a pop-up window displaying additional information relating to a predicted outcome represented by the selected predicted outcome element.
18. 18. The longitudinal patient history timeline system of claim 16, wherein the predicted outcomes of the one or more parameters is generated based on a first suggested care measure and a second suggested care measure.
19. 19. The longitudinal patient history timeline system of claim 18, wherein the first and second suggested care measures are considered in a cumulative manner when generating the predicted outcomes of the one or more parameters.
20. 20. The longitudinal patient history timeline system of claim 18, wherein the first and second suggested care measures are considered in a time aligned manner when generating the predicted outcomes of the one or more parameters.

Description

SYSTEMS AND METHODS FOR LONGITUDINAL TIMELINE PRESENTATION AND PREDICTIVE CLINICAL DECISION SUPPORT CROSS-REFERENCE TO RELATED APPLICATIONS [0001] The present application claims priority to U.S. Patent Application Serial No. 18/455,468, filed August 24, 2023, the contents of which are incorporated by reference herein in their entirety. FIELD [0002] Embodiments of the subject matter disclosed herein relate to care guideline recommendations, and more particularly to an integrated cardiology timeline presentation system including clinical decision support. BACKGROUND [0003] Digital collection, processing, storage, and retrieval of patient medical records may include a conglomeration of large quantities of data. In some examples, the data may include numerous medical procedures and records generated during investigations of the patient, including a variety of examinations, such as blood tests, urine tests, pathology reports, image-based scans, etc. Duration of the diagnosis of a medical condition of a subject followed by treatment may be spread over time from a few days to a few months or even years in the case of chronic diseases, including cardiac or cardiology-related conditions, which may be diseases that take more than one year to cure/treat or in some instances may be lifelong. Over the course of diagnosing and treating chronic disease, the patient may undergo many different treatments and procedures and may move to different hospitals and/or geographic locations. [0004] Physicians are increasingly relying on electronic medical record (EMR) systems to sort through historical health records of the patient during diagnosis, treatment, and monitoring of patient conditions. For patients with chronic cardiac conditions, hundreds or even thousands of EMRs entries may result from numerous visits. Information may also be included in various other data sources, such as radiology systems, picture archiving and communication systems, and many more. Sorting and extracting information from multiple data sources is slow and inefficient, increasing likelihood of missing records when determining care or treatment plans due to data being spread out across a large number of records. BRIEF DESCRIPTION [0005] In one example, a computing device comprises a display screen, the computing device configured to display on the display screen a menu listing one or more electronic medical records (EMRs) of one or more patients, and additionally being configured to display on the display screen a patient timeline graphical user interface (GUI) accessible from the menu, wherein the patient timeline GUI displays, for each patient, patient data as longitudinal medical history events and one or more predicted outcome elements of one or more corresponding parameters of a plurality of parameters of the patient data, the patient data obtained from the one or more EMRs and the one or more predicted outcome elements generated based at least in part on the patient data, wherein each element of the longitudinal medical history event elements and the one or more predicted outcome elements is selectable to launch a pop-up window with additional information related to the selected element, and wherein the patient timeline GUI is displayed while the one or more EMRs are in an unlaunched state. [0006] It should be understood that the brief description above is provided to introduce in simplified form a selection of concepts that are further described in the detailed description. It is not meant to identify key or essential features of the claimed subject matter, the scope of which is defined uniquely by the claims that follow the detailed description. Furthermore, the claimed subject matter is not limited to implementations that solve any disadvantages noted above or in any part of this disclosure. BRIEF DESCRIPTION OF THE DRAWINGS [0007] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. [0008] The present invention will be better understood from reading the following description of non-limiting embodiments, with reference to the attached drawings, wherein below: [0009] FIG. 1 shows a block diagram of an example system for displaying cardiology -focused clinical information of a patient to a user and generating clinical decision support. [0010] FIG. 2 shows a block diagram of an example data processing system. [0011] FIG. 3 is a flowchart illustrating a method for generating and displaying a timeline graphical user interface (GUI) and one or more activity items for a patient. [0012] FIG. 4 is a flowchart illustrating a method for generating and displaying a predicted outcome of one or more parameters based on a selected activity item. [0013] FIG. 5 is a flowchart illustrating a method for generating and displaying a predicted outcome of one or more parameters base