Patent Application
20190198164
Embodiments described herein relate to methods and systems for displaying an image, and more particularly, to displaying medical studies in a patient-centric timeline.
Physicians (such as radiologists and cardiologists) and other medical professionals typically use a commercial picture archive and communication system (PACS) when reviewing medical images (for example, medical image studies or exams). PACS is a central repository for various medical image studies of different modalities. PACS provides defined workflows for reviewing and analyzing the medical images and also functions a functions as a gatekeeper for other systems that access the medical images. A modality is anything that creates an image, x-ray, echocardiogram, magnetic resonance imaging (MM), and the like. Typically, medical images come in various modalities and are stored in the PACS central repository. Additionally, patients may typically have multiple studies at different times that may or may not be related. To understand the history of a patient, physicians often need to search through prior image studies and associated reports for a patient. Depending on the number of studies associated with a patient, a physician may have to scroll through multiple different studies to manually identify a relevant study, submit specific queries to attempt to locate relevant prior studies, or a combination thereof.
To solve these and other problems, embodiments described herein provide a two-dimensional view of prior medical imaging studies, wherein the dimensions are time and relevancy. In particular, the systems and methods described herein provide a patient-centric timeline that displays prior studies of a patient (icons or nodes representing such studies), wherein the position of prior study within the timeline indicates how the prior study is compared to a reference study in chronological order. Thus, embodiments described herein provide a user interface that provides users with easy access of medical images and other medical data for a patient. The user interface may also provide various viewing options for different types of images or data associated with a patient to improve clinical efficiency and accuracy in diagnosing and treating patients.
For example, one embodiment provides a system for generating a patient centric timeline of medical studies. The system comprising an electronic processor configured to receive a selection of a reference medical study associated with a patient, the reference medical study having a reference modality identifier and a reference procedure type in metadata associated with the reference medical study, The electronic processor is also configured to access a plurality of additional medical studies associated with the patient, each of the plurality of additional medical studies having a modality identifier, a procedure type, and a study time in metadata associated with each of the plurality of additional medical studies. The electronic processor is also configured to apply a set of rules to the plurality of additional medical studies to determine a relevancy level for each of the plurality of additional medical studies from a plurality of relevancy levels. The electronic processor applies the set of rules to the plurality of additional medical studies by comparing the reference modality identifier of the reference medical study and modality identifier of each of the plurality of additional medical studies and comparing the reference procedure type of the reference medical study and the procedure type of each of the plurality of additional medical studies. The electronic processor is also configured to generate and display the graphical user interface including the patient-centric timeline, wherein the patient-centric timeline includes a node for each of the plurality of additional medical studies, the node for each of the plurality of additional medical studies positioned along a first dimension of the timeline based on the study time of the additional medical study and positioned along a second dimension of the timeline based on the relevancy level of the additional medical study.
Another embodiment provides a method for generating a patient centric timeline of medical studies. The method includes receiving, with an electronic processor, a selection of a reference medical study associated with a patient, the reference medical study having a reference modality identifier and a reference procedure type in metadata associated with the reference medical study. The method also includes accessing, with the electronic processor, a plurality of additional medical studies associated with the patient, each of the plurality of additional medical studies having a modality identifier, a procedure type, and a study time in metadata associated with each of the plurality of additional medical studies. The method also includes applying, with the electronic processor, a set of rules to the plurality of additional medical studies to determine a relevancy level for each of the plurality of additional medical studies from a plurality of relevancy levels. Applying the set of rules to the plurality of additional medical studies includes comparing the reference modality identifier of the reference medical study and modality identifier of each of the plurality of additional medical studies and comparing the reference procedure type of the reference medical study and the procedure type of each of the plurality of additional medical studies. The method also includes generating, with the electronic processor, and displaying the graphical user interface including the patient-centric timeline, wherein the patient-centric timeline includes a node for each of the plurality of additional medical studies, the node for each of the plurality of additional medical studies positioned along a first dimension of the timeline based on the study time of the additional medical study and positioned along a second dimension of the timeline based on the relevancy level of the additional medical study.
Another embodiment is directed to a non-transitory, computer-readable medium storing instructions that, when executed by an electronic processor, perform a set of functions. The set of functions includes receiving, with the electronic processor, a selection of a reference medical study associated with a patient, the reference medical study having a reference modality identifier and a reference procedure type in metadata associated with the reference medical study. The set of functions also includes accessing, with the electronic processor, a plurality of additional medical studies associated with the patient, each of the plurality of additional medical studies having a modality identifier, a procedure type, and a study time in metadata associated with each of the plurality of additional medical studies. The set of functions also includes applying, with the electronic processor, a set of rules to the plurality of additional medical studies to determine a relevancy level for each of the plurality of additional medical studies from a plurality of relevancy levels. Applying the set of rules to the plurality of additional medical studies includes comparing the reference modality identifier of the reference medical study and modality identifier of each of the plurality of additional medical studies and comparing the reference procedure type of the reference medical study and the procedure type of each of the plurality of additional medical studies. The set of functions also includes generating, with the electronic processor, and displaying the graphical user interface including the patient-centric timeline, wherein the patient-centric timeline includes a node for each of the plurality of additional medical studies, the node for each of the plurality of additional medical studies positioned along a first dimension of the timeline based on the study time of the additional medical study and positioned along a second dimension of the timeline based on the relevancy level of the additional medical study.
Other aspects of the invention will become apparent by consideration of the detailed description and accompanying drawings.
One or more embodiments are described and illustrated in the following description and accompanying drawings. These embodiments are not limited to the specific details provided herein and may be modified in various ways. Furthermore, other embodiments may exist that are not described herein. Also, the functionality described herein as being performed by one component may be performed by multiple components in a distributed manner. Likewise, functionality performed by multiple components may be consolidated and performed by a single component. Similarly, a component described as performing particular functionality may also perform additional functionality not described herein. For example, a device or structure that is “configured” in a certain way is configured in at least that way, but may also be configured in ways that are not listed. Furthermore, some embodiments described herein may include one or more electronic processors configured to perform the described functionality by executing instructions stored in non-transitory, computer-readable medium. Similarly, embodiments described herein may be implemented as non-transitory, computer-readable medium storing instructions executable by one or more electronic processors to perform the described functionality. As used in the present application, “non-transitory computer-readable medium” comprises all computer-readable media but does not consist of a transitory, propagating signal. Accordingly, non-transitory computer-readable medium may include, for example, a hard disk, a CD-ROM, an optical storage device, a magnetic storage device, a ROM (Read Only Memory), a RAM (Random Access Memory), register memory, a processor cache, or any combination thereof.
In addition, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. For example, the use of “including,” “containing,” “comprising,” “having,” and variations thereof herein is meant to encompass the items listed thereafter and equivalents thereof as well as additional items. The terms “connected” and “coupled” are used broadly and encompass both direct and indirect connecting and coupling. Further, “connected” and “coupled” are not restricted to physical or mechanical connections or couplings and can include electrical connections or couplings, whether direct or indirect. In addition, electronic communications and notifications may be performed using wired connections, wireless connections, or a combination thereof and may be transmitted directly or through one or more intermediary devices over various types of networks, communication channels, and connections. Moreover, relational terms such as first and second, top and bottom, and the like may be used herein solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
As noted above, when reviewing a medical study, such as an image study, for a patient, a physician may often attempt to locate additional studies (for example, prior image studies), such as to compare a recent study with a previous study, compare studies of the same anatomy generated using different imaging modalities, or the like. Locating such studies is a tedious process and is subject to human error. Also, the more a physician has to divert his or her attention between reviewing images and other user interfaces (such as user interfaces for querying a PACS), the more eye fatigue the physician may suffer, which can impact the physician's review of medical images.
Accordingly,
The image database 205 includes a memory 216 (a non-transitory, computer-readable medium) storing a plurality of medical images 217. In some embodiments, the image database 205 may be combined with the server 210, the user device 215, or a combination thereof. Also, in some embodiments, the medical images 217 may be stored within a plurality of databases, some of which may be included in the server 210. Although not illustrated in
The server 210 includes a plurality of electrical and electronic components that provide power, operational control, and protection of the components within the server 210. For example, as illustrated in
The electronic processor 225 included in the server 210 may be a microprocessor, an application-specific integrated circuit (ASIC), or other suitable electronic device. The memory 230 includes non-transitory computer-readable medium, such as read-only memory (ROM), random access memory (RAM) (for example, dynamic RAM (DRAM), synchronous DRAM (SDRAM), and the like), electrically erasable programmable read-only memory (EEPROM), flash memory, a hard disk, a secure digital (SD) card, other suitable memory devices, or a combination thereof. The electronic processor 225 accesses and executes computer-readable instructions (“software”) stored in the memory 230. The software may include firmware, one or more applications, program data, filters, rules, one or more program modules, and other executable instructions. For example, the software may include instructions and associated data for performing a set of functions, including the methods described herein. In particular, as illustrated in
The communication interface 235 allows the server 210 to communicate with devices external to the server 210. For example, as illustrated in
The user device 215 may be a terminal or workstation, desktop computer, a laptop computer, a smartphone, a tablet computer, a smart television, a smart wearable, and the like. The user device 215 may include similar components as the server 210. For example, as illustrated in
A user may use the user device 215 to access medical images (and optionally other medical data) stored in the image database 205 and may access the timeline application 236 executed by the server 210 (through a browser application or a dedicated application stored and executed on the user device 215). However, in other embodiments, the medical images 217, the timeline application 236, or both are locally stored and executed by the user device 215 (the electronic processor 245).
As illustrated in
As illustrated in
The electronic processor 225 also automatically applies a set of rules (using the rules engine 238) to the accessed additional medical studies to determine a relevancy level for each of the additional medical studies. In some embodiments, a relevancy level is a numeric score within a predetermined range. In other embodiments, a relevancy level is a category from a predetermined set of categories, such as, for example, most relevant, relevant, least relevant and undetermined. Accordingly, the electronic processor 225 applies the set of rules (implemented via the rules engine 238) to the additional medical studies to compare (i) the reference modality identifier of the reference medical study and modality identifier of each of the plurality of additional medical studies, and (ii) the reference procedure type of the reference medical study and the procedure type of each of the plurality of additional medical studies.
For example,
In some embodiments, the set of rules stored in the rules engine 238 is configurable for a particular user (reviewer), group of users (a clinic, a hospital, a network, or the like), a particular patient or type of patient (patient demographics), disease or condition, imaging modality, number of additional medical studies, or the like. For example, the system 200 can provide a user interface that allows users (or an administrator) to configure the set of rules. Also, in some embodiments, the set of rules stored in the rules engine 238 is generated or customized using machine learning. Machine learning generally refers to the ability of a computer program to learn without being explicitly programmed. In some embodiments, a computer program (for example, a learning engine) is configured to construct a model (for example, one or more algorithms) based on example inputs. Supervised learning involves presenting a computer program with example inputs and their desired (for example, actual) outputs. The computer program is configured to learn a general rule (for example, a model) that maps the inputs to the outputs. The computer program may be configured to perform machine learning using various types of methods and mechanisms. For example, the computer program may perform machine learning using decision tree learning, association rule learning, artificial neural networks, inductive logic programming, support vector machines, clustering, Bayesian networks, reinforcement learning, representation learning, similarity and metric learning, sparse dictionary learning, and genetic algorithms. Using all of these approaches, a computer program may ingest, parse, and understand data and progressively refine models for data analytics. For example, a learning engine may be configured to track actions by a user to identify relevant medical studies and automatically set the rules (models) that can be applied to the reference medical study to determine a level of relevancy as described above.
With continued reference to
For example,
The graphical user interface 400 may also include is a sidebar selection tab 408 that allows a user to display a sidebar or hide a sidebar within the graphical user interface 400. For example, as illustrated in
As illustrated in
Also shown in
Each of the nodes 440, 450, 460, 470, and 480 represents a particular additional medical study associated with the patient. As described above, each of the nodes 440, 450, 460, 470, and 480 are positioned in a first dimension (vertically) within the graphical user interface 400 based on the relevancy level determined for the associated additional medical study. As noted above, in some embodiments, the relevancy of a medical study is categorized as most relevant 418, relevant 419, or least relevant 420. Also, in some embodiments, when the relevancy of the medical study is unknown, the medical study may be categorized as undetermined 421. In some embodiments, the most relevant medical studies are positioned at the top of the graphical user interface 400 followed by the relevant, least relevant, and the undetermined medical studies, which are positioned at the bottom of the graphical user interface 400. For example, if the reference medical study relates to the patient's heart, an additional medical study associated with the patient that is a CT scan of the patient's brain may be identified as least relevant to the reference medical study and, hence, positioned toward the bottom of the graphical user interface 400. As shown in
In some embodiments, each of the nodes 440, 450, 460, 470, and 480 includes an indicator (for example, “CT” indicating a “Computed Tomography”; “CR” indicating “Computed Radiography”; “XA” indicating “X-Ray Angiography”; and “US” indicating “Ultrasound;” or “MR” indicating “magnetic resonance”) that denotes a particular modality associated with the medical study. The indicator of the modality may be textual, numeric, graphical, a color, or the like.
In some embodiments, each of the nodes 440, 450, 460, 470, and 480 also includes an indicator that denotes the number of medical studies associated with a particular node. For example, node 470 includes the indicator “2” to denote that there are two medical studies associated with node 470. Thus, node 470 may be considered an aggregate node that represents multiple nodes and, hence multiple medical studies. Aggregate nodes may be used to group nodes (medical studies) depending on a duration of the timeline or a zoom level of the timeline. For example, when a patient has multiple medical studies conducted over a particular time period, the graphical user interface 400 may not have space to display a separate node for each study. Accordingly, the aggregate nodes displayed within the graphical user interface 400 may change as the duration of the timeline changes, the zoom level of the timeline changes, or the like. A user may select (click, mouse over, or the like) an aggregate node to view additional information or the individual nodes represented by the aggregate node, and a user may select an individual node to view additional information regarding the associated medical study. For example, as illustrated in
Thus, embodiments described herein provide methods and systems for generating a graphical user interface including a patient-centric timeline for medical studies. Various features and advantages are set forth in the following claims.
