Embodiments of the present disclosure relate generally to managing laboratory information and more specifically to the application of directing workflow by determining a configurable workflow process in an anatomic pathology laboratory.
In an anatomic pathology lab, human or animal tissue is processed through various methods to achieve a thin slice of stained tissue on a slide. In general, the operational work done on a specimen goes from one step or station to another in a sequence. These steps are related to the work being done on the specimen to create a final product of the stained tissue on the slide. Significant time and productivity is lost when this movement through the various laboratory operations is managed inefficiently. However, because the permutations of possible workflow and inventory of items in a lab are so large, it is very difficult to create efficient workflows by current conventional processes.
In the following description, reference is made to the accompanying drawings in which is shown, by way of illustration, specific embodiments in which the disclosure may be practiced. The embodiments are intended to describe aspects of the disclosure in sufficient detail to enable those skilled in the art to practice the invention. Other embodiments may be utilized and changes may be made to the disclosed embodiments without departing from the scope of the disclosure. The following detailed description is not to be taken in a limiting sense, and the scope of the present invention is defined only by the appended claims.
Furthermore, specific implementations shown and described are only examples and should not be construed as the only way to implement the present disclosure unless specified otherwise herein. It will be readily apparent to one of ordinary skill in the art that the various embodiments of the present disclosure may be practiced by numerous other partitioning solutions.
In the following description, elements, circuits, and functions may be shown in block diagram form in order not to obscure the present disclosure in unnecessary detail. Conversely, specific implementations shown and described are exemplary only and should not be construed as the only way to implement the present disclosure unless specified otherwise herein. Additionally, block definitions and partitioning of logic between various blocks is exemplary of a specific implementation. It will be readily apparent to one of ordinary skill in the art that the present disclosure may be practiced by numerous other partitioning solutions. For the most part, details concerning timing considerations and the like have been omitted where such details are not necessary to obtain a complete understanding of the present disclosure and are within the abilities of persons of ordinary skill in the relevant art.
Those of ordinary skill in the art would understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout this description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof. Some drawings may illustrate signals as a single signal for clarity of presentation and description. It will be understood by a person of ordinary skill in the art that the signal may represent a bus of signals, wherein the bus may have a variety of bit widths and the present disclosure may be implemented on any number of data signals including a single data signal.
The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a special purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A general-purpose processor may be considered a special-purpose processor while the general-purpose processor is configured to execute instructions (e.g., software code) related to embodiments of the present disclosure. A processor may also be implemented as a combination of computing devices, such as a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
Also, it is noted that the embodiments may be described in terms of a process that is depicted as a flowchart, a flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe operational acts as a sequential process, many of these acts can be performed in another sequence, in parallel, or substantially concurrently. In addition, the order of the acts may be re-arranged. A process may correspond to a method, a thread, a function, a procedure, a subroutine, a subprogram, etc. Furthermore, the methods disclosed herein may be implemented in hardware, software, or both. If implemented in software, the functions may be stored or transmitted as one or more instructions or code on computer-readable media. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.
In some embodiments, some or all of the features described herein are implemented within a computer processor or processing device that executes software procedures. The transformation of data that occurs according to the specific procedures of embodiments described herein render the processing device executing such embodiments as a special-purpose processing device capable of new functionality that is otherwise not available executing conventional software or logical procedures. In addition, efficient processing of such procedures requires implementation within computer processing systems. Furthermore, the interactions between an electronic storage device to store data associated with the techniques described herein and the computer processing devices to execute the techniques described herein achieve much greater efficacy than would be possible through other non-computerized means.
For at least these reasons, various embodiments of the present disclosure, as described more fully herein, provide a technical solution to one or more problems that arise from technology that could not reasonably be performed by a person, and various embodiments disclosed herein are rooted in computer technology in order to overcome the problems and/or challenges described below. Further, at least some embodiments disclosed herein may improve computer-related technology by allowing computer performance of a function not previously performable by a computer.
It should be understood that any reference to an element herein using a designation such as “first,” “second,” and so forth does not limit the quantity or order of those elements, unless such limitation is explicitly stated. Rather, these designations may be used herein as a convenient method of distinguishing between two or more elements or instances of an element. Thus, a reference to first and second elements does not mean that only two elements may be employed there or that the first element must precede the second element in some manner. In addition, unless stated otherwise, a set of elements may comprise one or more elements.
Elements described herein may include multiple instances of the same element. These elements may be generically indicated by a numerical designator (e.g. 110) and specifically indicated by the numerical indicator followed by an alphabetic designator (e.g., 110A) or a numeric indicator preceded by a “dash” (e.g., 110-1). For ease of following the description, for the most part element number indicators begin with the number of the drawing on which the elements are introduced or most fully discussed. Thus, for example, element identifiers on a
Headings may be included herein to aid in locating certain sections of detailed description. These headings should not be considered to limit the scope of the concepts described under any specific heading. Furthermore, concepts described in any specific heading are generally applicable in other sections throughout the entire specification.
Reference throughout this specification to “one embodiment,” “an embodiment,” or similar language means that a particular feature, structure, or characteristic described in connection with the indicated embodiment is included in at least one embodiment of the present disclosure. Thus, the phrases “in one embodiment,” “in an embodiment,” and similar language throughout this specification may, but do not necessarily, all refer to the same embodiment.
Before describing specific embodiments, and in order to facilitate description in the present disclosure, various terms are described herein. Where ambiguity may exist between the plain meaning, dictionary meaning, and the term as described herein, a person of ordinary skill in the art will recognize the term as described herein will best conform to a more comprehensive understanding of embodiments of the present disclosure.
As used herein, unless referred to specifically with a different meaning, an “accession” is a test or group of tests ordered for a particular specimen received by a lab or other health care service.
As used herein the term “module” means a software process, a collection of software processes, a collection of hardware elements, or a combination thereof configured to implement one or more elements of the present disclosure
As used herein, the term “substantially” in reference to a given parameter, property, or condition means and includes to a degree that one of ordinary skill in the art would understand that the given parameter, property, or condition is met with a small degree of variance, such as, for example, within acceptable manufacturing tolerances. By way of example, depending on the particular parameter, property, or condition that is substantially met, the parameter, property, or condition may be at least 90% met, at least 95% met, or even at least 99% met.
Some drawings presented herein include depictions of a Graphical User Interface (GUI), which may include color elements. Embodiments of the present disclosure address issues such as lab accuracy and lab efficiency. As such, formatting and colors associated with certain elements may be useful for increasing efficiency and accuracy by assisting a user with performing tasks related to presentation and modification of information related to embodiments of the present disclosure.
As non-limiting examples, the computing system 100 may be a user-type computer, a file server, a compute server, a notebook computer, a tablet, a handheld device, a mobile device, or other similar computer system for executing software.
The one or more processors 110 may be configured for executing a wide variety of operating systems and applications including the computing instructions for carrying out embodiments of the present disclosure.
The memory 120 may be used to hold computing instructions, data, and other information for performing a wide variety of tasks including performing embodiments of the present disclosure. By way of example, and not limitation, the memory 120 may include Synchronous Random Access Memory (SRAM), Dynamic RAM (DRAM), Read-Only Memory (ROM), Flash memory, and the like.
Information related to the computing system 100 may be presented to, and received from, a user with one or more user interface elements. As non-limiting examples, the user interface elements may include elements such as displays, keyboards, mice, joysticks, haptic devices, microphones, speakers, cameras, and touchscreens. A display on the computing system may be configured to present a GUI with information about the embodiments of the present disclosure, as is explained below.
The communication elements 150 may be configured for communicating with other devices or communication networks. As non-limiting examples, the communication elements 150 may include elements for communicating on wired and wireless communication media, such as for example, serial ports, parallel ports, Ethernet connections, universal serial bus (USB) connections IEEE 1394 (“firewire”) connections, Bluetooth wireless connections, 802.1 a/b/g/n type wireless connections, and other suitable communication interfaces and protocols.
The storage 140 may be used for storing relatively large amounts of non-volatile information for use in the computing system 100 and may be configured as one or more storage devices. By way of example, and not limitation, these storage devices may include computer-readable media (CRM). This CRM may include, but is not limited to, magnetic and optical storage devices such as disk drives, magnetic tapes, CDs (compact disks), DVDs (digital versatile discs or digital video discs), and other equivalent storage devices.
Software processes illustrated herein are intended to illustrate representative processes that may be performed by the systems illustrated herein. Unless specified otherwise, the order in which the process acts are described is not intended to be construed as a limitation, and acts described as occurring sequentially may occur in a different sequence, or in one or more parallel process streams. It will be appreciated by those of ordinary skill in the art that many steps and processes may occur in addition to those outlined in flow charts. Furthermore, the processes may be implemented in any suitable hardware, software, firmware, or combinations thereof.
When executed as firmware or software, the instructions for performing the processes may be stored on a computer-readable medium. A computer-readable medium includes, but is not limited to, magnetic and optical storage devices such as disk drives, magnetic tape, CDs (compact disks), DVDs (digital versatile discs or digital video discs), and semiconductor devices such as RAM, DRAM, ROM, EPROM, and Flash memory.
By way of non-limiting example, computing instructions for performing the processes may be stored on the storage 140, transferred to the memory 120 for execution, and executed by the processors 110. The processors 110, when executing computing instructions configured for performing the processes, constitutes structure for performing the processes and can be considered a special-purpose computer when so configured. In addition, some or all portions of the processes may be performed by hardware specifically configured for carrying out the processes.
Using a computing system 100 with a graphical operating system, embodiments of the present disclosure include software application tools providing functional panels or windows within the application to segment the functionality. Many panels can be used to describe multiple functions but in this description two of the panels will be presented to the user which control and display the items being utilized within the application tool. The application tool is used to create digital content for various products of which one element could be to generate a GUI to run on a computing system 100 utilizing an LCD touch/display screen. In this application tool, the user provides graphical data in the form of images, pictures, and text to create a digital content output. The digital content output could be represented on a computer screen or hardware screen or output to paper.
In an anatomic pathology laboratory operation, the operational work done on a specimen goes from one step or station to another in a sequence. These steps are related to the work being done on the specimen to create a final product of a stained tissue on a slide that can be presented to the pathologist for reading. Embodiments of the present disclosure include a software application to track each specimen on where it is in the lab workflow process and what step it should go to next. There are several variables that weigh into such decisions, for example: what type of specimen it is and what types of tests need to be performed for final output. To do this, the software application utilizes at least two processing identification items (IDs) within the system: a System Object (SO) and a System Object Map (SOM). These two IDs provide a multi-relational system to qualify the item or thing (System Object) that needs to be operated on and the location within the lab (System Object Map) where the item is presently located, where it needs to go next, or a combination of the two. The System Object Map provides a method that defines connections between two or more entities identified with a use context. These two items (System Objects and System Object Maps) are used to create many-to-many relationships which are then used within the software application for specimen management. The software application utilizes several items (e.g., a database, filesystem, application memory) to provide persistent storage for the System Objects and System Object Maps.
For items being stored in a database, the software application utilizes a relational database system with a set of tables to store the structures. There are different elements that may be defined in the database within the RDBMS (Relational Data Base Management System) schema. Some of these items can be listed as follows:
The software application uses data elements to provide a callback type and value as a return object to the calling function. The input data element allows what is stored in the map as a return value of the callback rather than the input values themselves. The map input for this data element becomes the input signature of the callback function itself, allowing for complex input value processing and evaluation functions such as range lookups, etc. Elements of this type are referenced in the map but are defined as callbacks in the application layer. The configuration value in the map is the return value of the callback (also classified as a Data Element). An example of this could be a Data Element return value of a function call operation which can be configured to a callback. The values configured in the map are the actual operations themselves, the callback (return object) of the function is “called” by the software application to obtain the value.
The software application utilizes a decision flow process to process these maps as shown in
At process block 250, the software application returns the solution found and prepared from operation 242. If the map engine 230 does not find a solution, the map engine returns a non-solution value.
L1 1=>A
L1 2=>B
L1 3=>C
The relationship of the first layer one (L1) 1=>A is a 1:1 of the first item (1) to the second item (A), item (2) is related to B, etc.
Conditional maps based on multiple input combinations of the same scope (different value combinations of the same input type, 1 layer) may be described as:
L1 1.1.2=>A
L1 1.2.1=>B
L1 2.3.2=>C
Complex maps based on multiple input combinations of varying scope (e.g., cascading multiple layers, until a solution is found), can be described as the following:
L3 2.3.4.5.1=>D
L2 1.2.3.1=>E
L2 1.2.3.3=>A
L1 1.1.2=>A
L1 1.2.1=>B
L1 2.3.2=>C
List Generation Mapping—single layer, can be described as:
L1 1.2=>A
L1 1.2=>B
L1 1.2=>C
Equivalency Mapping (Reverse List, single layer), can be described as
L1 1.1=>A
L1 1.2=>A
L1 1.3=>A
Map evaluation information can be configured to define the evaluation process, for example:
As another example, a workflow process step can be defined by describing the steps or operations based on input conditional values of using two maps. These two maps (e.g., A, B) can be defined as:
Map “A” may be defined as:
Map “B” may be defined as:
In the above examples, workflow steps can now be derived by defining input and output operations for each of the levels of map.
For many of the specimens, the sequence is predictable and similar. In some situations, the specimen type is special, a special test flow needs to be applied, or there are other input parameters that affect the lab operation that need to be addressed and route the specimen differently. Different labs will have one or more different special scenarios which cause extra work to be done compared to a normal workflow scenario of tissue and tests. To accommodate these extra variances within the workflow of a lab, the software application used to track the specimens in the lab needs to know about these variances.
The lab manager of the lab utilizes the software application to program the workflow map through a user interface to instruct the software application how to handle the exception cases that can occur. The software application uses these maps to determine all the work flow.
The software application then makes use of a System Object Map to relate the objects with each other.
As another example,
In summary, embodiments of the present disclosure comprise a computing system for managing pathology lab workflow, which includes memory and one or more processors operably coupled to the memory. The memory stores a plurality of system objects, each system object representing an item to be tracked in the pathology lab workflow, the plurality of system objects including objects selected from the group consisting of accession, patient, and tissue samples. The memory also stores the computing instructions and a plurality of system object maps, each system object map designating transitions between operations being tracked within the pathology lab workflow. The one or more processors are configured for executing the computing instructions to perform a multi-relational analysis of two or more system objects of the plurality of system objects applied to one or more system object maps of the plurality of system object maps to identify a next state in the pathology lab for an item being tracked. The processors are also configured to output to a user the next state in the pathology lab for the item being tracked.
Embodiments of the present disclosure also include a computer-implemented method for managing pathology lab workflow. The method includes storing a plurality of system objects, each system object representing an item to be tracked in the pathology lab workflow, the plurality of system objects including objects selected from the group consisting of accession, patient, and tissue samples. The method also includes storing a plurality of system object maps, each system object map designating transitions between operations being tracked within the pathology lab workflow. The method also includes performing a multi-relational analysis of two or more system objects of the plurality of system objects applied to one or more system object maps of the plurality of system object maps to identify a next state in the pathology lab for an item being tracked and outputting to a user the next state in the pathology lab for the item being tracked.
Embodiments of the present disclosure further include a computer-implemented method for managing pathology lab workflow. The method includes configuring a relational database comprising a plurality of system objects maps, each system object map comprising two or more input identifiers and an output identifier. Each system object map is configured to define a relationship of the output identifier with the two or more input identifiers to designate at least one of a transition between operations being tracked within the pathology lab workflow and a relationship between a parent specimen and one or more children specimens. The method further includes performing a mapping process, which comprises receiving a plurality of input values representing an item to be tracked and searching the relational database. Searching the database identifies a specific system object map of the plurality wherein the plurality of input values corelate with the two or more input identifiers for the specific system object map and then either returns a map solution comprising the output identifier for the specific system object map or returns a non-solution value if searching the relational database did not identify any specific system object maps. Finally, the method includes outputting to a user a next state in the pathology lab for the item being tracked responsive to the map solution.
While the disclosure is susceptible to various modifications and implementation in alternative forms, specific embodiments have been shown by way of examples in the drawings and have been described in detail herein. It should be understood that the invention is not limited to the particular forms disclosed. Rather, the invention includes all modifications, equivalents, and alternatives falling within the scope of the following appended claims and their legal equivalents.
This application claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Patent Application Serial No. 62/565,329, filed Sep. 29, 2017, the disclosure of which is hereby incorporated herein in its entirety by this reference. This application is also related to U.S. Patent Application Serial No. TBD, filed concurrently with this application and entitled “Macro-based Diagnoses for Anatomic Pathology,” which claims the benefit under 35 U.S.C. § 119(e) of U.S. Provisional Patent Application Serial No. 62/565,320, filed Sep. 29, 2017, the disclosures of which are hereby incorporated herein in their entirety by this reference.
Number | Date | Country | |
---|---|---|---|
62565329 | Sep 2017 | US |