Cloud-based quality control data management

Abstract

One or more instruments generate test result data. The test result data includes patient data and QC data. The test result data is provided via a local network to a QC data flow system that filters the test result data (e.g., using a set of rules) to extract QC data. The QC data is provided to a cloud-based QC data management platform via an external network. The cloud-based QC data management platform analyzes the QC data and provides the results back to the QC data flow system. The QC dataflow system forwards the results to middleware or instruments that trigger appropriate corrective actions based on the results.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Provisional Application Serial No. 63 / 349,805, filed on June 7, 2022, which is incorporated herein by reference. Technical Field

[0003] The described subject matter relates generally to managing instruments and, in particular, to using a management device to connect communications between instruments and a cloud-based quality control (QC) data management system. Background Art

[0004] Laboratory instruments (e.g., clinical diagnostic instruments) generate QC data indicating the current operating state of the instrument. The expected results can be periodically analyzed by the instrument for its known QC samples, and the actual results can be monitored over time. Therefore, trends or changes in the operating state of the instrument can be detected, predicted or corrected. For example, calibration drift can be identified and corrected, or used to select the appropriate time to trigger a recalibration program. As another example, QC data that vary over time can be used to predict when one or more reagents need to be replaced. It should be understood that a wide range of operations can be performed based on QC data to improve the reliability and functionality of the instrument.

[0005] However, existing QC data management methods are time-consuming and prone to errors. In one class of existing solutions, the operator manually transfers QC data from the instrument to the on-site QC data management system (e.g., by copying the QC data to a USB drive and then uploading it to the QC data management system). This method is prone to human error, and there is a risk that the responsible person forgets to transfer the QC data or edits the QC data before uploading it. In another class of existing solutions, QC data is transferred to the on-site QC data management system via a local network. This method is problematic because the QC data management software needs to be customized for each site, making it difficult to provide support, maintenance and updates. Summary of the invention

[0006] The above and other problems can be solved by using a field QC data stream system in combination with a cloud-based QC data management platform. In various embodiments, the QC data stream system receives QC data from one or more instruments directly or via a laboratory information system (LIS) or other middleware. The QC data stream system filters data according to one or more rules, and provides the filtered data to a cloud-based QC data management platform. The cloud-based QC data management platform analyzes the received QC data, and provides a response to the QC data stream system, which can forward the response to the corresponding instrument. For example, the response can indicate that the instrument is in good working condition, and no action is required, or maintenance or other corrective actions are required. Using a single QC data stream system can encourage adoption, because the instrument itself does not need to interact directly with the cloud. Therefore, as long as the QC data stream system is trusted to be safe, the advantages of cloud processing can be achieved, while reducing the potential safety hazards that are usually associated with such services.

[0007] This architecture can make unified software and / or hardware be used on site, and relevant customization is controlled remotely by the QC data management platform based on cloud.This QC data can be uploaded in a format-independent manner, so that new data formats and instruments can be supported and no major on-site changes are required.Specifically, users can use the same browser or custom application for all sites to view and manage QC data.In certain embodiments, this QC data stream system provides two-way communication.Therefore, users can provide configuration updates to the QC data management platform, and this QC data management platform pushes this update to the QC data management platform to be implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 is a block diagram of a network computing environment suitable for providing cloud-based QC data management according to one embodiment.

[0009] Figure 2 According to an embodiment Figure 1 Block diagram of the QC data flow system.

[0010] Figure 3 According to an embodiment Figure 1 Block diagram of the QC data management platform.

[0011] Figure 4 is a flow chart of a method for providing cloud-based QC data management according to one embodiment.

[0012] Figure 5 According to one embodiment, it is applicable to Figure 1 A block diagram of an example computer for use in a network computing environment. DETAILED DESCRIPTION

[0013] The accompanying drawings and the following description describe certain embodiments only by way of illustration. Those skilled in the art will readily recognize from the following description that alternative embodiments of the structures and methods may be employed without departing from the principles described. In the practicable range, similar or identical reference numerals are used in the accompanying drawings to indicate similar or identical functions. When an element shares a common mark followed by different letters, this indicates that the element is similar or identical. A separate reference to the mark generally refers to any one or any combination of such elements, unless the context indicates otherwise.

[0014] Example System

[0015] Figure 1 One embodiment of a network computing environment 100 suitable for providing cloud-based QC data management is shown. In the embodiment shown, the network computing environment 100 includes a local network 110, a QC data management platform 120, and one or more client devices 130. The local network 110 includes one or more instruments 112, middleware 114, and a QC data flow system 116. The local network 110 and the client device 130 communicate with the QC data management platform 120 via an external network (e.g., the Internet). In other embodiments, the network computing environment 100 includes different or additional elements. In addition, functions can be distributed between elements in a manner different from that described.

[0016] The local network 110 is a computer network maintained by a laboratory or other entity to provide connectivity between instruments 112, middleware 114, and QC data flow systems 116. The physical infrastructure of the local network 110 will typically be located in a single geographic location (e.g., a hospital or testing laboratory), but may also span multiple geographic locations (e.g., multiple laboratories connected by a VPN).

[0017] In the embodiments described below, the instrument 112 is a clinical diagnostic instrument that analyzes patient samples to generate test results, or a laboratory instrument that analyzes samples to generate test results, or other instrument that generates data. The test results typically include patient results and QC data obtained by analyzing patient samples. The QC data may include data generated by analyzing QC samples or running the instrument without samples. Additionally or alternatively, the QC data may include data generated or derived from the test results. The QC data may include data that a user deems relevant for QC purposes. The QC data may include additional information about the operation of the instrument 112. The instrument 112 may also generate value assignment (VA) data, which is used for instrument calibration. Although Figure 1Three instruments (112A, 112B, and 112N) are shown, but it should be understood that the local network 110 may include any number of instruments 112. It should also be understood that in other embodiments, other types of instruments may be managed using the same or similar techniques as described below.

[0018] The instrument 112 provides test result data (including QC data) to the middleware 114. The middleware 114 provides software functions within the local network 110 and manages the operation of the instrument 112. For example, the middleware 114 can be part of a LIS that provides the patient's test results for display to doctors and other operating personnel. In the embodiment shown, the middleware 114 provides the test result data to the QC data flow system 116, and provides the VA data (if used) from the QC data management platform 120 to the relevant instrument 112 or other laboratory system. Alternatively, one or more of the instruments 112 can provide the test result data directly to the QC data flow system 116. In another alternative embodiment, the VA data can be directly dispersed from the QC data flow system 116 to one or more instruments 112.

[0019] The QC data stream system 116 is a field resource that processes test result data and forwards it to the QC data management platform 120. The QC data stream system 116 can be a physical computing system or a virtual machine (e.g., running on a LIS) that acts as an edge node for a local network 110. In one embodiment, the QC data stream system 116 filters the test result data to extract QC data and remove sensitive information, such as patient test results and other personal data. For example, the QC data stream system 116 can be configured to identify the format of the test result data and extract the QC data. The QC data stream system 116 can be configured to identify one or more standardized (or non-standardized) data formats. In addition, the QC data stream system 116 can be remotely updated to identify and process new data formats without the need for technicians to visit the laboratory site.

[0020] Regardless of the precise filtering mechanism used, the QC data flow system 116 sends the QC data to the QC data management platform 120. The QC data flow system 116 receives the response and forwards the response to the middleware 114 or the instrument 112. For example, the response may indicate that the instrument 112 is in good working order and does not require any action, or that maintenance or other corrective action is required. In some embodiments, the middleware 114 or the instrument 112 may automatically trigger preventive maintenance or other corrective actions based on the received response (such as evaluating the instrument calibration value).

[0021] In some embodiments, the QC data flow system 116 enhances network security by disabling all ports except those used to communicate with the QC data management platform 120 and the middleware 114. Therefore, external devices cannot use the QC data flow system 116 as a network entry point into the local network 110. Similarly, the QC data flow system 116 can encrypt some or all of the data sent to the QC data management platform 120 via the external network. Figure 2 Various embodiments of the QC data stream system 116 are described in further detail.

[0022] The QC data management platform 120 includes one or more cloud-based computer systems that process QC data and provide corresponding functions to users. The QC data management platform 120 analyzes the received QC data to determine the operational status of one or more instruments 112. In one embodiment, the QC data management platform 120 compares the received QC data for a certain instrument with the previously received QC data for the instrument to identify patterns or trends. For example, if the measured value for the QC sample is below or above a threshold, the measured value may indicate that the reagent supply needs to be replenished or a component of the instrument 112 needs to be replaced. Additionally or alternatively, the QC data management platform 120 may use a machine learning model to identify the operational status of the instrument 112. The QC data management platform 120 may also provide a user interface (e.g., accessible via a client device 130) through which a user can view results and perform configuration updates. The following will be combined with Figure 3 Various embodiments of the QC data management platform 120 are described in more detail.

[0023] Client device 130 is a computing device that a user may utilize to interact with QC data management platform 120 . Figure 1 Three client devices (130A, 130B, and 130N) are included, but the network computing environment 100 may include any number of client devices 130. In one embodiment, the client devices 130 have a browser or dedicated application installed for interacting with the QC data management platform 120. By directing the browser to a web portal for the QC data management platform 120 (or opening a dedicated application), a user may be presented with a user interface for configuring the QC data flow system 116. For example, a user may submit a new data format for a new instrument 112 so that the QC data flow system 116 can extract QC data from the test result data provided by the new instrument. The QC data management platform 120 can push the new configuration to the QC data flow system 116 for implementation without requiring a technician to have to visit the site where the QC data flow system is located.

[0024] In some embodiments, the QC data management platform 120 may also provide reports or notifications on the operational status of the instruments 112 to the client devices 130. For example, if maintenance is required for a particular instrument 112, a notification may be pushed to the client device 130 associated with the user responsible for that instrument. As another example, the client device 130 may display a report indicating trend patterns in the QC data for the instrument 112 for analysis by the user.

[0025] Figure 2 One embodiment of the QC data flow system 116 is shown. In the embodiment shown, the QC data flow system 116 includes an ingestion module 210, a filtering module 220, a platform interaction module 230, a configuration update module 240, and a local data store 250. In other embodiments, the QC data flow system 116 includes different or additional elements. Furthermore, functionality may be distributed between elements in a manner different from that described.

[0026] Ingestion module 210 receives test result data from one or more instruments. In one embodiment, instrument 112 provides test data to middleware 114 (e.g., provided by a LIS), and middleware 114 pushes the test result data to ingestion module 210. Alternatively, ingestion module 210 may pull the test result data from middleware 114. In either case, the test result data may be provided to ingestion module 210 as received from instrument 112, periodically (e.g., every five minutes, assuming new data is available), when a certain amount of test result data has been generated, or on any other suitable schedule.

[0027] Filter module 220 filters the received test result data to extract QC data. In one embodiment, filter module 220 applies a set of one or more rules to test result data to identify QC data. For example, a first rule can identify the format of test result data (for example, based on the identifier of the instrument 112 of the test result data generated, or by checking the test result data and comparing the test result data with the set of templates of known data formats). A second rule can be selected based on the format of identification, and is applied to extract QC data. This second rule is specific to the data format and identifies which part or parts of the test result data are QC data. It should be understood that a series of rule sets can be used to analyze test result data and extract information of interest. For example, in some embodiments, this rule set can also extract other data and QC data, such as extracting and transmitting instrument diagnostic data to help remote diagnostic instruments or extracting molecular data for performing molecular diagnosis.

[0028] The platform interaction module 230 manages the interaction between the QC data flow system 116 and the QC data management platform 120. In one embodiment, the platform interaction module 230 sends the extracted QC data to the QC data management platform 120, which processes the QC data and sends a return result as a response. The result can indicate the operational status of the instrument 112 corresponding to the QC data. If the result indicates that the instrument 112 is in good working condition, the platform interaction module 230 can send a confirmation to the instrument 112 (via the middleware 114 or directly), thereby causing the instrument to continue to operate normally. On the contrary, if the result indicates that there is a problem, the platform interaction module 230 can send a signal to cause the instrument to suspend operation, and generate an alarm that requires corrective action (e.g., for display at the client device 130), or automatically trigger a corrective action (e.g., preventive maintenance), or perform both.

[0029] In some embodiments, the platform interaction module 230 sends a notification to the QC data streaming system 116 in response to a triggering event. The triggering event may be a loss of connection to the QC data management platform 120 due to an interruption in the Internet connection, the cloud, or any other service of the QC data streaming system 116. Alternatively, the triggering event may be a user-inputted request to store the QC data locally for a period of time. This time may be advantageous in the event of a planned power outage, laboratory closure, weather event affecting the Internet, and other predicted interruptions.

[0030] Regardless of the source of the triggering event, the triggering event causes the QC data streaming system 116 to store the QC data locally for up to a maximum amount of time. The maximum amount of time may be user defined or predetermined (e.g., 90 days). In one embodiment, the QC data streaming system 116 stores the QC data until the connection with the QC data management platform 120 is restored, at which point the stored QC data is forwarded to the QC data management platform and then deleted from the QC data streaming system 116. Alternatively, the QC data streaming system 116 may store the QC data until the maximum amount of time expires or until the user provides other input requests, at which point the QC data may be deleted without forwarding it to the QC data management platform 120.

[0031] The configuration update module 240 processes configuration updates received from the QC data management platform 120. In one embodiment, the configuration update module 240 receives an updated or new set of rules and stores the rule set for future use (e.g., in the local data store 250). In some embodiments, the configuration update module 240 can also distribute software or firmware to other devices within the local network 110. For example, a cloud system manager can securely maintain a list of registered edge devices and allow authorized users to remotely connect to a specific device over a secure connection to update the device's configuration.

[0032] The local data store 250 includes one or more computer-readable media that store data used by the QC data flow system 116. For example, the local data store 250 may include one or more rule sets for processing QC data. Although the local data store 250 is shown as a single entity that is part of the QC data flow system 116, in some embodiments, one or more external devices may be used for storage, which are accessed via the local network 110.

[0033] Figure 3 One embodiment of the QC data management platform 120 is shown. In the embodiment shown, the QC data management platform 120 includes a QC data processing module 310, a user interface module 320, QC data 330, and VA data 340. In other embodiments, the QC data management platform 120 includes different or additional elements. In addition, the functionality can be distributed between the elements in a manner different from that described.

[0034] The QC data processing module 310 receives and processes QC data from the QC data stream system 116. In one embodiment, the QC data processing module 310 receives new QC data from the instrument 112, identifies the instrument (e.g., based on the instrument ID in the new QC data), and retrieves historical QC data for the instrument (e.g., from the QC data 330). The QC data processing module 310 analyzes the new and historical QC data to determine the operational state of the instrument 112. For example, if the new QC data includes one or more values ​​that differ from the historical average or expected value by more than a threshold percentage, an error condition may be triggered. In some embodiments, the QC data processing module 310 may be configured to identify a plurality of different error conditions, each error condition being indicated by a corresponding pattern or change from a historical or expected value. Conversely, if the QC data is within one or more expected ranges, the QC data processing module 310 determines that the instrument 112 is in good working order. Regardless of how the QC data is analyzed, the QC data processing module 310 sends an indication of the results of the analysis to the QC data flow system 116, which implements any required actions, such as pausing operation of the instrument 112 or triggering preventative maintenance.

[0035] The user interface module 320 provides a user interface that a user can access via the client device 130. In one embodiment, the user interface enables a user to generate a report. The report can display some or all of the QC data in the OC data 330 for one or more instruments 112 in an easy to understand format, for example, data values ​​over time can be plotted on a graph to illustrate trends, to enable the user to predict future needs.

[0036] In some embodiments, the user interface enables a user to provide a new configuration for the QC data flow system 116 or the instrument 112. For example, the user may provide a definition of a new data format to enable the QC data flow system 116 to extract QC data from the test result data generated by the new instrument 112. The user interface may also enable a user to remotely log into the QC data flow system 116 or the instrument to provide remote support or maintenance.

[0037] The QC data 330 and the VA data 340 are stored in one or more computer-readable media. The VA data 340 includes assignments that can be used by the control instrument 112 for calibration (e.g., to set ranges). Although the QC data 330 and the VA data 340 are shown as distinct components, in some embodiments, they are stored together in a single data store. In addition, some or all of the QC data 330 and the VA data 340 can be stored remotely and accessed via a network (e.g., in a distributed database).

[0038] Example Method

[0039] Figure 4 A method 400 for providing cloud-based QC data management is shown according to one embodiment. Figure 4 The steps in are shown from the perspective of the QC data flow system 116 executing the method 400. However, some or all of the steps may be performed by other entities or components. In addition, some embodiments may perform the steps in parallel, in a different order, or perform different steps.

[0040] exist Figure 4 In the illustrated embodiment, the method 400 begins with the QC data stream system 116 receiving 410 test result data from the instrument 112. The test result data may include results and QC data generated by analyzing a patient sample. The QC data stream system 116 filters 420 the test result data using a set of one or more rules to extract the QC data. The QC data is provided 430 to a cloud-based QC data management platform 120 (e.g., via the Internet). Because the test result data is filtered 420, any personal and health data of the patient is retained within the laboratory network 110.

[0041] The QC data stream system 116 receives 440 responses to the provided QC data from the QC data management platform 120. The response indicates the result of the analysis performed on the QC data by the QC data management platform 120. For example, the response can indicate whether the instrument 112 is in good working order and whether the patient sample can be continued to be analyzed, or whether maintenance or other corrective actions need to be taken. The QC data stream system 116 forwards the response 450 to the middleware 114 (e.g., LIS), which takes appropriate actions. If the response indicates that the instrument 112 is in good working order, appropriate actions can only allow the instrument to continue to analyze the sample. On the contrary, if the response indicates that there is a problem, appropriate actions can include one or more of the following: causing the instrument 112 to stop analyzing the sample, notifying the responsible user that corrective actions are needed, or triggering preventive maintenance operations. It should be understood that other types of corrective actions are possible and can be recommended or automatically triggered by the middleware 114.

[0042] Computing system architecture

[0043] Figure 5 According to one embodiment, it is suitable for Figure 1 1 is a block diagram of an example computer 500 for use in the network computing environment 100 of FIG. The example computer 500 includes at least one processor 502 coupled to a chipset 504. The chipset 504 includes a memory controller hub 520 and an input / output (I / O) controller hub 522. A memory 506 and a graphics adapter 512 are coupled to the memory controller hub 520, and a display 518 is coupled to the graphics adapter 512. A storage device 508, a keyboard 510, a pointing device 514, and a network adapter 516 are coupled to the I / O controller hub 522. Other embodiments of the computer 500 have different architectures.

[0044] exist Figure 5 In the embodiment shown in , storage device 508 is a non-transitory computer-readable storage medium, such as a hard disk, a compact disk read-only memory (CD-ROM), a DVD, or a solid-state memory device. Memory 506 stores instructions and data used by processor 502. Pointing device 514 is a mouse, trackball, touch screen, or other type of pointing device, and can be used in conjunction with keyboard 510 (which can be an on-screen keyboard) to enter data into computer system 500. Graphics adapter 512 displays images and other information on display 518. Network adapter 516 couples computer system 500 to one or more computer networks, such as local network 110 or an external network.

[0045] Depend on Figures 1 to 3The type of computer used by the entities in the example may vary depending on the embodiment and the processing power required by the entity. For example, the LIS may include multiple blade servers working in concert to provide the described functionality. In addition, the computer may lack some of the components described above, such as keyboard 510, graphics adapter 512, and display 518.

[0046] Additional considerations

[0047] Some parts of the description above describe embodiments in the form of algorithmic processes or operations. These algorithmic descriptions and representations are commonly used by those skilled in the art of computing to effectively convey the essence of their work to other skilled in the art. Although these operations are described functionally, computationally or logically, it should be understood that they are implemented by computer programs including instructions executed by processors or equivalent circuits, microcodes, etc. In addition, sometimes for convenience, the arrangement of these functional operations is referred to as a module without loss of generality.

[0048] As used herein, any reference to "one embodiment" or "an embodiment" means that the particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The phrase "in one embodiment" appearing in various places in the specification does not necessarily all refer to the same embodiment. Similarly, the use of "one" or "an" before an element or component is merely for convenience. The description should be understood to mean that there are one or more elements or components in an element or component, unless it is obvious that it has other meanings.

[0049] When a value is described as "approximately" or "substantially" (or its derivatives), the value should be interpreted as accurate to ±10%, unless otherwise apparent from the context. For example, "approximately ten" should be understood as "within the range of nine to eleven."

[0050] As used herein, the terms "comprises," "comprises," "includes," "including," "has," "having," or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that includes a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent in those processes, methods, articles, or apparatuses. In addition, unless expressly provided otherwise, "or" refers to an inclusive "or" rather than an exclusive "or." For example, a condition A or B satisfies any one of the following: A is true (or exists) and B is false (or does not exist), A is false (or does not exist) and B is true (or exists), and both A and B are true (or exist).

[0051] Upon reading this disclosure, those skilled in the art will appreciate that additional alternative structures and functions for providing cloud-based QC data management are designed for systems and processes. Therefore, although specific embodiments and applications have been shown and described, it will be understood that the described subject matter is not limited to the precise configurations and components disclosed. The scope of protection shall be limited only by the claims below.

Claims

1. A computer-implemented method for providing cloud-based quality control (QC) data management, the method comprising: receiving test result data for the instrument via the local network, the test result data comprising patient data and QC data; filtering the test result data to extract the QC data; Providing the QC data to a cloud-based QC data management platform via an external network; receiving a response to the QC data from the cloud-based QC data management platform, the response indicating an operational status of the instrument; as well as The response is provided via the local network to middleware, the middleware managing the instrument.

2. The computer-implemented method of claim 1, wherein a corrective action is triggered in response to the response.

3. The computer-implemented method of claim 2, wherein the corrective action is automatically triggered preventive maintenance. The computer-implemented method of claim 1 , wherein the filtering is performed using a set of one or more rules.

5. The computer-implemented method of claim 4, further comprising: receiving an updated set of rules from the cloud-based QC data management platform; receiving additional test result data for the instrument; as well as Additional QC data is extracted from the additional test result data using the updated rule set.

6. The computer-implemented method of claim 1, wherein the instrument is a clinical diagnostic instrument.

7. The computer-implemented method of claim 1 , further comprising: identifying a triggering event, the triggering event indicating that a connection to the cloud-based QC data management platform is unavailable; responsive to the triggering event, storing the QC data on the local network for up to a maximum amount of time; as well as In response to receiving an indication that the connection to the cloud-based QC data management platform is again available, the stored QC data is forwarded to the cloud-based QC data management platform.

8. The computer-implemented method of claim 7, further comprising: In response to forwarding the QC data, the QC data is deleted from the local network.

9. The computer-implemented method of claim 7, wherein the triggering event is a user input indicating a planned downtime for the connection to a cloud-based QC data management platform.

10. A network computing system for providing management of QC data, the network computing system comprising: one or more instruments that generate test result data, the test result data comprising patient data and QC data; a laboratory information system (LIS) coupled to the one or more instruments via a local network; a QC data flow system coupled to the LIS via the local network, the QC data flow system comprising one or more computing devices configured to receive the test result data and extract the QC data from the test result data using a set of one or more rules; as well as a QC data management platform coupled to the QC data flow system via an external network, the QC data management platform comprising one or more computing devices configured to process the QC data to generate results and send the results to the QC data flow system via the external network, Wherein the QC data flow system forwards the results to the LIS, and the LIS implements corrective actions for the instrument based on the results.

11. The network computing system of claim 10, wherein the QC data flow system is a computing device located within a geographic space that includes the instrument.

12. The network computing system of claim 10, wherein the QC data flow system is a virtual machine running on the LIS.

13. The network computing system of claim 10, wherein all ports of the QC data flow system are disabled except for ports used to receive the test result data and provide the QC data to the QC data management platform.

14. The network computing system according to claim 10, further comprising: identifying a triggering event, the triggering event indicating that a connection to the cloud-based QC data management platform is unavailable; responsive to the triggering event, storing the QC data on the local network for up to a maximum amount of time; as well as In response to receiving an indication that the connection to the cloud-based QC data management platform is again available, the stored QC data is forwarded to the cloud-based QC data management platform.

15. The network computing system according to claim 14, further comprising: In response to forwarding the QC data, the QC data is deleted from the local network.

16. The network computing system of claim 14, wherein the triggering event is a user input indicating a planned downtime for the connection to a cloud-based QC data management platform.

17. A non-transitory computer readable medium configured to store code comprising instructions, wherein the instructions, when executed by one or more processors, cause the one or more processors to perform steps comprising: receiving test result data for the instrument via the local network, the test result data comprising patient data and QC data; filtering the test result data to extract the QC data; Providing the QC data to a cloud-based QC data management platform via an external network; receiving a response to the QC data from the cloud-based QC data management platform, the response comprising an operational status of the instrument; as well as The response is provided via the local network to middleware, the middleware managing the instrument.

18. The non-transitory computer readable medium of claim 17, wherein corrective action is triggered in response to the response.

19. The non-transitory computer readable medium of claim 17, further comprising: receiving an updated set of rules from the cloud-based QC data management platform; receiving additional test result data for the instrument; as well as Additional QC data is extracted from the additional test result data using the updated rule set.

20. The non-transitory computer readable medium of claim 17, further comprising: identifying a triggering event, the triggering event indicating that a connection to the cloud-based QC data management platform is unavailable; responsive to the triggering event, storing the QC data on the local network for up to a maximum amount of time; as well as In response to receiving an indication that the connection to the cloud-based QC data management platform is again available, the stored QC data is forwarded to the cloud-based QC data management platform.

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