Systems and methods for detecting potential remanufacturing and generating guidance for biomedical engineers

Abstract

In a remanufacturing regulatory compliance method, information describing maintenance performed on or scheduled to be performed on a medical device is received. One or more modified device metrics are estimated for the medical device as modified by the maintenance. The modified device metrics are based on at least the received information describing the maintenance. A determination is made whether the maintenance constitutes remanufacturing of the medical device based on a comparison of the estimated modified device metrics to corresponding original equipment manufacturer (OEM) specifications for the medical device. In response to determining that the maintenance constitutes remanufacturing, output is directed regarding modifying the maintenance to not constitute remanufacturing or regarding complying with a regulation governing remanufacturing of medical devices including the medical device.

Description

Technical Field

[0001] The following text generally covers medical equipment maintenance technology, medical imaging equipment maintenance technology, medical equipment regulatory compliance technology, and related technologies. Background Technology

[0002] In the United States, the Food and Drug Administration (FDA) distinguishes between refurbishment and remanufacturing of medical devices. Remanufacturing of a medical device significantly alters the performance, safety specifications, or intended use of the finished device. In contrast, refurbishment aims to return a medical device to the safety and performance specifications established by the original equipment manufacturer (OEM) and to meet its original intended use.

[0003] The distinction between repair and remanufacturing can impact the regulatory responsibility of medical device owners / operators. Assuming the original medical device is FDA-approved, repair merely restores the device to its original FDA-approved state, and therefore may not be subject to FDA oversight. In contrast, remanufacturing can impart significantly new and / or different performance characteristics to a medical device, which in some instances could subject remanufactured devices to additional FDA oversight. The distinction between repair and remanufacturing is also relevant to the users of the medical device, as it can affect the device's performance or functionality.

[0004] Service engineers and biomedical engineers (biomedical technicians) receive little guidance on whether their work constitutes repair or remanufacturing. For example, during the repair of medical devices, parts may be replaced with non-OEM parts, which may or may not bring repair activities into remanufacturing. Similarly, activities involving the installation and / or upgrading of software may or may not constitute remanufacturing.

[0005] Other jurisdictions may also distinguish between repair and remanufacturing, although different terminology may be used and regulatory frameworks may have different granularities. For example, in the European Union (EU), medical devices are regulated by member states, sometimes utilizing inputs from the EU level. Typically, the appropriate regulatory body (e.g., the FDA in the US) approves medical devices, such as those manufactured and sold by OEMs, for use by patients. Therefore, it may be necessary to distinguish between repair, which restores a medical device to its already approved OEM design and capabilities, and remanufacturing, which substantially modifies the design and / or capabilities of a medical device in a manner that extends beyond the scope of the OEM's regulatory approval for medical devices, and thus may involve different regulatory compliance requirements.

[0006] The following improvements are disclosed to overcome these and other issues. Summary of the Invention

[0007] In one aspect, a non-transient computer-readable medium is disclosed, storing: a database storing multiple specifications for multiple medical devices; and instructions executable by at least one electronic processor to perform a remanufacturing regulatory compliance method, the remanufacturing regulatory compliance method comprising: receiving information describing maintenance performed on or planned to be performed on a medical device; determining whether the maintenance constitutes remanufacturing of the medical device based on a comparison of the received information describing the maintenance with specifications of the medical device retrieved from the database as the object of the maintenance; and outputting guidance for resolving the determined remanufacturing in response to determining that the maintenance constitutes remanufacturing. In some embodiments, the guidance may include guidance on modifying the maintenance to not constitute remanufacturing.

[0008] In another aspect, a remanufacturing regulatory compliance method is disclosed. The method includes: receiving information describing maintenance performed on or planned to be performed on a medical device; estimating one or more modified device metrics of the medical device modified by the maintenance, based at least on the received information describing the maintenance; determining whether the maintenance constitutes remanufacturing of the medical device based on a comparison of the estimated modified device metrics with the corresponding original equipment manufacturer (OEM) specification of the medical device; and, in response to determining that the maintenance constitutes remanufacturing, outputting guidance on modifying the maintenance to not constitute remanufacturing or guidance on complying with regulations governing the remanufacturing of medical devices including the medical device.

[0009] On another front, a remanufacturing regulatory compliance device is disclosed, comprising: a hardware processor programmed to execute a remanufacturing regulatory compliance method, the remanufacturing regulatory compliance method comprising: receiving information describing a modification or planned modification of a medical device, the modification or planned modification including replacing OEM parts of the medical device with non-original equipment manufacturer (OEM) parts or installing non-original equipment manufacturer (non-OEM) software updates or additions; estimating one or more modified device metrics of the medical device using the modification or planned modification described by the received information; determining whether the modification or planned modification constitutes remanufacturing of the medical device based on a comparison of the estimated one or more modified device metrics with a corresponding OEM specification of the medical device extracted from test data, the test data being used to obtain regulatory approval for the medical device; and, in response to determining that the modification or planned modification constitutes remanufacturing, outputting guidance on revising the modification or planned modification to not constitute remanufacturing or guidance on complying with regulations governing the remanufacturing of medical devices including the medical device.

[0010] One advantage is that it distinguishes between the repair process and the remanufacturing process of medical equipment.

[0011] Another advantage is that it trains service engineers and biomedical engineers in the repair and remanufacturing processes of medical devices.

[0012] Another advantage is that it helps to comply with regulatory requirements when performing maintenance on medical devices.

[0013] Another advantage is that it provides personalized guidance on such regulatory compliance for specific maintenance tasks.

[0014] A given embodiment may provide zero, one, two, more, or all of the aforementioned advantages, and / or may provide other advantages that will become apparent to those skilled in the art upon reading and understanding this disclosure. Attached Figure Description

[0015] This disclosure can take the form of various components and component arrangements, as well as various steps and step arrangements. The accompanying drawings are for illustrative purposes only and should not be construed as limiting this disclosure.

[0016] Figure 1 The diagram illustrates a medical device maintenance guidance device according to the present disclosure.

[0017] Figure 2 The diagram illustrates the use Figure 1 An embodiment of a medical device maintenance guidance method.

[0018] Figure 3 The diagram illustrates... Figure 1 An embodiment of a module for guiding medical devices. Detailed Implementation

[0019] The following pertains to maintenance performed on medical devices that have been approved by regulatory authorities for use with patients in their original sale or leased condition. As used herein, maintenance operations may constitute repair, renewal, or upgrade of the medical device. The systems and methods disclosed herein advantageously provide service engineers, biomedical technicians, or other maintenance personnel with guidance on whether maintenance operations performed on medical devices constitute repair or remanufacturing. For this purpose, OEM specifications for medical devices published by the Original Equipment Manufacturer (OEM) are employed. For example, OEM specifications may include information (or a summary thereof) provided to one or more regulatory authorities for approval of the use of the medical device with medical patients. OEM specifications may be generated or derived from verification or validation tests performed on prototypes of the medical device, numerical simulations of the performance of the medical device design, and / or other types of empirical or other supporting data. By way of some non-limiting illustrative examples, OEM specifications may include specifications such as minimum image quality metrics (for medical imaging devices), airflow characteristics of mechanical ventilators (e.g., maximum deliverable flow rate, maximum deliverable pressure, etc.), and patient data acquisition characteristics (e.g., vital sign sampling rate, digital resolution of vital sign samples, etc.) in the case of patient monitoring devices. OEM specifications may also include operating rules, such as minimum air gaps around the medical device to provide adequate ventilation, or specifications on how the medical device should be electrically connected and / or grounded, or specifications that a component of the medical device must not come into contact with the patient (e.g., an electrical insulation barrier must be provided to ensure that high-voltage components cannot come into contact with the patient). Therefore, the OEM specifications of medical devices sold (or leased) serve as a standard for determining whether maintenance procedures would likely be considered a valid alternative to repair or remanufacturing by regulatory authorities.

[0020] As used herein, the term "repair" (and its variations) refers to the performance of maintenance on a medical device that does not extend the medical device beyond its OEM specifications (making the maintenance unlikely to affect its regulatory approval). In some illustrative examples, the jurisdiction is the United States, the regulatory body is the Food and Drug Administration (FDA), the approved medical device is an FDA-approved medical device, and the OEM specifications are provided to the FDA to obtain FDA approval for the medical device, or the OEM specifications are a summary of or derived from validation or verification data provided to the FDA upon obtaining FDA approval. As an example of the latter, if the validation or verification data provided to the FDA demonstrates that the medical device meets a specific performance level (e.g., in the case of a medical imaging device, a specific achievable image resolution and other image quality characteristics), the demonstrated performance level can be part of the OEM specifications. In other countries or jurisdictions, the regulatory body may differ (e.g., in the case of an EU member state, a member-level regulatory body), and the approved medical device is a medical device approved by that regulatory body. In cases where medical devices are used in different jurisdictions, the same OEM specifications can be applied across jurisdictions (e.g., the most stringent OEM specifications in any jurisdiction can be issued by the OEM), or different OEM specifications can be applied in different jurisdictions where assessments for repair or remanufacturing are being conducted to reflect the different regulatory standards in the different jurisdictions.

[0021] If a medical device continues to meet OEM specifications, it is considered to have been repaired. This is because meeting these OEM specifications allows the repaired medical device to continue to have the regulatory approvals obtained for the original sale or lease of the medical device based on those OEM specifications. This is a consequence of servicing a medical device or simply restoring it to its original OEM specifications. Therefore, repairs are not expected to require regulatory authorization or regulatory compliance actions to ensure that the repaired medical device remains regulatory compliant for use with a patient when performing medical functions.

[0022] Unlike repair, maintenance operations that remove a medical device from its OEM specifications may constitute remanufacturing. This is because OEM specifications are the basis for regulatory approval (or derived from validation or verification data used to obtain regulatory approval), and therefore, maintenance operations that take the device outside those OEM specifications may take the medical device outside the scope of its regulatory approval. In this case, the regulatory approvals obtained for the medical device at the time of its original sale or lease may not continue to apply to the remanufactured medical device. Therefore, remanufacturing may require regulatory authorization and / or may require certain regulatory compliance actions to ensure that the remanufactured medical device remains regulatory compliant for use with a patient when performing medical functions.

[0023] The distinction between repair and remanufacturing is also relevant to the users of medical devices, as remanufacturing can affect the performance or functionality of the device. For example, remanufacturing a medical imaging device may reduce the image resolution of medical images acquired by the device, or remanufacturing a mechanical ventilator may remove certain functions of the ventilator (e.g., by removing its ability to perform in certain ventilation modes).

[0024] Therefore, the disclosed apparatus and equipment for providing guidance on whether a maintenance operation is repair or remanufacturing offers a data-driven and physically feasible method for conducting this assessment. Thus, the disclosed method addresses a significant challenge for service engineers, biomedical technicians, or other maintenance personnel—namely, the difficulty in distinguishing between repair and remanufacturing, especially for service engineers who (typically) lack specialized training in regulatory administration and / or may be unfamiliar with OEM expectations regarding the performance of medical devices. This guidance can be useful for repair personnel under pressure to return medical devices to service but who may lack the knowledge to determine whether the maintenance performed to do so falls within the scope of tests conducted using regulatory declarations.

[0025] The following discloses a system for evaluating maintenance actions to determine whether they can actually constitute remanufacturing. In doing so, OEM specifications (e.g., those provided for regulatory approval, or OEM specifications derived from test data provided to regulators upon obtaining such approval) are used to conduct the evaluation. If the action is determined to be remanufacturing, the system provides guidance on appropriate regulatory compliance actions that should be taken. These compliance actions may include, for example, submitting appropriate FDA and / or other regulatory documentation, checking whether the service engineer is working on behalf of a certified remanufacturer, or not proceeding with the action (e.g., ordering OEM parts instead of using available non-OEM parts whose installation would constitute remanufacturing).

[0026] To this end, the disclosed system includes a conversion / quantification module for generating measurable metrics that produce OEM specifications. For hardware, this can include metrics such as whether a part comes into contact with the human body, various performance metrics of the medical device, various safety metrics, etc. Measurable metrics can also take into account the interrelationships of parts or components of the medical device. Parts or components may appear equivalent in isolation, but can cause problems during system integration. This is especially true for software, which is why software modifications (including loading any third-party software onto a medical device) can constitute remanufacturing.

[0027] As an example of the operation of the disclosed system, an OEM magnetic field gradient coil used in a medical device, serving as a magnetic resonance imaging (MRI) scanner (in this example), has a peak gradient intensity specification. A suspicious activity detector monitors maintenance actions performed on the MRI scanner (e.g., by monitoring a parts ordering system or service logs) to detect actions that could potentially veer from repair to remanufacturing. When a suspicious action is detected, a relevant measurable metric quantifying the OEM specification is determined for that action (e.g., for a non-OEM replacement part), and if the determined metric is a significant change from the OEM specification, this is identified as a possible remanufacturing. The metric quantifying the OEM specification can be calculated through simulation or determined through natural language processing (NLP) or other analysis of the non-OEM part's documentation (e.g., the non-OEM gradient coil should already have specifications including its peak gradient intensity listed). If the action is determined to be likely for remanufacturing, a generation module then generates appropriate recommendations for service engineers or biomedical technicians to ensure regulatory compliance.

[0028] In some non-limiting illustrative examples, the output of the guidance may, for example, include an indication of changes in metrics related to the OEM specifications of the medical device. The output guidance may also include recommendations for one or more possible methods to avoid such changes in metrics due to maintenance, or recommendations for one or more possible methods to minimize changes such that maintenance is considered repair rather than remanufacturing.

[0029] In the case of new software or software upgrades, calculating measurable metrics for evaluating repair and remanufacturing can be difficult or impossible. In some embodiments, the identification of potential remanufacturing may be based on categories; for example, certain categories of software that affect image acquisition speed, image resolution, or other medical-related outputs of a medical device, or that constitute control software affecting the mechanics of a medical device, may qualify as remanufacturing; while antivirus software and other types of software that do not affect medical operation are unlikely to qualify as remanufacturing. However, in other embodiments, the evaluation may have a stronger tendency to classify software upgrades or modifications as remanufacturing. For example, the evaluation may distinguish between modified / third-party software and tested and approved patches. The introduction of new security software may have significant performance problems on the system. Modifications to security software may introduce problems into the system and cause it to malfunction. Therefore, in some embodiments, the evaluation may classify such security upgrades or additions as potential remanufacturing.

[0030] In the disclosed optional aspects, maintenance is identified in a database of previous maintenance actions that are suspected of being remanufactured. Any of these actions performed at any time are automatically flagged as suspicious. However, since the assessment of repair versus remanufacturing can depend on many factors (such as, for example, a system with non-OEM parts installed), relevant measurable metrics are calculated for each case to determine whether a given action is likely to be remanufactured. To provide a case-based assessment, in some embodiments, log files of the medical device and fault-finding trees from the service manual are analyzed to determine the most likely root cause of the problem, and corresponding possible repair actions can be analyzed to determine whether a repair action could have taken the medical device outside of OEM specifications.

[0031] In another disclosed optional aspect, the performance of the medical device can be monitored after a maintenance action is performed, for example, by monitoring the machine logs of the medical device. If the monitoring determines that the action has resulted in the medical device exhibiting performance outside of OEM specifications, the action can be identified as remanufacturing, and appropriate guidance can be provided to retrospectively ensure regulatory compliance.

[0032] refer to Figure 1 This illustration shows an illustrative apparatus 10 for guiding the maintenance of medical device 12. For example, medical device 12 may include an illustrative medical imaging device 12 (also referred to as a medical device, imaging apparatus, imaging scanner, or variations thereof), which may be a magnetic resonance imaging (MRI) scanner, a computed tomography (CT) scanner, a positron emission tomography (PET) scanner, a gamma camera for performing single-photon emission computed tomography (SPECT), an interventional radiology (IR) device, an X-ray device, an image-guided therapy (IGT) device, an ultrasound (US) device, etc. Although described herein as an imaging device, medical device 12 may also be any other suitable medical device used with a patient to perform medical functions such as diagnosis and / or treatment, such as a patient monitor, radiation therapy device, mechanical ventilator, etc.

[0033] Electronic processing device 18, such as a workstation computer or more generally a computer, or a smart device (e.g., a cellular phone (“phone”), a smart tablet, etc.), can be operated by a service engineer (SE). Electronic processing device 18 may also include a server computer or multiple server computers, which may be interconnected, for example, to form a server cluster, cloud computing resources, etc., to perform more complex computing tasks. Electronic processing device 18 includes typical components such as an electronic processor 20 (e.g., a microprocessor), at least one user input device (e.g., a mouse, keyboard, trackball, etc.) 22, and a display device 24 (e.g., an LCD display, a plasma display, a cathode ray tube display, etc.). In some embodiments, display device 24 may be a component separate from electronic processing device 18, or may include two or more display devices.

[0034] Electronic processor 20 is operatively connected to one or more non-transient storage media 26. By way of non-limiting illustrative example, non-transient storage media 26 may include one or more of the following: a disk, RAID, or other magnetic storage media; a solid-state drive, a flash drive, an electrically erasable read-only memory (EEROM), or other electronic storage; an optical disk or other optical storage device; various combinations thereof; and may be, for example, a network storage device, an internal hard disk drive of workstation 18, various combinations thereof, etc. It should be understood that any reference herein to one or more non-transient media 26 should be interpreted broadly to cover a single medium or multiple media of the same or different types. Similarly, electronic processor 20 may be embodied as a single electronic processor or two or more electronic processors. Non-transient storage media 26 stores instructions executable by at least one electronic processor 20. Instructions include instructions for generating a visualization of a graphical user interface (GUI) 28 for display on display device 24.

[0035] Electronic processing device 18 also includes a database 30 storing multiple OEM specifications 32 of multiple medical devices 12 (in Figure 1(Shown as server computer) communication. For example, OEM specification 32 may include OEM specifications such as the maximum slew rate of the gradient coil, physical dimensions, whether the component can contact the patient, etc. It should be understood that the number of specifications 32 in database 30 may be large, for example, tens of thousands, hundreds of thousands or more, and in many cases, a search may return tens of thousands (or more) specifications 32. For example, different OEM specifications may be stored for different models or configurations of the same medical device, different OEM specifications may be stored for different regulatory jurisdictions, and so on. It should be understood that OEM specifications 32 may be stored in various representations, such as OEM specifications being stored as a set of quantitative metrics for assessing whether a given medical device meets OEM specifications. In some embodiments, database 30 also stores information about previously performed maintenance on the medical device, which is annotated regarding whether the maintenance was determined to be repair or remanufacturing. Database 30 also includes, or has access to, medical device maintenance information 34 regarding maintenance performed on medical device 12 (and generally related to maintenance performed on other medical devices in hospitals, radiology laboratories, etc.). The medical device maintenance information 34 may include, for example, purchase records of components purchased for installation in the medical device 12 (e.g., purchase records may constitute a parts ordering system, parts inventory, etc., or be extracted from or derived from a parts ordering system, parts inventory, etc.), service records of the medical device 12, etc. In cases where components of the medical device 12 are replaced with non-OEM parts, the medical device maintenance information 34 may include, for example, specifications of the non-OEM replacement parts obtained from the internet (e.g., by accessing a manual for the non-OEM replacement parts available on the supplier's website). In some cases, the non-OEM replacement parts may include QR codes or barcodes, which can be scanned using a mobile phone or similar device to automatically retrieve the specification information of the non-OEM parts.

[0036] The apparatus 10 is configured as described above to perform a remanufacturing regulatory compliance method or process 100. A non-transient storage medium 26 stores instructions that can be read and executed by at least one electronic processor 20 to perform the disclosed operations, including performing the maintenance assessment method or process 100. In some examples, method 100 may be performed at least partially by cloud processing.

[0037] refer to Figure 2 And continue to refer to Figure 1An illustrative embodiment of an example of method 100 is shown schematically as a flowchart. At operation 102, information 34 describing the medical device 12 is received from database 30, and in operation 103, maintenance operations to be performed on the medical device 12 are determined based on this information. In a retrospective case where maintenance operations have already been performed, the information obtained in operation 102 may include the medical device's service log, which directly states the maintenance operations performed. In the anticipated case, maintenance planned to be performed on the medical device 12 (or information sufficient to determine planned maintenance) is retrieved from database 30 and received at electronic processing device 18. In one example, the service engineer enters the planned maintenance operations into the service log before performing them, and this is retrieved in operation 103. In other embodiments, when the service engineer enters descriptions of observed symptoms or other problems into the service log, this information (possibly along with log information automatically generated from the medical device 12) is extracted and analyzed to determine possible maintenance operations, for example, using a fault-finding tree. In some examples, the maintenance operation determined at operation 103 may include replacing the original equipment manufacturer (OEM) part of medical device 12 with a non-OEM part or installing a non-OEM software update or add-on. In this example, the information received at operation 102 may include specification information for replacing the non-OEM part. Such information may be retrieved from the Internet, for example, using a search query automatically generated based on the non-OEM part manufacturer and part number information, or semi-automatically obtained by scanning a QR code or barcode set on the non-OEM part. If the necessary information cannot be obtained in such an automatic or semi-automatic manner, the user may be required to manually enter relevant information about the non-OEM part to complete operation 102. The relevant information generally corresponds to similar information about medical device 12 as set forth in Medical Device Specification 32, provided that the information relates to regulatory approval for the medical device. As an illustrative example, in the case of a medical imaging device, the relevant information may include information such as achievable image resolution and other image quality characteristics, imaging field of view, maximum magnetic field applied to the patient (in the case of MRI), and whether the part is in contact with the patient.

[0038] At operation 104, the electronic processing device 18 determines whether the identified maintenance operation constitutes a remanufacturing of the medical device 12 based on a comparison of information received in operation 102 describing the maintenance operation and its impact on the performance of the medical device 12 with the OEM specifications 32 of the medical device 12, which is the object of maintenance, retrieved from the database 30. For example, if the maintenance involves replacing an original equipment manufacturer (OEM) part of the medical device 12 with a non-OEM part, then operation 104 includes determining, based on the OEM specifications 32 of the medical device 12, that the OEM part never directly contacts the patient during the clinical use of the medical device 12, and if it is determined that the non-OEM part can directly contact the patient during the clinical use of the medical device 12, such as by replacing the OEM part with a non-OEM part, then the maintenance constitutes a remanufacturing of the medical device 12. (This may be the case, for example, if the OEM part is a high-voltage component with an insulating housing to ensure that the patient is not exposed to high voltage; while the non-OEM part lacks such a housing). In another example, if the maintenance is the installation of a non-OEM software update or add-on, then determination operation 104 includes assigning a category to the software update based on the functionality of the non-OEM software update or add-on, and determining whether the maintenance constitutes remanufacturing of the medical device 12 based on the assigned category. In yet another example, information about previously performed maintenance of the medical device is retrieved from database 30, which is annotated regarding whether the maintenance was determined to be remanufacturing, and determination operation 104 includes whether the maintenance matches one of the stored previously performed remanufacturing maintenance actions.

[0039] To perform determination operation 104, electronic processing device 18 is configured to generate one or more OEM specification metrics according to OEM specification 32 of the medical device 12, which is the object of maintenance. As previously described, OEM specification 32 includes test data used to obtain regulatory approval for the medical device 12 or derived from such test data, and thus serves as a data-driven quantitative mechanism for assessing whether the maintenance operation constitutes repair or remanufacturing. For example, the metrics may meet predetermined guidelines from regulatory agencies (i.e., the FDA) and may include one or more of the following: whether replacement parts of the medical device 12 come into contact with the human body, performance metrics of the medical device, and safety metrics.

[0040] One or more modified device metrics of the medical device 12, such as those modified by maintenance, are estimated based at least on information describing maintenance received from receiving operation 102. To estimate the modified device metrics, a simulation process is performed on the medical device 12, such as those modified by maintenance. The deviations of the one or more modified device metrics from one or more OEM specification metrics are then determined. Electronic processing device 18 is configured to determine that maintenance constitutes remanufacturing if the deviation exceeds a predetermined remanufacturing threshold.

[0041] At operation 106, in response to determining that maintenance constitutes remanufacturing, guidance 38 regarding resolving the determined remanufacturing is output on display device 24. In one example, guidance 38 is guidance on complying with regulations governing the remanufacturing of medical devices including medical device 12. In another example, guidance 38 includes guidance on modifying the repair to not constitute remanufacturing. Optionally, the guidance may be logged in the service log of medical device 12 for tracking future failures, and / or may be reported to the intended recipient, such as a designated regulatory compliance officer. The process then terminates at terminal 108.

[0042] On the other hand, in response to determining that maintenance constitutes repair, the process flows directly to terminal 108. Alternatively, although not shown, it should be expected that, in response to determining that maintenance constitutes repair, an indication of the effect can be output. Example

[0043] The apparatus 10 and method 100 are described in more detail below. The apparatus 10 is configured to convert regulatory or quality management documents into measurable assessments, detect suspicious maintenance activities (i.e., maintenance activities suspected of constituting remanufacturing because they would cause the medical device to go beyond OEM specifications), estimate the scale of variation, and generate guidance and / or questions that require further input from the user.

[0044] Figure 3 Another example of device 10 is shown. For example... Figure 3 As shown, device 10 includes a first module 40 implemented in electronic processing device 18. The first module 40 is configured to convert relevant guidance items into assessments. To this end, the first module 40 is configured to retrieve textual information about remanufacturing from online resources or local knowledge bases and then convert them into measurable assessments, for example, from new guidance on how to determine performance changes to performance metrics, or from hospital quality regulations to quality metrics. Baseline performance can come from Specification 32 and / or performance testing, as well as manual input. The first module 40 retrieves relevant regulatory requirements based on the client's legal location. Resources for such regulatory requirements can come from authorized entities such as the FDA or the hospital's own quality management system. These requirements include compliance with guidelines for remanufacturing, repair, refurbishment, remarketing, etc., as well as requirements for other processes.

[0045] As described in this article, the FDA is described as the primary external regulatory body. The FDA publishes guidance, white papers, and workbooks on the remanufacturing of medical devices over time. These documents define remanufacturing and repair (i.e., maintenance), and include a list of heuristics, examples, and flowcharts to help distinguish between maintenance actions and remanufacturing. Various techniques can be used to extract assessments from these documents to determine remanufacturing actions. Examples of assessments could include, for instance, direct contact with the human body, performance, safety, dimensions, operational malfunctions, etc.

[0046] In addition, the first module 40 retrieves documents (e.g., specifications, manuals, training materials) from the OEM of the medical device 12, wherein it extracts relevant OEM specifications from test data used to obtain regulatory approval for the medical device. Furthermore, the first module 40 performs a process of finding baseline performance or test performance from documents such as training materials.

[0047] For each component, the output of the first module 40 can be a metric conforming to the OEM specifications of the medical device, as an evaluation list with measurable metrics and baseline measurement results (or indications). In one example, for a gradient coil, performance evaluation metrics could include slew rate, slice thickness, spatial resolution, etc., as well as binary metrics indicating whether the gradient coil can be in direct contact with a patient. For each metric, a threshold is defined for what would be considered a significant change (if it is numerical); or, in the case of binary metrics, an answer conforming to the OEM specifications is defined (e.g., an OEM performance metric specifying that the gradient coil should not be able to contact a patient). Baseline dimensions are retrieved from OEM specification 32. Table 1 shows examples of gradient coil evaluations and metrics. Table 1

[0048] In addition, Module 40 takes into account local market and hospital regulatory requirements, translating them into assessments and metrics. Thresholds will be defined by the relevant regulatory body; if not, they can be measured through pilot testing or by analyzing usage data.

[0049] The first module 40 is configured to, for example, use Natural Language Processing (NLP) to convert the textual guidelines into an evaluation. The NLP can extract a list of constraints that the remanufactured parts should be compared to. The constraints will include a set of performance metrics, some of which are associated with values ​​reported in the guidelines. For others, specification values ​​can be evaluated from historical or third-party data according to the primary implementation. The NLP will be configured for dedicated Named Entity Recognition (NER) (see, for example, Puccetti, G., Chiarello, F., & Fantoni, G. (2021). A simple and fast method for extracting named entity context from patents. An expert system 184 (0957-4174) with an application and a Relation Extraction (RE) processor (see, for example, Korger, A., & Baumeister, J. (2021). Rule-based semantic relation extraction from regulatory documents. Lwda2021. Munich). This identifies portions of text representing specific entities, associates them with entity types from a predefined set, and places them into relations, for example, associating performance metrics with relevant values.

[0050] Using the extracted and structured information, a set of constraints to be automatically checked can be created. Similar methods can be designed to extract the same information from documents containing metrics in text tables. Specialized image processing and OCR (Optical Character Recognition) can be applied to convert the tables into corresponding text representations, and an NLP engine trained for this purpose will extract entities and their relationships.

[0051] like Figure 3 As shown, the device 10 includes a second module 42 implemented in the electronic processing device 18. The second module 42 is configured to detect suspicious maintenance activities that may become remanufacturing based on medical device maintenance information 34. This information 34 can be obtained, for example, through self-reporting (when a biomedical engineer (“biomedical technician”) is using a third-party component), QR scanning, software detection, or by using sensors (sensing that the part is not from the OEM).

[0052] Suspicious hardware maintenance activities that may become remanufacturing can be detected through QR scanning of parts and the use of sensors on the device (e.g., sensing that the part is not from the OEM). It can utilize part information recorded in a parts database, purchase records, quotes, or even CAD / 3D models of the parts. Once a non-OEM hardware part is detected, it is considered a potential remanufacturing activity.

[0053] For software, Module 42 will remove assessments that are not applicable to software, such as those involving direct human contact. Additionally, it can detect the type of software activity a user is performing. The FDA has guidance that certain types of software activities may not be considered remanufacturing. Some examples may include implementing updates and upgrades provided by the OEM, running software-based hardware diagnostics, assessing for viruses, malware, and other cybersecurity-related issues, reinstalling OEM software to restore original performance and security specifications, collecting system logs, etc.

[0054] To understand whether software might constitute remanufacturing (i.e., the medical device is expected to be taken outside of OEM specifications), relevant documents regarding software releases / updates, such as software specifications, release notes, manuals, etc., can be retrieved. For example, in a non-limiting illustrative example, the software specification might state that new features have been added for detecting a new virus, ABC. Module 42 would attempt to match this statement with one of the software activities in guidelines extracted from regulatory documents and find that it meets a guideline (which may not be considered remanufacturing) for assessing virus, malware, and other cybersecurity-related issues. In another non-limiting illustrative example, the software specification document indicates that bug fixes on image post-processing have been added to the update. This statement does not match any known guidelines in the above list that are generally not considered remanufacturing and can therefore be considered suspicious (i.e., potentially remanufacturing). Module 42 then applies predefined rules (e.g., rules specifying image post-processing versus image quality mapping) or uses NLP to determine that the bug fixes are related to image quality and thus suspect a quality change defined by the hospital. In other embodiments, the analysis of the software can be designed with a stronger tendency to classify software upgrades or revisions as remanufacturing. For example, any third-party software that is not on the list of tested and approved software patches can be considered suspicious (i.e., possibly remanufactured).

[0055] The output of the second module 42 is a binary option (e.g., "yes" (it is a suspected remanufacturing activity) or "no" (it is not a suspected remanufacturing activity)). In some examples, it has a multiple output that is monitored when the magnitude of the changes introduced by the software cannot be determined before actual use.

[0056] like Figure 3As shown, device 10 includes a third module 44 implemented in electronic processing device 18. The third module 44 is configured to estimate the scale of change in maintenance. This may include using machine logs, parts manuals, software release notes, and evaluation results to estimate whether it is a significant change in the evaluation metric; in the case of using third-party parts, the OEM may provide API features to run simulations with the third-party parts to test for changes / deviations. Alternatively, performance changes may be compared to previous repair actions on the same parts. For each factor, i.e., performance, safety, etc., there is a list of corresponding metrics. Performance changes may be compared to previous repair actions on the same parts or provided by the OEM. Safety indicators may be based on risk assessments or historical records.

[0057] like Figure 3 As shown, device 10 includes a fourth module 46 implemented in electronic processing device 18. The fourth module 46 is configured to generate guidance 38 for the user. In some examples, when changes can be estimated, guidance 38 may guide the user to comply with FDA or other regulatory processes (i.e., FDA, local government, and hospital QM (quality management) processes) or to adopt alternative options for repair (rather than remanufacturing). In the absence of data, the fourth module 46 may generate questions to guide the user to perform a risk assessment or other risk evaluation (…). For example, after reinstallation, the performance metric P1 value between x and y did not change significantly. Alternatively, after installing the part, image quality tests showed a 50% reduction compared to before the replacement. When answers cannot be obtained automatically, Module 46 generates questions to guide the user to provide input, such as risk assessments. Another possibility is that when remanufacturing is deemed possible, suggestions on possible remedies can be offered. This could be issuing a service call to the OEM or authorized remanufacturer, reversing some or all steps, or taking corrective actions.

[0058] In the first example, for hardware maintenance, the gradient coil of the magnetic resonance (MR) system needs to be replaced. The biomedical technician searches for a non-OEM replacement gradient coil and decides to use the non-OEM component due to timing constraints. According to module 42, when a third-party service company installs its gradient coil into the MR system, device 10 detects that the gradient coil is non-OEM. Method 100 requires new dimensional data from the replacement gradient coil, which the biomedical technician inputs. It is concluded that there is no significant dimensional change compared to OEM specifications. After a test run, the system collects performance data (see Table 2) and compares it to performance from the OEM, concluding that the peak gradient intensity and image performance (e.g., spatial resolution) are significantly different. While this example analyzes a non-OEM gradient coil in isolation, the analysis can also consider whether the combination of a non-OEM gradient coil with other components of the MRI scanner could potentially take the MRI scanner outside of OEM specifications and thus constitute remanufacturing. For example, the magnetic field applied to the patient is a combination of the gradient field applied by the gradient coil and the static (BO) magnetic field applied by the superconducting main magnet. Therefore, gradient coils installed in MRI scanners with lower-strength superconducting magnets can be considered repaired, but installed in MRI scanners with higher-strength superconducting magnets can be considered remanufactured. Table 2 shows the output from tests run after installing third-party gradient coils.

[0059] Module 46 instructs the biomedical technician as Guide 38: “The replacement gradient coil may be considered remanufactured as defined by the FDA because the peak gradient intensity is 20% higher than the OEM specification.” Furthermore, Guide 38 guides the biomedical technician on how to comply with the FDA and document the replacement. In a contemplated embodiment, the aforementioned analysis is performed prior to gradient coil installation, triggered, for example, by entering the planned gradient coil replacement into the service log, or by detecting an order for a non-OEM gradient coil via a linked parts ordering system. The determination of potential remanufacturing can also automatically trigger an inventory check on the OEM parts ordering system to determine if a suitable OEM gradient coil is available, and this can be advised to the biomedical technician as a way to ensure maintenance does not constitute remanufacturing. If no suitable OEM gradient coil is available, the system can recommend to the biomedical technician that they request regulatory compliance certification from the seller of the non-OEM gradient coil before purchasing or installing it.

[0060] In the second example, for software maintenance, the OEM can provide a machine learning model for more advanced image analysis. The machine learning model is customized to run on custom hardware. The hospital has the same imaging equipment; therefore, the hardware has not changed. When the software is upgraded, the new machine learning model is detected in the package, and it requires a different hardware configuration. Method 100 guides biomedical technicians to perform tests using the new machine learning model. The outputs are listed in Table 3. Table 3 shows the output from tests run after installing third-party machine learning models.

[0061] In this scenario, there are no significant performance changes compared to the OEM specification. However, the reduction in scan speed compared to the OEM specification is significant, meaning that adding a machine learning model will slow down image throughput (i.e., the scan speed in the table). Therefore, the system can recommend to biomedical technicians that the new machine learning model should not be installed, or take other actions, such as reconfiguring the machine learning module to operate offline or on a cloud server, to reduce its impact on scan speed. Method 100 retrieves relevant quality management documents from the hospital and guides biomedical technicians through hospital procedures.

[0062] In the third example, over time, decision-making paths and equipment are captured in the learning database 30. It records all metrics and results so they can be used for later queries. Engineers can query by providing information about parts and equipment, and the database can then match it with similar cases. If an engineer has previously used a third-party part A on the same equipment identified as remanufacturing, this could be considered a point of suspicion for remanufacturing if no new guidance is found from the regulatory body. However, if a change occurs in metric (X), such as a different part size than before, method 100 will reassess the scale of the change and make new decisions and guidance accordingly.

[0063] In the fourth example, after the corrective action is completed, method 100 will maintain an estimate of the scale of change, regardless of whether it is remanufacturing or repair. If the estimate of the change becomes significant, feedback should be given to the engineer regarding the steps he / she should not have performed (or should have performed differently) and the reasons (measured metrics); furthermore, a root cause analysis is performed to identify the steps that may have led to this change. Because the service record database records the roles of the person performing the corrective action, it knows whether the engineer is a certified remanufacturer, which can help determine responsibility and educate on potential future issues.

[0064] In the fifth example, the repair type could generate a series of questions or images to help determine if the maintenance steps taken were correct. This can be provided to the hospital's risk department to ensure quality control. For example, if the maintenance operation involved wiring, a series of photos could be presented to the risk manager showing the correct and incorrect ways the system should be inspected after the repair. For instance, if wiring is exposed or there are connections, kinks, or tears in the wiring insulation or protective casing, this should alert the risk manager to a problem with how the repair was done, which could take the system outside of OEM specifications and / or create risks. In another example, if the maintenance operation involved replacing radiation shielding, questions for the risk compliance manager could include inquiring about the presence of any holes, cracks, tears, or clumps of tape, as such damage could increase radiation risks not considered in the specifications. In such a case, the problem might not be remanufacturing, but rather the quality of the parts used that could take the system outside of OEM specifications.

[0065] In other anticipated scenarios, the system can request images of the replaced parts and compare them using an image matching algorithm against a library of reference images showing how the parts are correctly assembled. This helps risk compliance managers who are not trained on the system and / or cannot see the replaced parts. The risk manager can then use the comparison output for review, along with biomedical analysis, to determine why appropriate steps were not taken.

[0066] This disclosure has been described with reference to preferred embodiments. Modifications and variations may arise in others after reading and understanding the foregoing detailed description. Exemplary embodiments are intended to be constructed to include all such modifications and variations, provided they fall within the scope of the appended claims or their equivalents.

Claims

1. A non-transient computer-readable medium (26) storing: Database (30) that stores multiple specifications (32) for multiple medical devices (12); and Instructions, which can be executed by at least one electronic processor (20) to perform a remanufacturing regulatory compliance method (100), said remanufacturing regulatory compliance method comprising: Receive information (34) describing maintenance performed on or planned to be performed on the medical device (12); Whether the maintenance constitutes remanufacturing of the medical device is determined by comparing the received information describing the maintenance with the specifications of the medical device (12) retrieved from the database as the object of the maintenance; as well as In response to determining that the maintenance constitutes remanufacturing, a guide (38) is output for resolving the determined remanufacturing.

2. The non-transient computer-readable medium (26) according to claim 1, wherein, The specifications of the medical device (12) include specifications for the performance of the medical device.

3. The non-transient computer-readable medium (26) according to claim 1, wherein, The guidance (38) includes guidance on compliance with the following regulations: the regulations govern the remanufacturing of the medical device (12) as the object of the maintenance.

4. The non-transient computer-readable medium (26) according to claim 1, wherein, The guidance (38) includes guidance on modifying the maintenance to not constitute remanufacturing.

5. The non-transient computer-readable medium (26) according to any one of claims 1-4, wherein, The specifications of the medical device (12) are the original equipment manufacturer (OEM) specifications of the medical device, and the determination includes: One or more original OEM specification metrics are generated based on the specification (32) of the medical device (12) that is the object of the maintenance. At least based on the received information describing the maintenance (34), one or more modified device metrics of the medical device modified by the maintenance are estimated; Determine the deviation between the one or more modified device metrics and the one or more OEM specification metrics; and If the deviation exceeds a predetermined remanufacturing threshold, then the maintenance is determined to constitute remanufacturing.

6. The non-transient computer-readable medium (26) according to claim 5, wherein, Estimating the one or more modified device metrics includes: A simulation process is performed on the medical device (12) modified by the maintenance.

7. The non-transient computer-readable medium (26) according to claim 5, wherein, Generating one or more OEM specification metrics includes: By performing natural language processing (NLP) on the specification (32) of the medical device (12) that is the object of maintenance, one or more OEM specification metrics are extracted from the specification (32) of the medical device (12) that is the object of maintenance.

8. The non-transient computer-readable medium (26) according to any one of claims 5-7, wherein, The OEM specification of the medical device (12) is derived from test data, and the medical device regulatory approval is obtained based on the test data.

9. The non-transient computer-readable medium (26) according to any one of claims 1-8, wherein, The maintenance includes replacing the original equipment manufacturer (OEM) parts of the medical device (12) with non-OEM parts.

10. The non-transient computer-readable medium (26) according to claim 9, wherein, Determining whether the maintenance constitutes remanufacturing of the medical device (12) includes: Based on the specifications (32) of the medical device (12) being maintained, it is determined that the OEM component never directly contacts the patient during the clinical use of the medical device by the patient; and If it is determined that the non-OEM component can directly contact the patient during clinical use of the medical device modified by replacing the OEM component with the non-OEM component, then the maintenance is determined to constitute remanufacturing of the medical device.

11. The non-transient computer-readable medium (26) according to any one of claims 1-8, wherein, The maintenance includes installing or adding software updates from non-original equipment manufacturers (OEMs).

12. The non-transient computer-readable medium (26) according to claim 11, wherein, Determining whether the maintenance constitutes remanufacturing of the medical device (12) includes one of the following: The software update is categorized based on the features added to the non-OEM software update, and the maintenance is determined to constitute a remanufacturing of the medical device based on the categorized features. or Whether the maintenance constitutes a remanufacturing of the medical device is determined based on whether the non-OEM software update or add-on is an OEM-approved software update or add-on.

13. The non-transient computer-readable medium (26) according to any one of claims 1-12, wherein, The database (30) also stores information about previously performed maintenance on the medical device, the information being annotated regarding whether the maintenance was determined to be remanufacturing, and the method (100) further includes: Determine whether the maintenance matches one of the previously performed maintenance stored that was identified as being remanufactured.

14. A remanufacturing regulatory compliance approach (100), comprising: Receive information (34) describing maintenance performed on or planned to be performed on the medical device (12); One or more modified device metrics of the medical device modified by the maintenance are estimated, at least based on the received information describing the maintenance. Whether the maintenance constitutes remanufacturing of the medical device is determined by comparing the estimated modified device metric with the corresponding original equipment manufacturer (OEM) specification of the medical device. as well as In response to determining that the maintenance constitutes remanufacturing, output guidance (38) on modifying the maintenance to not constitute remanufacturing or guidance (38) on complying with regulations governing the remanufacturing of medical devices including the medical device (12).

15. The method (100) according to claim 14, wherein, The guidance (38) includes guidance on compliance with the following regulations: the regulations govern the remanufacturing of the medical device (12) as the object of the maintenance.

16. The method (100) according to claim 14, wherein, The guidance (38) includes guidance on modifying the maintenance to not constitute remanufacturing.

17. The method (100) according to any one of claims 14-16, wherein, The OEM specification of the medical device (12) is derived from test data used to obtain regulatory approval for the medical device.

18. The method (100) according to any one of claims 14-17, wherein, Estimating the one or more modified device metrics includes: A simulation process is performed on the medical device (12) modified by the maintenance.

19. The method (100) according to any one of claims 14-17, wherein, Receiving information (34) describing maintenance performed on or planned to be performed on the medical device (12) includes: receiving a fault lookup tree and using the fault lookup tree to predict the maintenance.

20. A remanufacturing regulatory compliance device (10), comprising: A hardware processor (20) programmed to execute a remanufacturing regulatory compliance method (100), said remanufacturing regulatory compliance method comprising: Receive information (34) describing modifications or planned modifications to the medical device (12), the modifications or planned modifications including replacing original equipment manufacturer (OEM) parts of the medical device with non-original equipment manufacturer (non-OEM) parts or installing non-original equipment manufacturer (non-OEM) software updates or additions; The modifications or planning described by the received information are used to estimate one or more modified device metrics of the medical device; A comparison of estimated one or more modified device metrics with the corresponding OEM specifications of the medical device extracted from test data determines whether the modification or planned modification constitutes remanufacturing of the medical device, the test data being used to obtain regulatory approval for the medical device; and In response to determining that the modification or planned modification constitutes remanufacturing, guidance (38) is output regarding revising the modification or planned modification to not constitute remanufacturing or guidance (38) regarding compliance with regulations governing the remanufacturing of medical devices including the medical device (12).

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