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EP4395630A1 - Systèmes et procédés d'assistance technique de systèmes de surveillance continue d'analyte et de capteur - Google Patents

Systèmes et procédés d'assistance technique de systèmes de surveillance continue d'analyte et de capteur

Info

Publication number
EP4395630A1
EP4395630A1 EP22777553.3A EP22777553A EP4395630A1 EP 4395630 A1 EP4395630 A1 EP 4395630A1 EP 22777553 A EP22777553 A EP 22777553A EP 4395630 A1 EP4395630 A1 EP 4395630A1
Authority
EP
European Patent Office
Prior art keywords
patient
processor
sensor
analyte
analyte sensor
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP22777553.3A
Other languages
German (de)
English (en)
Inventor
Caroline M. Strom
Arturo Garcia
Nicole Marie Weikert
Aarthi Mahalingam
Apurv Ullas Kamath
Nolan Rey
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dexcom Inc
Original Assignee
Dexcom Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US17/467,072 external-priority patent/US12033749B2/en
Application filed by Dexcom Inc filed Critical Dexcom Inc
Publication of EP4395630A1 publication Critical patent/EP4395630A1/fr
Pending legal-status Critical Current

Links

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue
    • A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration or pH-value ; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid or cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A61B5/0031—Implanted circuitry
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7271—Specific aspects of physiological measurement analysis
    • A61B5/7282—Event detection, e.g. detecting unique waveforms indicative of a medical condition

Definitions

  • the present disclosure relates generally to automated or semi-automated technical support of medical device systems. More particularly, the present disclosure is directed to systems, methods, apparatuses, and computer products for automated or semi-automated technical support of a continuous analyte monitoring system.
  • SMBG self-monitoring blood glucose
  • Continuous glucose monitors have been increasing in popularity as an easy way to monitor glucose levels and automatically alert the patient of glucose level events. For example, one potentially dangerous timeframe is at night because a patient’s glucose levels can fall dangerously low during sleep. As a result, continuous glucose monitors have gained popularity by providing a sensor that continuously measures glucose levels of a patient and transmits the measured glucose levels wirelessly to a display. This allows the patient or patient’s caregiver to monitor the patient’s glucose levels throughout the day and even set alarms for when glucose levels reach a predefined level or experience a defined change.
  • the pattern associated with the event indications indicates multiple consecutive event indications indicative of the sensed signals being above a maximum configured error threshold.
  • the one or more root causes comprise at least one of: a malfunction associated with the analyte sensor; high sensitivity of the analyte sensor; damage to a membrane of the patient coupled to the analyte sensor; or high moisture condition associated with the analyte sensor.
  • the pattern associated with the event indications indicates multiple consecutive event indications indicative of the sensed signals being below a minimum configured error threshold.
  • the one or more root causes comprise at least one of: compression on the analyte sensor; wound trauma at an interface between the analyte sensor and the patient; low sensor sensitivity associated with the analyte sensor; or deteriorated quality of a signal sensed by the analyte sensor.
  • determining the one or more root causes comprises determining that a difference between the one or more analyte measurements and the one or more reference analyte measurements is greater than a threshold; and wherein the one or more root causes comprise deficient sensor calibration.
  • one or more of the plurality of event indications indicate a rate of change associated with the one or more sensed signals being higher than a threshold.
  • the processor is further configured to receive one or more answers to one or more questions presented to a user, and wherein the determining of the one or more root causes is further based on the one or more answers.
  • the one or more actions comprise at least one of: indicating to a user to relocate or reorient the analyte sensor on a body of the patient; indicating to the user to change a position of the body of the patient; indicating to the user to change a diet of the patient; indicating to the user to apply a cream to an interface between the analyte sensor and the patient; indicating to the user to apply an agent to an interface between the analyte sensor and the patient; indicating to the user to have the patient digest one or more supplements to increase adhesion of the analyte sensor at the interface between the analyte sensor and the patient; indicating to the user that a specific activity has caused the one or more event indications; indicating to the user to re-calibrate the analyte sensor; indicating to the user to order a new analyte sensor for the patient; or ordering a new analyte sensor for the patient.
  • the processor is further configured to receive secondary sensor data associated with the patient, wherein the determining of the one or more root causes is further based on the secondary sensor data.
  • the one or more actions comprise at least one of: indicating to a user to uninstall and re-install the application executed by the processor; or indicating to the user to reopen the application executed by the processor.
  • FIG. 1A illustrates aspects of an example system that may be used in connection with implementing embodiments of the disclosure.
  • FIG. IB illustrates aspects of an example system that may be used in connection with implementing embodiments of the disclosure.
  • FIG. 3A illustrates aspects of an example system that may be used in connection with implementing embodiments of the disclosure.
  • FIG. 3B illustrates aspects of an example system that may be used in connection with implementing embodiments of the disclosure.
  • FIG. 4 illustrates an example architecture of an automated or semi-automated technical support system in accordance with embodiments of the present technology.
  • FIGs. 5A and 5B illustrate a flow chart of an example process to provide automated or semi-automated technical support in accordance with embodiments of the present technology.
  • FIGs. 6A and 6B illustrate aspects of example systems for automatic failure detection.
  • analyte as used herein is a broad term and is to be given its ordinary and customary meaning to a person of ordinary skill in the art (and is not to be limited to a special or customized meaning), and furthermore refers without limitation to a substance or chemical constituent in a biological fluid (for example, blood, interstitial fluid, cerebral spinal fluid, lymph fluid, urine, sweat, saliva, etc.) that can be analyzed. Analytes can include naturally occurring substances, artificial substances, metabolites, and/or reaction products. In some implementations, the analyte for measurement by the methods or devices is glucose.
  • glucose While the analyte for measurement and analysis by the devices and methods described herein is glucose, other analytes listed, but not limited to, above may be considered. Biological parameters, such as body temperature, heart rate, metabolic function, respiratory rate, and the like, may be also be considered.
  • the sensor electronics module is configured to search for and/or attempt wireless communication with a display device from a list of display devices. In some embodiments, the sensor electronics module is configured to search for and/or attempt wireless communication with a list of display devices in a predetermined and/or programmable order (e.g., grading and/or escalating), for example, wherein a failed attempt at communication with and/or alarming with a first display device triggers an attempt at communication with and/or alarming with a second display device, and so on.
  • a predetermined and/or programmable order e.g., grading and/or escalating
  • an implantable glucose sensor may be used.
  • the devices and methods described herein can be applied to any device capable of detecting a concentration of glucose and providing an output signal that represents the concentration of glucose (e.g., as a form of analyte data).
  • wireless communication protocols may be used to transmit and receive data between analyte sensor system 308 and the display device 310 via communication medium 305.
  • Such wireless protocols may be designed for use in a wireless network that is optimized for periodic and small data transmissions (that may be transmitted at low rates if necessary) to and from multiple devices in a close range (e.g., a personal area network (PAN)).
  • PAN personal area network
  • one such protocol may be optimized for periodic data transfers where transceivers may be configured to transmit data for short intervals and then enter low power modes for long intervals.
  • the protocol may have low overhead requirements both for normal data transmissions and for initially setting up communication channels (e.g., by reducing overhead) to reduce power consumption.
  • burst broadcasting schemes e.g., one way communication
  • This may eliminate overhead required for acknowledgement signals and allow for periodic transmissions that consume little power.
  • transceiver 360 may be referred to as a “dummy transceiver”, wherein transceiver 360 is configured to only transmit analyte values to display device 310 without additional processing, e.g., without generating event indications associated with the sensed signals prior to transmission. Accordingly, only processor/microprocessor 335, as opposed to both transceiver 360 and processor/microprocessor 335, may be configured to generate event indications indicating one or more errors associated with the continuous analyte monitoring system.
  • the duration of the predetermined time interval can be selected to be long enough so that analyte sensor system 308 does not consume too much power by transmitting data more frequently than needed, yet frequent enough to provide substantially real time sensor information (e.g., measured glucose values or analyte data) to display device 310 for output (e.g., via display 345) to a user. While the predetermined time interval is every five minutes in some embodiments, it is appreciated that this time interval can be varied to be any desired length of time.
  • connectivity interface 315 interfaces display device 310 to communication medium 305, such that display device 310 may be communicatively coupled to analyte sensor system 308 via communication medium 305.
  • Transceiver 320 of connectivity interface 315 may include multiple transceiver modules operable on different wireless standards. Transceiver 320 may be used to receive analyte data and associated commands and messages (e.g., event indications generated by analyte sensor system 308) from analyte sensor system 308. Additionally, connectivity interface 315 may in some cases include additional components for controlling radio and/or wired connections, such as baseband and/or Ethernet modems, audio/video codecs, and so on.
  • storage 325 may store analyte sensor application 330 that, when executed using processor 335, for example, receives input (e.g., by a conventional hard/soft key or a touch screen, voice detection, or other input mechanism), and allows a user to interact with the analyte data and related content via GUI 340, as will be described in further detail herein.
  • processor 335 may store analyte sensor application 330 that, when executed using processor 335, for example, receives input (e.g., by a conventional hard/soft key or a touch screen, voice detection, or other input mechanism), and allows a user to interact with the analyte data and related content via GUI 340, as will be described in further detail herein.
  • a display module may present (e.g., via display 345) various screens to a user, with the screens containing graphical representations of information provided by application 330.
  • application 330 may be used to display to the user an environment for viewing and interacting with various display devices that may be connectable to analyte sensor system 308, as well as with analyte sensor system 308 itself.
  • Sensor application 330 may include a native application modified with a software design kit (e.g., depending on the operating system) in order to carry out the functionalities/features described herein.
  • display device 310 also includes processor 335.
  • Processor 335 may include processor sub-modules, including, by way of example, an applications processor that interfaces with and/or controls other elements of display device 310 (e.g., connectivity interface 315, application 330, GUI 340, display 345, RTC 350, etc.).
  • Processor 335 may include a controller and/or microcontroller that provides various controls (e.g., interfaces with buttons and switches) related to device management, such as, for example, lists of available or previously paired devices, information related to measurement values, information related to network conditions (e.g., link quality and the like), information related to the timing, type, and/or structure of messaging exchanged between analyte sensor system 308 and display device 310, and so on.
  • the controller may include various controls related to the gathering of user input, such as, for example, a user’s finger print (e.g., to authorize the user’s access to data or to be used for authorization/encryption of data, including analyte data), as well as analyte data.
  • Processor 335 may include circuitry such as logic circuits, memory, a battery and power circuitry, and other circuitry drivers for periphery components and audio components.
  • Processor 335 and any sub-processors thereof may include logic circuits for receiving, processing (e.g., for performing root cause analysis, as described herein), and/or storing data received and/or input to display device 310, and data to be transmitted or delivered by display device 310.
  • Processor 335 may be coupled by a bus to display 345 as well as connectivity interface 315 and storage 325 (including application 330). Hence, processor 335 may receive and process electrical signals generated by these respective elements and thus perform various functions.
  • analyte monitors have been increasing in popularity as both a convenient and necessary way to monitor and always be aware of a user’s analyte levels.
  • the user base utilizing the above-described analyte monitoring system continues to expand, as has the volume of calls to a patient support hotline, accordingly.
  • a typical call to a patient support center entails several aspects. For example, a tech support technician typically spends 10-45 minutes on the phone diagnosing and resolving an issue for which a patient has placed a patient support call.
  • the embodiments described herein can comprise situations when the described systems or methods proactively, or as a result of an initiating request for tech support from a patient, automatically or semi-automatically identify, resolve technical issues, provide one or more appropriate notifications to affected patients, patients’ remote monitors or third parties and record the tech support issues, resolutions and associated data in appropriate databases, including regulatory compliance databases.
  • FIG. 4 illustrates an example architecture of an automated or semi-automated technical support system in accordance with embodiments of the present technology.
  • a continuous analyte sensor 402 such as a continuous glucose sensor referred to as CGM 402, for example, can be inserted in a patient (e.g., transcutaneously) to sense and transmit medical data (e.g., glucose analyte data) of a patient to one or more transceivers 404a and 404b.
  • the transceivers 404a and 404b can be custom analyte monitoring display devices or computing devices such as smart phones, tablets, smart glasses, smart watches, desktop computers or a combination of these or similar devices.
  • Real time data can include one or more of estimated glucose value(s) (EGV), glucose concentration rate of change information, CGM alert information, raw sensor data, and/or other type of public or private data.
  • EUV estimated glucose value
  • CGM alert information CGM alert information
  • raw sensor data raw sensor data
  • other type of public or private data real time data is separated from bulk data because action may need to be taken based on the real time data in an immediate or timely manner.
  • public data includes information that is presented to a patient in charts or reports such as glucose values, monitor/calibration values, time adjustments, event entries by a patient (like meals, carbs, exercise, etc.), when sensors were started/stopped, which transmitter was used and when, and the like.
  • private data generally comprises information about the system and devices that comprise the system such as battery levels, screen durations, error logs, raw sensor signals, proprietary algorithm input/output, stack dumps of memory, and the like.
  • Public data and private data can comprise one or both of real time data and bulk data.
  • Bulk data can include, for example, data points such as system software version information, diagnostic information, other proprietary data and stored readings such as glucose levels recorded over a time period such as one hour, two hours, etc.
  • real time data can include, for example, data points such as monitored glucose levels, timestamps associated with monitored values, glucose monitor status, and the like.
  • real time data is data that is transmitted by the CGM 402 or transceivers 404a, 404b as it is created or shortly thereafter (e.g., intermittently or periodically, such as every one minute, five minutes, 10 minutes, etc.), while bulk data is data that may be stored on the CGM 402 or the transceivers 404a, 404b for a longer period of time than real time data (e.g., one hour) and transmitted less frequently than real time data.
  • the transceivers 404a and 404b can in turn transmit their respective data to a cloud computing architecture 410.
  • the cloud computing architecture 410 can include a real time server 408 for receiving and processing real time data from the transceiver 404a.
  • the cloud computing architecture 410 can also include a bulk data collector (BDC) 412 for receiving and processing bulk data from the transceivers 404a and 404b.
  • BDC bulk data collector
  • the real time data can be shared with a remote monitor 416 operated by a caregiver user, e.g., affiliated with the patient user.
  • a patient’s parent or guardian can have access to the remote monitor 416 for the purpose of remotely monitoring the patient’s health and receiving system alarms related to patient’s health.
  • Examples of systems and methods for remote monitoring of analyte data, such as by remote monitor 416 are described in more detail in U.S. Patent Publication Nos. 2014/0184422 and 2014/0187889, all of which are incorporated herein by reference in their entirety for all purposes.
  • the cloud computing architecture 410 includes a tech support server 422.
  • the tech support server 422 can include one or more computers (e.g., servers) in communication with one or more databases to form a tech support system 420 for diagnosing and resolving patients’ technical issues associated with a medical device, such as CGM 402 and/or transceiver 404a, 404b, and handling subsequent logging and reporting associated with those technical issues.
  • Various embodiments of the tech support system 420 are described that comprise the tech support server 422 in communications with a patient records server or database 424, product records server or database 426, an accounting server or database 428, a regulatory records server or database 430, and/or a tech issues & solutions server or database 432.
  • the tech support server 422 can communicate with a patient records database 424.
  • diagnosing or resolving a patient’s complaint involves an investigation or query of the patient’s records.
  • Such investigation can reveal information relevant to resolving the patient’s technical issue.
  • the investigation can help determine what sensor the patient is currently using, the age of the sensor, or other historical data related to the patient’s hardware, software or the patient’s prior technical issues.
  • the automated or semi-automated systems and methods described herein can automatically order replacement parts, for example replacement sensors, and automatically update the appropriate patient’s records in the patient records database 424.
  • the tech support server 422 can be configured to both store and query a tech issues & solutions database 432.
  • the database 432 can be a knowledge database updated automatically by the tech support server 422 or by the tech support personnel operating a tech support personnel computing system 434. Some references to the tech support personnel computing system 434 may refer to the personnel operating the computing system 434.
  • the tech issues & solutions database 432 can maintain histories and logs of issues the patients have experienced as well as known solutions to those issues.
  • data or population analytics can be run on the data in the database 432 or alternatively on data provided by the BDD 414.
  • the call volume to the tech support center (e.g., tech support personnel 434) can be reduced substantially, e.g., such as up to 50% reduction of the example top 6 issues.
  • addressing the top-ranked issues may improve saving flows to the other downstream activities that tech support issues subsequently cause (e.g., such as QA/Regulatory etc., as well as may improve customer retention.
  • Examples of the top-ranked tech support issues can include a question mark icon (“???”) presented in the status box (e.g., associated with communication disruptions between transmitter and receiver), inaccurate calibrations, hardware error icons, or others.
  • Such automated coding of errors can improve the patient’s experience when troubleshooting an issue.
  • patients do not refer to various components of the analyte monitoring system by correct terminology. Consequently, time and resources are spent attempting to identify the technical issue for which a patient is contacting tech support.
  • tech support technician when discussing a technical issue with tech support technician, a patient may incorrectly state that his sensor does not work, while the issue may be that the patient’s receiver does not turn on. Consequently, the technician attempts to resolve the issue by applying sensor failure troubleshooting scripts. In some cases, the technician may incorrectly order replacement sensors for the patient, while the issue may reside in the patient’ s receiver.
  • the analyte sensor application 330 can append those permissions to the error ticket, or if those permissions are not previously obtained, the analyte sensor application 330 can prompt the user for those permissions, append the obtained permissions to the error ticket and transmit the error ticket to the tech support server 422.
  • the tech support server 422 can extract the error code from the error ticket and search the database of known issues in the tech issues & solutions database 432.
  • the error code may have, for example, identified one or more conflicting applications running in the background of the display devices 404, which causes data gaps at nighttime.
  • a message can be generated by the tech support server 422 and transmitted as an alert to the display devices 404 containing a message alerting the patient about the detection of the issue of data gaps at night and the suggested solution of closing those applications during nighttime.
  • the monitored analyte values are by design allowed to be outside range for some 10 to 20% of the time during an analyte monitoring session.
  • Some patients may not be aware of such or other system limitations and incorrectly assume that these system limitations amount to technical issues.
  • the analyte sensor application 330 can alert the patient thus alleviating the need to generate or transmit error tickets.
  • the tech support server 422 can search the tech issues & solutions database 432 for other tech support personnel who may have recent experiences with a similar issue. Subsequently, the tech support server 422 can connect the two tech support personnel via an on-screen chat box or other methods to provide for an ability of the tech support personnel 434 to query and use other tech support personnel’s knowledge and skill in resolving patients’ technical issues.
  • the tech support server 422 can categorize an issue and consult an appropriate troubleshooting script in the tech issues & solutions database 432. Alternatively, if the tech support server 422 determines that the resolution of the issue is better left to a tech support personnel 434, the tech support server 422 can route the issue to a tech support personnel 434 who is known to be skilled in handling the issue.
  • the tech support server 422 can be configured with appropriate thresholds to automatically alert when the reports from the tech issues & solutions database 432 surpasses those thresholds.
  • system-wide reports can be run on data which is not subject to HIPAA.
  • the engineering & design team 436 can subsequently indicate whether a particular issue reported to them was acknowledged and have been added to their workload. Consequently, an analysis of the tech issues & solutions database 432 can reveal issues that have not yet been acknowledged or acted upon by the engineering & design team 436.
  • the ability of the engineering & design team 436, to have visibility into the technical issues encountered by the patients, enables the engineering & design team 436 to proactively experiment with various solutions and potentially update the tech issues & solutions database 432 with new solutions for emerging issues.
  • the tech support server 422 can proactively search for and detect technical issues by running population data analytics (e.g., based on multiple patient experiences) on the bulk data contained in the BDC 412 or data provided by the BDD 414.
  • population data analytics e.g., based on multiple patient experiences
  • technical issues would have to be reported and logged through regular technical support channels. Months of patients’ calls need to be manually analyzed before trends in the emerging or potential issues could be detected.
  • by proactively mining the data in the BDC 412 and/or BDD 414 emerging trends and potential issues can be detected and remedied before they can afflict many patients.
  • remedying detected technical issues include tech support system 420 sending over-the-air (OTA) software fixes to display devices 404.
  • OTA over-the-air
  • the BDC 412 can be analyzed, separately or together, for the purposes of providing proactive tech support. Such analysis can reveal latent or overt technical issues.
  • the tech support server 422 can compare different streams of data associated with same reading sessions to detect discrepancies indicative of an underlying technical issue.
  • the data stored on the real time server 408 and the BDC 412 can contain duplicative analyte data associated with same analyte read out sessions. Discrepancies between the streams of data stored in different databases can indicate the existence of a technical issue.
  • the tech support server 422 can be configured to analyze the data on one or more reading sessions stored on the real time sever 408 or BDC 412 in order to diagnose and resolve an error ticket initiated by the user or the analyte sensor application 330.
  • the tech support server 422 can be configured to be in communication with the remote monitor 416.
  • the remote monitor 416 may desire to initiate an error ticket.
  • the remote monitor 416 may not receive analyte data and/or alerts, via the real time server 408, associated with the patient user’s analyte state monitored by CGM 402 and transceiver 404 A, 404B.
  • the remote monitor 416 can initiate an error ticket similar to the way a transceiver 404 A generates and transmits an error ticket as described herein.
  • the remote monitor 416 can add authentication or verification data in the error ticket to identify itself as a HIPAA authorized user.
  • the remote monitor 416 receives real time data from the real time server 408.
  • An error ticket and a request for tech support generated by the remote monitor 416 can include real time data.
  • the tech support server 422 can be configured to analyze real time data contained in an error ticket from a remote monitor 416 in conjunction with the bulk data from the BDD 414 to diagnose and resolve the error ticket using techniques described herein.
  • the tech support server 422 can be in communication with an authentication system to authenticate the remote monitor 416 prior to communicating with the remote monitor 416.
  • the remote monitor 416 is presented with real time data in a visual form or graphical display.
  • a remote monitor 416 can detect and initiate an error ticket based on inspection of the visual or graphical display.
  • the tech support system 420 may also have access to same or similar copies of the visual or graphical displays transmitted to the remote monitor 416, and can decode an error ticket generated based on the visual or graphical displays.
  • the tech support system 420 can include visual or graphical display data including, data tables, charts, data categories (e.g., estimated glucose values (EGVs), logs, etc.) with the same or similar visual or graphical display data as provided to the remote monitor 416.
  • the visual or graphical display data can include charts presenting data in a chronological form.
  • the visual or graphical display data can include an identification of the source of the data (e.g., hardware or software generating or initiating the visual or graphical display).
  • the tech support system 430 may include one or more tools for automatically or semi-automatically downloading relevant data from and analyzing one or multiple returned display devices 404 or returned CGM devices 402. In conventional customer support environments, the cost and administrative burden of properly analyzing a returned unit may be prohibitive. Consequently, product improvements or troubleshooting advantages, which could be gained from analyzing such returned units, may be forfeited.
  • the tech support system 420 can request that a patient return a custom analyte display device or a CGM 402 for further troubleshooting and analysis.
  • the cloud computing architecture may receive and store multiple copies of the same data stream for various purposes including providing automatic or semiautomatic tech support, issue detection and resolution.
  • the real time server 408 can receive real time data from the display devices 404, more frequently than the BDC 412 receives data from the display devices 404.
  • the real time server 408 can receive real time data from the display device 404a every hour automatically via a wireless connection; the BDC 412 can receive bulk data from the display device 404b when the patient initiates uploading bulk data.
  • a copy of bulk data can be stored in the BDD 414 for a longer time than the same copy stored in the BDC 412.
  • various storage durations for various copies of the same data stream can be designated and executed to accomplish different objectives, for example, to comply with a mandated “keep data” order within the cloud computing system 410.
  • the cloud computing system 410 can include an IT archive server, which can store data for which there is a mandated “keep data” order longer than the storage durations among other components of the cloud computing system 410.
  • multiple copies within the cloud computing system 410 (which may be included for objectives other than providing tech support) can nevertheless be utilized to automatically identify and resolve technical issues.
  • multiple copies are stored in the IT archive server to comply with quality requirements “keep data” durations. These multiple copies may be recalled, analyzed and compared with other copies of the same data stream in order to identify or resolve technical issues.
  • Proactive detection, identification and analysis of technical issues can be accomplished by automatically analyzing the output of the medical device provider’s systems and services that may not be specifically directed to providing technical support.
  • retrospective reporting may be provided to allow patients and their caregivers to view patient’s data and metrics associated with the patient’s data.
  • the tech support system 420 detects a failure, the patient or patient’s caregiver can be provided with questionnaires in addition to retrospective reporting.
  • the questionnaires may be in the form where answers are collected by receiving inputs and selections via drop down menus, radio buttons or other forms where limited free text is allowed. Collecting data in this form allows for expedient analysis, for example, via running population or data analytics.
  • the patient may be presented with general or real time information on the tech support system 420 or the tech support personnel 434.
  • the patient can, by navigating through a menu driven application, be informed as to a current estimate of tech support wait/hold times if the patient were to speak with a tech support technician.
  • comparison estimated wait times of automated troubleshooting option can be presented.
  • the wait time estimates can be determined from system-wide historical analysis of tech support data by time of day, week, month, etc.
  • the wait time estimates can be provided to the patient after the patient has provided information and data associated with her technical issue. The provided wait time estimates can be informed by or adjusted by the technical issue data entered into the system.
  • the analyte sensor application 330 or similar application used by the patient can be equipped with a menu option for locating physical stores where devices of a medical device company or replacement parts are sold.
  • the patient can place an order for medical device products or replacement parts by interacting with the analyte sensor application 330.
  • the physical stores can allow inventory availability checks, receipt of orders, holding of and in-store pick-up of products.
  • the tech support system 420 or the tech support personnel 434 can establish remote control of a patient’s medical devices (e.g., display devices 404 or CGM 402) in order to provide automated or semiautomated tech support.
  • a remote control event can include status query, self-diagnostic troubleshooting algorithms, reading and writing control data into and out of the patient’s medical devices, modifying device parameters and other control events.
  • FIG. 4 shows the tech support server 422 as a separate server than the BDD 414
  • the tech support server 422 can be an integral part of the BDD 414 to expedite diagnosis or resolution of patient’s technical issues.
  • the tech support server 422 can be a separate server from the BDD 414 as shown in FIG. 4.
  • Advantages of separating the tech support server 422 from the BDD 414 can include an ability to operate the two databases under separate FDA classifications.
  • the tech support server 422 can be operated as a Class I or Class II device by controlling the data routed to the tech support server 422.
  • one tech support server 422 with the same FDA classification as the BDD 414 can be embedded in the BDD 414 and handle patient’s technical issues and data that are appropriate for the FDA classification of the BDD 414.
  • Other issues and data appropriate to other FDA classifications can be routed to an alternate tech support server 422.
  • intelligent routing of patient’s technical issues to appropriate tech support server 422 diagnosis and resolution of the issues can be performed expeditiously and the resources of the cloud computing architecture 410 can be preserved.
  • the contents of the error ticket can be turned into an email and forwarded to the tech support personnel 434.
  • the tech support personnel 434 can manually perform the logging, recording and reporting that may be associated with the patient’s request for tech support.
  • the logging, recording and reporting can be performed by the tech support system 420, without intervention from the tech personnel 434.
  • a combination of automated and semi-automated implementations can be used where the tech support personnel intervene in some circumstances and not in others.
  • the tech support system 420 can be configured to automatically check its relevant databases on the components age-out date (or some predetermined time prior to age-out date) to determine whether a replacement part has been scheduled for shipping. If yes, the tech support system 420 can notify the patient of the scheduled shipment and associated information, such as expected delivery date, tracking number and billing information. If no replacement part has been scheduled as expected, the tech support system 420 can notify the patient accordingly and request authorization for scheduling and shipment of replacement parts.
  • Certain embodiments described herein involve continuous analyte monitoring systems capable of automatically detecting early failure or failure of one or more components of the continuous analyte monitoring system.
  • certain embodiments of the present disclosure provide one or more prediction algorithms capable of detecting early failure or failure associated with an analyte sensor (e.g., analyte sensor 375 of FIG. 3B, also designated with the numeral 10 in FIG. 1A) and/or a transceiver (e.g., transceiver 360 of FIG. 3B, also referred to herein as transmitter 360) of the continuous analyte monitoring system.
  • the continuous analyte monitoring system may include an analyte sensor system (e.g., such as analyte sensor system 308 of FIGs. 3A and 3B) having at least an analyte sensor (e.g., analyte sensor 375 of FIG. 3B, which may also be designated with the number 10 in FIG. 1A) and a transmitter (e.g., transceiver 360 in FIG. 3B, which may also be a part of item 12 in FIG. 1A) and in communication with at least one display device (e.g., display device 310 of FIGs. 3A and 3B) having a processor (e.g., processor/microprocessor 35 of FIG.
  • an analyte sensor system e.g., such as analyte sensor system 308 of FIGs. 3A and 3B
  • an analyte sensor e.g., analyte sensor 375 of FIG. 3B, which may also be designated with the number 10 in FIG. 1
  • analyte sensor application 330 executing on processor 335 may be capable of performing such early failure detection and diagnosis irrespective of a server (e.g., such as server system 334 illustrated in FIG. 3A).
  • a server e.g., such as server system 334 illustrated in FIG. 3A.
  • Root cause analysis performed by processor 335 (1) identifies one or more root causes of a plurality of event indications generated based on one or more errors associated with the continuous analyte monitoring system and (2) determines corrective actions to address the one or more root causes.
  • the root cause analysis process provides a way to analyze multiple different factors that may have contributed to the generation of each of the event indications and determine what factor(s) are the underlying root cause.
  • the root cause analysis seeks to (1) isolate the root cause of an error in the continuous analyte monitoring system, (2) accurately determine actions for preventing similar future errors from occurring, and (3) provide a recommendation for removing the root cause or take action to remove the root cause.
  • a continuous analyte monitoring system deployed on a patient may generate (e.g., via transceiver 360 of analyte sensor system 308) a plurality of event indications indicating sensed signals (e.g., generated based on sensed analyte levels of the patient) are below a minimum configured error threshold.
  • a plurality of event indications indicating sensed signals are below a minimum threshold may indicate to the continuous analyte monitoring system that analyte sensor 375 has failed, before making this determination, processor 335 may perform a root cause analysis to more accurately determine a root cause of the generated event indications.
  • Processor 335 may take into account many factors which may have contributed to generation of the event indications.
  • processor 335 may consider each of these factors when making the determination.
  • processor 335 may determine that the plurality of event indications were generated because analyte sensor 375 has fallen off the body of the patient.
  • Processor 335 may further ascertain that analyte sensor 375 has fallen off the patient’s body due to severe dryness and flaking of the patient’s skin.
  • the root cause analysis provides a more accurate determination for why one or more errors exist with the continuous analyte monitoring system, beyond merely identifying the errors are caused by a failing component of the system.
  • the continuous analyte monitoring system may recommend or take one or more actions to help prevent similar errors from reoccurring such that when a component of the continuous analyte monitoring system does, in fact, fail, processor 335 will be able to accurately identify this failure (or premature failure).
  • Such root cause analysis may be described in more detail below.
  • processor 335 may receive analyte measurements from transceiver 360, and in some cases event indications generated and transmitted by transceiver 360. In some embodiments, to perform the root cause analysis, the processor 335 may further receive information from a server (e.g., server system 334 of FIG. 3 A, etc.). In some embodiments, processor 335 may further receive information from the patient to better inform the root cause analysis. With this additional information, processor 335 may more precisely identify patterns and trends for the autonomous detection of component failures associated with the patient’s analyte monitoring system.
  • a server e.g., server system 334 of FIG. 3 A, etc.
  • processor 335 may further receive information from the patient to better inform the root cause analysis. With this additional information, processor 335 may more precisely identify patterns and trends for the autonomous detection of component failures associated with the patient’s analyte monitoring system.
  • steps 808, 810, and 812 may be performed by server system 334, and in certain other embodiments, steps 808, 810, and 812 may be performed by a combination of processor 335 and server system 334.
  • transmitter 360 may gather the electric sensor current from analyte sensor 375 for conversion into a calibrated and/or filtered data streams that are used to provide useful values of analyte for analysis.
  • the transmitter may determine estimated glucose values (EGV data) for analysis.
  • event indications generated by transmitter 360 may indicate one or more errors associated with analyte sensor 375.
  • the plurality of event indications may indicate (1) signals sensed by analyte sensor 375 above a configured error threshold (e.g., event indications related to a very high signal error), (2) signals sensed by analyte sensor 375 below a configured error threshold (e.g., event indications related to a very low signal error), (3) errors associated with a calibration of analyte sensor 375, (4) signals sensed by analyte sensor 375 having a rate of change higher than a threshold (e.g., event indications related to high or low spikes in sensed signals), or any combination thereof.
  • a configured error threshold e.g., event indications related to a very high signal error
  • signals sensed by analyte sensor 375 below a configured error threshold e.g., event indications related to a very low signal error
  • operations 800 continue by the processor (e.g., processor 335) receiving the plurality of event indications indicating one or more errors associated with the analyte sensor (e.g., analyte sensor 375).
  • Processor 335 receiving these event indications indicating one or more errors associated with analyte sensor 375 may analyze whether a root cause of the generation of these event indications corresponds to a prematurely failing analyte sensor 375, an already failed analyte sensor 375, an analyte sensor 375 that is no longer attached to the body of the patient (e.g., analyte sensor 375 that has fallen off or has become detached thereby creating a gap between an interface of analyte sensor 375 and the patient’s body), or some other reason, explained in more detail herein.
  • root cause analysis performed by processor 335 in the continuous analyte monitoring system may involve four major steps including, the gathering of necessary data to be able to localize errors associated with the continuous analyte monitoring system, event and causal factor prediction, root cause identification, and recommendation generation and implementation.
  • processor 335 may collect all necessary data to be able to localize an error with respect to the continuous analyte monitoring system.
  • processor 335 may receive analyte data and a plurality of event indications from transmitter 360 of the continuous analyte monitoring system to begin processing. However, in some cases, this information may not be sufficient to accurately determine a root cause of the error(s). If signals sensed by analyte sensor 375 fail to provide all essential data, the root cause analysis may not be complete. For this reason, in some embodiments, processor 335 may receive additional information to further inform the root cause analysis.
  • an event indication may be generated for reasons beyond a failing component of or associated with the continuous analyte monitoring system. For example, excessive pressure on analyte sensor 375 may result in very low sensed signals detected by analyte sensor 375 while excessive moisture at an interface of analyte sensor 375 and the patient may result in very high sensed signals detected by analyte sensor 375. Without additional information, processor 335 may inaccurately assume analyte sensor 375 has failed, when, in fact, other factors were contributing to the error. Accordingly, in some embodiments, processor 335 may be further configured to receive secondary sensor data associated with the patient. The secondary sensor data may be used by processor 335 to more accurately identify an underlying root cause of the error. Secondary sensors may provide quick, reliable data thereby removing the need to inquire further with a patient to collect pertinent data for analysis.
  • the secondary sensory data may include accelerometer data associated with movement of analyte sensor 375.
  • a patient whom regularly engages in walking, running, exercise, etc. may have increased, or prolonged periods of, perspiration that may impact signals sensed by analyte sensor 375.
  • a patient whom regularly engages in swimming may expose analyte sensor 375 to prolonged periods of moisture which may also impact signals sensed by analyte sensor 375.
  • accelerometer data may be used to determine previous activities of a patient based on a mapping between patient acceleration and patient activity to inform the root cause analysis.
  • the secondary sensory data may include gyrometer data indicating an orientation of analyte sensor 375.
  • a gyrometer may be capable of detecting an orientation of analyte sensor 375 to determine whether there is too much pressure on analyte sensor 375 thereby causing sensor 375 to collect very low signals.
  • gyrometer data may indicate that analyte sensor 375 of a patient is in a horizontal position, facing downward, and processor 335 may use this gyrometer data to determine that, based on an orientation of sensor 375, the patient is likely laying on their stomach. Processor 335 may then use this assumption to determine that very low signals sensed by analyte sensor 375 are due to excess pressure caused by the patient laying on their stomach, as opposed to determining that analyte sensor 375 has failed.
  • the secondary sensory data may include moisture detection data indicating a moisture level at an interface between analyte sensor 375 and the patient (also referred to herein as the patch site of analyte sensor 375).
  • processor 335 may leverage moisture data to determine whether increased moisture at an interface between analyte sensor 375 and the patient is contributing to very high signals being sensed by analyte sensor 375.
  • a moisture sensor may shed light on a patient’s routine (e.g., patient showers twice a week, patient regularly engages in swimming, etc.) or a patient’s skin attributes (e.g., perspiration levels of the patient) to better inform the root cause analysis.
  • the secondary sensory data may include heart sensor data indicating a heart rate of the patient.
  • a patient’s heart rate may be indicative of the types of activities the patient actively engages in.
  • information about a patient’s recent activities may be essential information for processor 335 to have when performing the root cause analysis.
  • While secondary sensor data provides access to a depth of reliable data which a user may not be able to provide, information obtained from sensor technology may be costly and/or limited as to the type of data that may be collected. For example, medical history of a patient may provide many insights during the root cause analysis; however, a sensor may not be able to provide such information. For this reason, additional methods of collecting pertinent data, including patient questionnaires, may be contemplated.
  • processor 335 may be further configured to receive one or more answers to one or more questions presented to a user, thus, determining one or more root causes may be further based on the answers.
  • a user may be the patient, or in the alternative, a user may be a patient’s caregiver, physician, relative, etc.
  • a user may choose to report further information about an event indication or provide other contextual information to be included with the event indication.
  • the questionnaires may be in a form where answers are collected by receiving inputs and selections via drop down menus, radio buttons or other forms where limited free text is allowed. Collecting data in this form may allow for expedient analysis, for example, via running data analytics by processor 335.
  • certain questions may be associated with a skin condition of the patient. For example, questions may inquire about perspiration levels of the patient, dryness of the patient’s skin, roughness of the patient’s skin, as well as any skin allergies or reactions the patient has previously experienced.
  • certain questions may be associated with recent activities of the patient.
  • a user may be provided with a multiple-choice question inquiring into whether the patient regularly engages in any sports activities known to have an effect on patch life of the analyte sensor (e.g., swimming, sports with high movements in patch site regions, “high impact” in site regions, etc.).
  • certain questions may be associated with nutrition of the patient. For example, questions may inquire into a diet of the patient, and more specifically, whether the patient has a high glycemic diet or a low glycemic diet.
  • a patient’s diet may provide many valuable insights to the root cause analysis, including, but not limited to, a patient’s rate of glucose release or a patient’s sebum content level, where sebum is typically connected to hair follicles and used to form a protective barrier on the skin to prevent excessive water loss.
  • a patient whom consumes food low on the glycemic index (GI) scale may tend to release glucose slowly and steadily, while a person whom consumes food high on the GI scale may release glucose more rapidly.
  • GI glycemic index
  • a patient whom consumes high GI foods may be able to offset hypo- (or insufficient) glycemia, as opposed to a patient whom does not consume high GI foods.
  • Understanding a patient’ s rate of glucose release may help to differentiate between scenarios where a spike in a patient’s glucose values occurs due to the patient’s diet versus scenarios where a spike in a patient’s glucose value occurs due to a failing component of the continuous analyte monitoring system.
  • understanding a patient’s diet helps to better inform why glucose values specific to a patient appear to be abnormally high, abnormally low, experiencing a quick rate of change, experiencing a slow rate of change, etc. which may help to accurately identify situations where an actual failure (or early failure) of a component is occurring.
  • a patient whom consumes food low on the GI scale may have reduced sebum; therefore, the patient may have increased skin shedding (e.g., flaking) which in turn affects adhesion of an analyte sensor to the patient’s skin.
  • skin shedding e.g., flaking
  • Questions associated with nutrition of the patient may also inquire into the water intake of the patient over a specified period of time to provide awareness as to a condition of the patient’s skin.
  • a patient whom regularly drinks water may mitigate transepidermal water loss (TEWL) (e.g., rate of water vapor that is lost to the atmosphere) and increase collagen function (e.g., increase skin elasticity) of the patient’s skin thereby reducing a potential for analyte sensor 375 to fall off the body of the patient.
  • TEWL transepidermal water loss
  • collagen function e.g., increase skin elasticity
  • Proper hydration may stabilize the structure of collagen, preserving its function to keep skin elastic.
  • Increased collagen- water structures may reduce the flow of water to the skin boundary, thereby reducing TEWL.
  • one or more questions presented to a user may include one or more questions associated with an interface between analyte sensor 375 and the patient (e.g., patch site). Questions may inquire into a preferred placement of analyte sensor 375 by the patient (e.g., preferred placement on a patient’s abdomen, lower back, back side of arm, etc.), an orientation of analyte sensor 375, whether analyte sensor 375 is worn along skin lines of deformation, and/or whether analyte sensor 375 is placed in a location on the skin with a significant amount of hair.
  • analyte sensors worn along skin lines of deformation may be more prone to falling off than analyte sensors that are placed on a patient’s arm due, at least in part, to constant bending at the patch site. Such information may further inform the root cause analysis performed by processor 335.
  • certain questions may be associated with a deployment routine of analyte sensor 375 by the patient.
  • questions may inquire into a time of day analyte sensor 375 is generally applied to the body (e.g., moming/aftemoon/evening), how long after showering the patient waits before re-applying analyte sensor 375 (e.g., directly after a patient’s shower, six hours after a patient’s shower, twenty-four hours after a patient’s shower), whether any lotions or powders are used on the skin prior to deployment of analyte sensor 375, and/or whether any cleaners, enhancers, or overlays are used.
  • processor 335 may collect secondary sensor and questionnaire data to further inform the root cause analysis. In some cases, collected secondary sensor data and/or questionnaire data may be used to verify data of each other, or analyte levels sensed by analyte sensor 375.
  • processor 335 may use a “walking back” method to determine one or more root causes associated with a plurality of event indications.
  • the “walking back” method may include comparing a recent event indication indicating an error associated with analyte sensor 335 to one or more event indications, also indicating errors associated with analyte sensor 335, generated prior to the recent event indication.
  • a recently received event indication transmitted to processor 335 by transmitter 360 may indicate an error associated with analyte sensor 375.
  • processor 335 may compare this event indication to an event indication received from transmitter 360 ten minutes prior, twenty minutes prior, etc. to determine whether a root cause may be ascertained across the plurality of event indications.
  • processor 335 may use pattern recognition to determine one or more root causes associated with a plurality of event indications.
  • Pattern recognition is a process that determines whether any regularities exist within a compilation of data (e.g., event indications, secondary sensor data, patient questionnaire answers, and additional information necessary for analysis). Pattern recognition may be broken into three main parts: (1) an explorative part, where a predictive algorithm, executed by processor 335, searches for patterns among the collected data, (2) a descriptive part, where the predictive algorithm begins to categorize recognized patterns (segment data), and (3) an analysis part, where the segmented data is analyzed.
  • the predictive algorithm at processor 335 may analyze a pattern of data from the patient to determine whether actions of the patient are artificially causing analyte sensor 375 to appear like analyte sensor 375 has failed, although analyte sensor 375 is still functioning properly.
  • processor 335 may use machine learning to determine one or more root causes associated with a plurality of event indications.
  • Machine learning techniques whether deep learning networks or other experiential/observational learning systems, may be used to build a model trained to recognize patterns between generated event indications indicating errors associated with the continuous analyte monitoring system and possible root causes for the event indications.
  • the model may be based on sample data, known as “training data”, in order to make predictions without being explicitly programmed to do so.
  • “training data” of known pluralities of event indications mapped to one or more root cases may be used to train the model.
  • processor 335 may be further configured to receive an indication from a server (e.g., server system 334 of FIG. 3) indicating a pattern associated with event indications for a population of patients. Processor 335 may use the received pattern associated with event indications for a population of patients to determine the one or more root causes. For example, after receiving and/or generating three event indications indicating that sensed signals are above a maximum configured threshold, processor 335 may determine a root cause of the three event indications based, at least in part, on one or more patterns received from server system 334.
  • a server e.g., server system 334 of FIG. 3
  • the received pattern of high sensed signals (e.g., the three event indications) in addition to other data from the patient (e.g., activity levels sensed by an accelerometer and/or moisture detection data sensed by a moisture sensor) may be compared against this specific pattern created based on population data to determine that a root cause of the high sensed signals is being caused by increased moisture at the analyte sensor when the patient’s data aligns with the pattern received from server system 334.
  • processor 335 may engage in root cause identification where processor 335 identifies one or more root causes associated with the plurality of event indications.
  • an event indication may, in some cases, indicate a prematurely failing or failed analyte sensor 375 or transmitter 360 of the analyte monitoring system; however, this may not always be the case. Instead, where an event indication comprises a false positive failure detection, processor 335 may further ascertain a root cause of the false positive indication.
  • event indications corresponding to one or more errors associated with analyte sensor 375 may include error codes related to very low sensed signals, error codes related to very high sensed signals, error codes related to sensor calibration, and error codes related to a residual operations failure mode.
  • Error codes related to very low sensed signals may be generated by transmitter 360 when multiple consecutive events indicate that the sensed signals are below a minimum configured error threshold.
  • Configured error thresholds may include a minimum configured error threshold and a maximum configured error threshold. Configured error thresholds may be consistent across all manufactured continuous analyte monitoring systems or configured to be patient- specific based on compiled patient-specific analyte data over an adequate period of time. For example, where the analyte measured is glucose, a patient with consistently high glucose values may have a maximum configured threshold greater than a maximum configured threshold for a patient with consistently low glucose values.
  • the maximum error threshold configured for the patient with consistently high glucose values may help to reduce false positive indications of failure generated by transmitter 360 by decreasing the likelihood of a high glucose value triggering the generation of an event indication by transmitter 360.
  • the one or more root causes may include at least one of: analyte sensor 375 is failing, analyte sensor 375 has failed, detachment of analyte sensor 375 from the patient’s body, compression on analyte sensor 375, wound trauma at an interface between analyte sensor 375 and the patient, low sensor sensitivity associated with analyte sensor 375, or deteriorated quality of a signal sensed by analyte sensor 375.
  • the root cause may not always be due to failure of analyte sensor 375 or detachment of analyte sensor 375 from the patient’s body.
  • multiple consecutive events indicating sensed signals are below a minimum configured error threshold may be due, at least in part, to compression on analyte sensor 375.
  • Compression may include localized pressure on analyte sensor 375 causing a depletion of oxygen, or a decrease in the amount of oxygen, that may reach the patch site (e.g., reach the interface between analyte sensor 375 and the patient’s body).
  • a decrease or depletion in oxygen may result in artificially low signal or attenuated signal sensed by analyte sensor 375.
  • analyte sensor 375 may experience excessive pressure when a patient sleeps on their stomach.
  • Processor 335 may give these factors additional weight when determining whether compression on analyte sensor 375 is the cause of one or more errors associated with analyte sensor 375. For example, a plurality of event indications generated during the hours of 2:00 am and 4:00 am may be a good indication that compression is the underlying root cause.
  • multiple consecutive events indicating sensed signals are below a minimum configured error threshold may be due, at least in part, to wound trauma at an interface between analyte sensor 375 and the patient (e.g., patch site).
  • a wearable analyte sensor 375 including a continuous glucose monitor (CGM) may require the patient to insert a needle under their skin when deploying the analyte sensor 375.
  • inserting the needle may create a wound at the patch site. The wound may cause white blood cells to accumulate at the insertion site where the needle is inserted.
  • These white blood cells may consume glucose locally around the insertion point and may cause a noticeable difference in capillary blood glucose versus glucose around analyte sensor 375 due to the fact that there is less glucose around the insertion site. Accordingly, the artificial differential in glucose may cause signals sensed by analyte sensor 375 to be very low.
  • Wound trauma may be patient-specific; thus, processor 335 may take this into consideration when determining whether wound trauma is the cause of one or more errors associated with analyte sensor 375.
  • multiple consecutive events indicating sensed signals are below a minimum configured error threshold may be due, at least in part, to deterioration of analyte sensor 375.
  • Deterioration may decrease reliability of analyte sensor 375, and where analyte sensor 375 is not reliably tracking analyte, very low signals may be sensed by analyte sensor 375.
  • exposure of analyte sensor 375 to prolonged or increased incidents of noise (e.g., unwanted effects on the signal) and/or higher degrees of noise may lead to deterioration of analyte sensor 375.
  • increased noise may be due, at least in part, to placement of analyte sensor 375 under a patient’s arm or at a pant line of the patient’s stomach. Additionally, deterioration of analyte sensor 375 may be more prevalent as analyte sensor 375 nears the end of its “working period” (e.g., days eight through ten of the life of the sensor). Processor 335 may give these factors additional weight when determining whether deteriorated quality of a signal sensed by analyte sensor 375 is the cause of one or more errors associated with analyte sensor 375.
  • the one or more root causes may include at least one of: analyte sensor 375 is failing, analyte sensor 375 has failed, a malfunction associated with analyte sensor 375, high sensitivity of analyte sensor 375, damage to a membrane of the patient coupled to analyte sensor 375, or high moisture condition associated with analyte sensor 375.
  • the root cause may not always be due to failure of analyte sensor 375 or a malfunction associated with analyte sensor 375.
  • multiple consecutive events indicating sensed signals are above a maximum configured error threshold may be due, at least in part, to damage to a membrane of the patient coupled to analyte sensor 375.
  • a tear in a patient’s membrane may expose a working electrode of analyte sensor 375 to more surface area. By increasing the surface area the working electrode is exposed to, more current may be allowed to flow thereby causing transmitter 360 to see very high sensed signals and triggering the generation of one or more event indications corresponding to the very high sensed signals.
  • multiple consecutive events indicating sensed signals are above a maximum configured error threshold may be due, at least in part, to a high moisture condition associated with analyte sensor 375.
  • Moisture present at the interface may adversely affect signals sensed by analyte sensor 375.
  • processor 335 may be further configured to receive moisture detection data indicating the high moisture condition. The moisture detection data may aid the root cause analysis in selecting or eliminating high moisture content as a likely cause of the error associated with analyte sensor 375. In other words, the moisture sensor may help prevent the false detection of analyte sensor 375 failure.
  • one or more root causes may include deficient sensor calibration when a difference between the one or more analyte measurements and the one or more reference analyte measurements is greater than a threshold.
  • reference analyte measurements may be measurements from a finger stick procedure performed by a patient.
  • a finger stick blood test may be used to measure the amount of certain substances in a patient’s blood, by making a small prick into the patient’s fingertip and collecting blood sample(s) to be used as one or more reference analyte measurements.
  • Processor 335 may receive these reference analyte measurements from the patient and transmit them to transmitter 360 (e.g., transceiver 360 which may also be configured to receive).
  • Transmitter 360 may receive the finger stick measurements from processor 335 and compare them to analyte measurements, for example glucose readings, transmitter 360 is receiving from analyte sensor 375.
  • transmitter 360 may take action to recalibrate analyte sensor 375 by generating event indications and transmitting the event indications to processor 335.
  • Error codes related to a residual operation failure mode may also be generated by transmitter 360.
  • transmitter 360 When analyte sensor 375 is exposed to light or moderate noise, one or more filters may be applied to “smooth” the raw sensor data. The filter signal may be compared to the raw sensor signal by transmitter 360. If the transmitter realizes a residual between these two streams (e.g., a differential between the raw signal and the filtered signal) has become too large, transmitter 360 may generate an event indication. The event indication may be representative of a residual operation failure mode.
  • the one or more root causes may include compression on analyte sensor 375. For example, an onset to compression that is very steep may appear to transmitter 360 as a large differential between the raw signal and the filtered signal.
  • the one or more root causes may include damage to a membrane of the patient coupled to analyte sensor 375.
  • a tear in a patient’s membrane may expose the working electrode to more surface area. This may appear to transmitter 360 as a large differential between the raw signal and the filtered signal.
  • operations 800 continue by the processor (e.g., processor 335) taking one or more actions to resolve the one or more root causes.
  • processor 335 may engage in recommendation generation and implementation (e.g., in accordance with the fourth step of the root cause analysis process).
  • processor 335 may be configured to take one or more actions to resolve the one or more root causes.
  • one or more actions may include autonomous (e.g., without outside instruction from a user, technical support personnel, etc.) actions taken by processor 335.
  • one or more actions may include the generation of one or more recommendations to be provided to a user, wherein the recommendations relate to suggestions or steps for minimizing or eliminating one or more root causes which led to generation of the one or more event indications.
  • Recommendations may be patient- specific and vary for each patient/event indication combination analyzed by processor 335.
  • one or more actions may include indicating to a user to relocate or reorient analyte sensor 375 on a body of the patient.
  • processor 335 may determine one or more activities regularly engaged in by the patient, e.g., using methods described herein, and suggest a preferred site for deployment of analyte sensor 375.
  • processor 335 may indicate to a user to relocate analyte sensor 375 to along lines of least deformation to decrease a likelihood of analyte sensor 375 falling off the body of the patient.
  • processor 335 may suggest movement of analyte sensor 375 to a location of the patient’s body having less hair.
  • processor 375 may suggest a user change the orientation of analyte sensor 375 from a transverse wear to a longitudinal wear for purposes of increasing elasticity (e.g., elasticity of a patient’s skin may be increased in the longitudinal direction) and reducing a likelihood of analyte sensor 375 falling off the body of the patient.
  • one or more actions may include indicating to a user to change a position of the body of the patient.
  • processor 335 may suggest a user change a sleeping position of the patient at night where the patient was previously sleeping on his or her stomach thereby causing excessive compression to analyte sensor 375.
  • one or more actions may include indicating to a user to change a diet of the patient.
  • processor 335 may indicate to a user that the patient’s sebum may be reduced by consuming low GI foods and reducing saturated fats.
  • processor 335 may suggest the patient reduce consumption of milk and/or other dairy product to decrease sebum content.
  • the processor may suggest the patient increase their water intake to help mitigate TEWL and increase collagen function. While skin may shed regardless of measures taken by the patient, keeping the patient in a constant hydration state may be important to mitigate the amount and/or type of shedding, particularly around the patch site.
  • processor 335 may suggest the patient increase consumption of linoleic acid containing foods during days following initial deployment of analyte sensor 375.
  • one or more actions may include indicating to a user to apply a cream to an interface between analyte sensor 375 and the patient.
  • processor 335 may suggest the patient apply creams containing hyaluronic acid which thermally stabilizes water and increases retention.
  • hyaluronic acid topic application may improve elasticity of the patient’s skin by as much as 55% (varied results in literature) thereby reducing a likelihood of analyte sensor 375 becoming detached from the patient’s body.
  • processor 375 may suggest alternative moisturizing creams that are known to have minimal effects on adhesion of analyte sensor 375 to the patient’s body.
  • Skin adhesion enhancers may include, but may not be limited to, diglycol, glycerin, sorbitol, oxctoxynol-9, dimethycone copolyol, diazolidinyl urea, methyparaben, isipropyl alcohol, partially hydrogenated rosin, gum mastic, styrax, alcohol (SDA-23), or methyl salicylate.
  • one or more actions may include indicating to a user to have the patient digest one or more supplements to increase adhesion of analyte sensor 375 at the interface between analyte sensor 375 and the patient.
  • processor 335 may suggest the patient take one or more supplements to increase the patient’s collagen content.
  • processor 335 may suggest the patient take anti-inflammation/histaminic suppressants to aid in the prevention of skin shedding.
  • one or more actions may include indicating to a user that a specific activity has caused the one or more event indications.
  • processor 335 may notify the user that excessive showering or swimming by the patient may be causing issues, described herein, with analyte sensor 375 of the patient.
  • processor 335 may further suggest the patient prevent analyte sensor 375 from experiencing cycles of hydration/dehydration of analyte sensor 375 by decreasing showering and/or swimming activity of the patient.
  • processor 335 may suggest the patient refrain from increased heart rate activities immediately following deployment of analyte sensor 375 to prevent excessive perspiration at the patch site.
  • one or more actions may include indicating to the user to recalibrate analyte sensor 375. In some embodiments, one or more actions may include indicating to the user to order a new analyte sensor for the patient. In some embodiments, one or more actions may include indicating to a user to order a new transmitter for the patient if a warranty period has expired.
  • one or more actions may include autonomous actions taken by processor 335.
  • one or more actions may include ordering a new analyte sensor for the patient.
  • the automated methods and systems may determine that a resolution of error(s) with a patient's continuous analyte monitoring system entails ordering of an analyte sensor replacement.
  • Processor 335 may therefore order a replacement analyte sensor to be shipped to the patient.
  • Processor 335 may subsequently create one or more invoices for the patient.
  • the event may be recorded in appropriate company accounting databases as a taxdeductible eligible event.
  • processor 335 may determine the delivery and shipment speed appropriate for the patient based on the urgency of the need to deliver a new replacement sensor.
  • the patient may be notified via an email message, short message service (SMS), on-screen alert, or other means of communication.
  • SMS short message service
  • the patient may also be provided with shipment tracking information.
  • processor 335 may check the patient records to determine whether multiple sensors have been ordered within a short period of time. If the patient records show that the patient has ordered multiple sensors within a short period of time, processor 335 may flag the error ticket and request intervention from tech support personnel, by sending an email, on-screen alert or other means of communication.
  • event indications indicating one or more errors associated with analyte sensor 375 and root causes that may correspond to each of these event indications event indications indicating one or more errors not associated with analyte sensor 375 may be generated and root causes that may correspond to each of these event indications may be determined, as well.
  • event indications indicating one or more errors not associated with analyte sensor 375 may include one or more errors associated with transmitter 360, an application (e.g., analyte sensor application 330) executed by processor 335, or one or more other devices connected to processor 335 and/or applications executing on such connected
  • processor 335 of the continuous analyte monitoring system may be configured to, not only receive event indication data from transmitter 360, but also generate event indication data for performing root cause analysis.
  • processor 335 of FIG. 3B may generate a plurality of event indications and process the event indications to determine one or more root causes.
  • FIG.9 illustrates a flow chart 900 associated with an example method for automatically self-diagnosing and resolving performance problems detected and associated with a transmitter, an application, one or more other connected devices, or applications executing on such connected devices and associated with a continuous analyte monitoring system, in accordance with embodiments of the present technology.
  • the operations 900 may be performed, for example, by components of a continuous analyte monitoring system, such as components of continuous analyte monitoring system 302 shown in FIG. 3B.
  • operations 900 may be performed by at least analyte sensor 375, transceiver 360 (also referred to herein as transmitter 360), and processor 335 of continuous analyte monitoring system 302 illustrated in FIG. 3B.
  • Operations 900 of FIG. 9 may, for example, be performed when transmitter 360 is unable to communicate with processor 335. Accordingly, only event indications generated by processor 335 may be analyzed to determine one or more root causes.
  • operations 900 begin by a processor (e.g., processer 335) generating an event indication indicative of one or more errors associated with a transmitter (e.g., transmitter 360), an application (e.g., analyte sensor application 330) executed by the processor (e.g., processor 335), one or more other connected devices, or one or more applications executing on the one or more other connected devices.
  • a processor e.g., processer 335
  • an application e.g., analyte sensor application 330
  • the processor e.g., processor 335
  • one or more other connected devices e.g., one or more applications executing on the one or more other connected devices.
  • Each of the plurality of event indications generated by processor 335 may indicate errors, including but not limited to, (1) errors related to a battery and warranty period of transmitter 360, (2) errors related to initial pairing of transmitter 360 and processor 335, (3) errors related to a lost connection between transmitter 360 and processor 335, (4) errors related to an inability of processor 335 to connect to a server (e.g., server system 334), (5) errors related to a lost connection between processor 335 and server system 334, (6) errors related to authorization failure at server system 334, (7) errors related to internal server system 334 issues, (8) errors related to an inability of processor 335 to connect to one or more other devices, (9) errors related to a lost connection between processor 335 and one or more other devices, (10) errors related to the receipt of incorrect data at processor 335 by a third-party application, or any combination thereof.
  • Event indications indicating errors associated with the transmitter may be generated when transmitter 360 is not functioning properly, for example, transmitter 360 is unable to communicate analyte date and/or one or more event indications (described with respect to FIG. 8) to processor 335.
  • event indications indicating errors related to a battery and warranty period of transmitter 360 may be generated by processor 335 when there is an issue with a battery of transmitter 360 and transmitter 360 is unable to communicate with processor 335.
  • event indications indicating errors related to an initial pairing of transmitter 360 and processor 335 may be generated by processor 338 when an initial pairing between transmitter 360 and processor 335 has failed, essentially identifying that processor 335 cannot find transmitter 360.
  • event indications indicating errors related to an inability of processor 335 to connect to server system 334 and errors related to a lost connection between processor 335 and server system 334 may be generated by processor 335 when a host/domain name of server system 334 cannot be found by processor 335, a time out error occurs, connection is refused by server system 334, or server system 334 fails to produce a response within a predetermined set time.
  • a time out error may occur when server system 334 is located using its host/domain name, but a connection is unable to be established to a port of server system 334 within a predetermined amount of time.
  • a connection refused by server system 334 may occur when server system 334 is found by processor 335 using its host/domain name, but server system
  • Server system 334 refuses to accept the connection to processor 335.
  • Server system 334 may fail to produce a response within a predetermined set time when server system 334 is located using its host/domain name and a connection is established with a port of server system 334, but server system 334 does not respond with a predetermined amount of time.
  • event indications indicating errors related to authorization failure at server system 334 may be generated by processor 335 when the pairing requires user authentication and processor 335 has failed to accurately provide authorization.
  • event indications indicating errors related to internal server system 334 issues may be generated by processor 335 when server system 334 encounters an unexpected condition which prevents server system 334 from fulfilling a request (e.g., unable to push requested reports back to processor 335).
  • event indications indicating errors related to one or more other connected devices e.g., sensor devices including a pump, other analyte sensors, third-party devices such as FitBit, etc.
  • applications executing thereon may be generated by processor
  • processor 335 when processor 335 is unable to connect to the one or more other devices, when there is a lost connection between processor 335 and one or more other devices, or when processor 335 receives incorrect data from a third-party application.
  • processor 335 may be configured to generate a plurality of sensor-triggered event indications (e.g., event indications indicating one or more errors associated with analyte sensor 375), instead of these event indications being generated by transmitter 360, as illustrated with respect to FIG. 8.
  • sensor-triggered event indications e.g., event indications indicating one or more errors associated with analyte sensor 375
  • processor 335 after generating these event indications, may analyze whether a root cause of the generation of these indications corresponds to a prematurely failing transmitter 360, an already failed transmitter 360, errors that may based, at least in part, on some other reason (e.g., user error), explained in detail below, and may be fixed by configuring processor 335 to take one or more corrective actions, or errors that may be associated with other connected devices or applications executing thereon.
  • some other reason e.g., user error
  • operations 900 continue by the processor (e.g., processer 335) determining one or more root causes associated with the event indication generated by the processor.
  • processor 335 may be further configured to determine whether a warranty period associated with transmitter 360 has expired.
  • any malfunction or failure occurring under normal use with respect to the transmitter 360 may result in replacement of transmitter 360 at no cost to the patient.
  • transmitter 360 may be replaced at the patient’s expense.
  • the one or more root causes may include that transmitter 360 is failing or transmitter 360 which has already failed.
  • a user when activating transmitter 360, a user must follow steps provided on a display device housing processor 335 or an application executed by processor 335. The user may scan or manually enter the serial number of transmitter 360 for pairing. The application or display device may scan for that serial number, and where a match is found, a connection may be established between transmitter 360 and processor 335. Where “handshaking” between transmitter 360 and processor 335 is accomplished, the pairing may be considered to be successful; however, in cases where transmitter 360 is failing, or has already failed, “handshaking” between transmitter 360 and processor 335 may not be successful. For example, transmitter 360 may be dead, thus no serial number may be located by processor 335 for coordination of the pairing.
  • the one or more root causes may include a failure to activate transmitter 360 based, at least in part, on entry of an inaccurate serial number.
  • Each serial number may be a unique, identifying number or group of numbers and letters assigned to every manufactured transmitter 360; therefore, entry of an incorrect serial number may create user error affecting an ability of processor 335 to pair with transmitter 360.
  • the one or more root causes may include a failure to activate transmitter 360 based, at least in part, on failure to acknowledge a pairing popup message.
  • a user may be required to acknowledge (e.g., accept the pairing terms, conditions, etc.) a pop-up message on a user’s display device (e.g., an iOS pop-up message on a user’s phone) to complete the pairing.
  • a pop-up message may appear asking the user whether a Bluetooth pairing to a device attempting to connect to the user’s display device may be allowed.
  • the pairing may be incomplete thereby causing processor 335 to generate an event indication indicating such an error.
  • processor 335 may determine an issue exists with respect to the connection when, after a threshold amount of time (e.g., fifteen minutes), processor 335 has not received one or more signals (e.g., packets) from transmitter 360.
  • the connection loss may be related to an issue with transmitter 360 or an issue with the application executed by processor 335 (e.g., application has been swipe killed, application malfunction, Bluetooth malfunction, etc.).
  • the one or more root causes may include transmitter 360 is failing or transmitter 360 has already failed.
  • the event indication may indicate an error comprising a permanent loss of connection, thus, transmitter 360 may need to be replaced.
  • processor 335 may be further configured to indicate to a user to take one or more remedial actions. As a first action, processor 335 may request the user confirm the application is still running, and if not, the user may be requested to open the application. For example, a user may have inadvertently swipe killed the application causing the application to not be running in the background.
  • the one or more root causes may indicate a problem exists with respect to a domain name system (DNS) or connectivity to the DNS.
  • DNS domain name system
  • the one or more root causes may indicate an issue with one or more routers or a firewall, a web server hardware failure, or general internet connectivity problems.
  • the one or more root causes may indicate a problem exists with web server software.
  • the one or more root causes may indicate an issue with web server software or back-end systems or an overloaded server.
  • the one or more root causes may indicate processor 335 has failed to accurately provide authorization or an issue with server system 334 because although server system 334 may understand the authorization request server system 334 is refusing to fulfill it.
  • the one or more root causes may indicate an issue with server system 334.
  • the generated event indication indicates errors related to one or more other connected devices (e.g., sensor devices including a pump, other analyte sensors, third-party devices such as FitBit, etc.) and/or applications executing thereon
  • the one or more root causes may indicate an issue with one or more other connected devices and/or applications executing thereon.
  • operations 900 continue by the processor (e.g., processer 335) taking one or more actions to resolve the one or more root causes.
  • processor 335 may engage in recommendation generation and implementation (e.g., in accordance with the fourth step of the root cause analysis process).
  • processor 335 may be configured to take one or more actions to resolve the one or more root causes.
  • the one or more actions may include actions described below for each of the identified root causes.
  • one or more actions may include processor 335 indicating to a user to order a new transmitter for the patient.
  • one or more actions may include processor 335 ordering a new transmitter for the patient.
  • Processor 335 may therefore order a replacement transmitter to be shipped to the patient.
  • Processor 335 may subsequently create one or more invoices for the patient.
  • the event may be recorded in appropriate company accounting databases as a tax-deductible eligible event.
  • processor 335 may determine the delivery and shipment speed appropriate for the patient based on the urgency of the need to deliver a new replacement transmitter.
  • processor 335 may check the patient records to determine whether multiple transmitters have been ordered within a short period of time. If the patient records show that the patient has ordered multiple transmitters within a short period of time, processor 335 may flag the error ticket and request intervention from tech support personnel, by sending an email, on-screen alert or other means of communication.
  • one or more actions may include indicating to a user to re-scan or re-enter the serial number of transmitter 360 for pairing. In some embodiments, one or more actions may include indicating to a user to re-attempt placement of the transmitter such that it is correctly installed with respect to other components of continuous analyte monitoring system 302. In some embodiments, one or more actions may include indicating to a user that a previous pairing pop-up has failed to be acknowledged and further indicate to the user to attempt pairing again by re-installing transmitter 360 and acknowledging the pairing pop-up message. [0312] As described previously, in some embodiments, one or more actions may include indicating to a user to take one or more remedial actions.
  • one or more actions may include indicating to a user to check whether one or more other connected devices (e.g., sensor devices including a pump, other analyte sensors, third-party devices such as FitBit, etc.) and/or applications executing thereon are running properly. Further, processor 335 may indicate to the user to fix a connected device and/or an applications executing thereon if the user determines an issue is present.
  • other connected devices e.g., sensor devices including a pump, other analyte sensors, third-party devices such as FitBit, etc.

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Abstract

Selon certains aspects, la présente invention concerne des procédés et des systèmes d'assistance technique de systèmes de surveillance continue d'analyte et de capteur. Selon certains aspects, un procédé consiste à détecter, par un capteur d'analyte, des niveaux d'analyte d'un patient pour générer un ou plusieurs signaux détectés. Le procédé consiste en outre à générer, par un émetteur, une pluralité d'indications d'événement sur la base du ou des signaux détectés. Le procédé consiste en outre à transmettre, par l'émetteur, la pluralité d'indications d'événement à un processeur. Le procédé consiste également à recevoir la pluralité d'indications d'événement indiquant une ou plusieurs erreurs associées au capteur d'analyte. Le procédé consiste en outre à déterminer une ou plusieurs causes profondes associées à la pluralité d'indications d'événement sur la base d'un motif associé à la pluralité d'indications d'événement. Le procédé consiste également à prendre une ou plusieurs mesures pour résoudre la ou les causes profondes.
EP22777553.3A 2021-09-03 2022-09-01 Systèmes et procédés d'assistance technique de systèmes de surveillance continue d'analyte et de capteur Pending EP4395630A1 (fr)

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US17/467,072 US12033749B2 (en) 2016-11-09 2021-09-03 Systems and methods for technical support of continuous analyte monitoring and sensor systems
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