Patent Application
20220375558
The present disclosure relates to systems, devices and methods for displaying patient data. More particularly, the present disclosure relates to systems, devices, and methods for displaying logged medical and contextual information pertaining to a person with diabetes.
Some persons with diabetes maintain logs and/or records of medical and contextual information pertaining to their condition. Such logs and/or records may include data regarding doses of insulin that they received, such as when such doses were administered and the amount of such doses. Such logs and/or records may also include a historical record of their glucose level measurements. Health care providers may review such records to monitor the person's compliance with their treatment regimen, to detect medical trends or conditions that require treatment, or to identify other issues that require discussion with the person.
The present disclosure relates to systems, devices and methods for displaying patient data. Such patient data may include logged medical and contextual information, such as medications taken, blood glucose levels, errors/alerts/information related to insulin delivery devices, information regarding meals (e.g., types of food ingested, amount of food, time of meals), and factors that may affect the patient's health and/or condition (e.g., illnesses, menstruation, stress, exercise/activity, and the like). More particularly, the present disclosure relates to systems, devices and methods for displaying patient data including logged medical and contextual information pertaining to a person with diabetes. Such logged medical and contextual information may include both glucose events and contextual factors such as manual dose overrides, site changes, and/or missed or late boluses.
Various aspects are described in this disclosure, which include, but are not limited to, the following aspects:
1. A method for displaying selected patient data on a display screen of a computing device, the method comprising: displaying, on the display screen of the computing device, a plurality of panels, each panel associated with a unique time window and displaying one or more glucose measurements for a patient recorded during the unique time window; receiving a first user input selecting at least one glucose event type of a plurality of glucose event types; receiving a second user input selecting at least one contextual factor type of a plurality of contextual factor types; and displaying, on the display screen in response to receiving the first and second user inputs, a subset of panels from the plurality of panels that are visually distinguished over other panels from the plurality of panels not included in the subset, wherein each panel in the subset of panels displays at least one glucose measurement that exhibits the selected at least one glucose event type and was recorded during a time period in which the patient experienced the selected at least one contextual factor type.
2. The method of claim 1, further comprising displaying, on the display screen of the computing device, the plurality of glucose event types and the plurality of contextual factor types separate from the plurality of panels.
3. The method of any of claims 1-2, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually de-emphasizing panels from the plurality of panels that do not belong to the subset by fading, obscuring, shrinking, or de-saturating the de-emphasized panels on the display screen.
4. The method of any of claims 1-2, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises removing, from the display screen in response to receiving the first and second user inputs, panels from the plurality of panels that do not belong to the subset of panels.
5. The method of any of claims 1-4, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually emphasizing the subset of panels on the display screen by changing a color of said subset of panels, adding a border around said subset of panels, adding a symbol to each panel of said subset of panels, or increasing a size of each panel of said subset of panels.
6. The method of any of claims 1-5, wherein the plurality of glucose events comprise at least one of a hypoglygemic event, a nocturnal hypoglycemic event, a hyperglycemic event, and a prolonged hyperglycemic event.
7. The method of any of claims 1-6, wherein the plurality of contextual factors comprise at least one of a user override of an automatic dose increase, a user override of an automatic dose decrease, a late bolus, a manual bolus, a missed bolus, a critical pump alarm, a change of an infusion site, and a suspension of an automatic infusion dosing algorithm.
8. The method of any of claims 1-7, wherein each panel of the plurality of panels displays one or more glucose measurements for a patient recorded during a different day.
9. The method of any of claims 1-8, wherein each panel displays one or more glucose measurements recorded by at least one of a blood glucose monitor (BGM), a continuous glucose monitor (CGM), and a flash glucose monitor (FGM).
10. A computing device comprising: a display screen; at least one processor; and non-transitory computer-readable media storing computer-executable instructions that, when executed by the at least one processor, are operable to cause the at least one processor to: display on the display screen a plurality of panels, each panel associated with a unique time window and displaying one or more glucose measurements for a patient recorded during the unique time window; receive a first user input selecting at least one glucose event type of a plurality of glucose event types; receive a second user input selecting at least one contextual factor type of a plurality of contextual factor types; and display, on the display screen in response to receiving the first and second user inputs, a subset of panels from the plurality of panels that are visually distinguished over other panels from the plurality of panels not included in the subset, wherein each panel in the subset of panels displays at least one glucose measurement that exhibits the selected at least one glucose event type and was recorded during a time period in which the patient experienced the selected at least one contextual factor type.
11. The computing device of claim 10, wherein the at least one processor is further configured to display, on the display screen of the computing device, the plurality of glucose event types and the plurality of contextual factor types separate from the plurality of panels.
12. The computing device of any of claims 10-11, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually de-emphasizing panels from the plurality of panels that do not belong to the subset by fading, obscuring, shrinking, or de-saturating the de-emphasized panels on the display screen.
13. The computing device of any of claims 10-11, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises removing, from the display screen in response to receiving the first and second user inputs, panels from the plurality of panels that do not belong to the subset of panels.
14. The computing device of any of claims 10-13, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually emphasizing the subset of panels on the display screen by changing a color of said subset of panels, adding a border around said subset of panels, adding a symbol to each panel of said subset of panels, or increasing a size of each panel of said subset of panels.
15. The computing device of any of claims 10-14, wherein the plurality of glucose events comprise at least one of a hypoglygemic event, a nocturnal hypoglycemic event, a hyperglycemic event, and a prolonged hyperglycemic event.
16. The computing device of any of claims 10-15, wherein the plurality of contextual factors comprise at least one of a user override of an automatic dose increase, a user override of an automatic dose decrease, a late bolus, a manual bolus, a missed bolus, a critical pump alarm, a change of an infusion site, and a suspension of an automatic infusion dosing algorithm.
17. The computing device of any of claims 10-16, wherein each panel of the plurality of panels displays one or more glucose measurements for a patient recorded during a different day.
18. The computing device of any of claims 10-17, wherein each panel displays one or more glucose measurements recorded by at least one of a blood glucose monitor (BGM), a continuous glucose monitor (CGM), and a flash glucose monitor (FGM).
19. Non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, are operable to cause the one or more processors to: display, on a display screen of a computing device, a plurality of panels, each panel associated with a unique time window and displaying one or more glucose measurements for a patient recorded during the unique time window; receive a first user input selecting at least one glucose event type of a plurality of glucose event types; receive a second user input selecting at least one contextual factor type of a plurality of contextual factor types; and display, on the display screen in response to receiving the first and second user inputs, a subset of panels from the plurality of panels that are visually distinguished over other panels from the plurality of panels not included in the subset, wherein each panel in the subset of panels displays at least one glucose measurement that exhibits the selected at least one glucose event type and was recorded during a time period in which the patient experienced the selected at least one contextual factor type.
20. The non-transitory computer-readable media of claim 19, wherein the computer-executable instructions, when executed by the one or more processors, are further operable to cause the one or more processors to display, on the display screen of the computing device, the plurality of glucose event types and the plurality of contextual factor types separate from the plurality of panels.
21. The non-transitory computer-readable media of any of claims 19-20, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually de-emphasizing panels from the plurality of panels that do not belong to the subset by fading, obscuring, shrinking, or de-saturating the de-emphasized panels on the display screen.
22. The non-transitory computer-readable media of any of claims 19-20, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises removing, from the display screen in response to receiving the first and second user inputs, panels from the plurality of panels that do not belong to the subset of panels.
23. The non-transitory computer-readable media of any of claims 19-22, wherein displaying the subset of panels that are visually distinguished over other panels from the plurality of panels not included in the subset comprises visually emphasizing the subset of panels on the display screen by changing a color of said subset of panels, adding a border around said subset of panels, adding a symbol to each panel of said subset of panels, or increasing a size of each panel of said subset of panels.
24. The non-transitory computer-readable media of any of claims 19-23, wherein the plurality of glucose events comprise at least one of a hypoglygemic event, a nocturnal hypoglycemic event, a hyperglycemic event, and a prolonged hyperglycemic event.
25. The non-transitory computer-readable media of any of claims 19-24, wherein the plurality of contextual factors comprise at least one of a user override of an automatic dose increase, a user override of an automatic dose decrease, a late bolus, a manual bolus, a missed bolus, a critical pump alarm, a change of an infusion site, and a suspension of an automatic infusion dosing algorithm.
26. The non-transitory computer-readable media of any of claims 19-25, wherein each panel of the plurality of panels displays one or more glucose measurements for a patient recorded during a different day.
27. The non-transitory computer-readable media of any of claims 19-26, wherein each panel displays one or more glucose measurements recorded by at least one of a blood glucose monitor (BGM), a continuous glucose monitor (CGM), and a flash glucose monitor (FGM).
The above-mentioned and other features and advantages of this disclosure, and the manner of attaining them, will become more apparent and will be better understood by reference to the following description of embodiments of the invention taken in conjunction with the accompanying drawings, wherein:
Corresponding reference characters indicate corresponding parts throughout the several views. The exemplifications set out herein illustrate exemplary embodiments of the invention and such exemplifications are not to be construed as limiting the scope of the invention in any manner.
Persons with diabetes may maintain logs and/or records of the doses of insulin that they received, as well as of their glucose level measurements. Such logs and/or records may also sometimes be supplemented with contextual factors. Such contextual factors can include whether the dose they received was calculated by a bolus calculator, and if so, whether the dose they received was higher or lower than the dose recommended by the calculator. Such contextual factors may also include data regarding whether and/or when the person missed a bolus or took a bolus late, whether and/or when an automatic insulin delivery device of the person experienced a critical failure (e.g., an occlusion), or whether and/or when the person changed an infusion site of the automatic insulin delivery device.
Health care providers may review such logs and/or records with the person to monitor the person's compliance with their treatment regimen, to detect medical trends or conditions that require treatment, or to identify other issues that require discussion with the person. However, as the amount of information contained in the person's log and/or records increases, health care providers (HCPs) may find it increasingly difficult to quickly accomplish these tasks. Accordingly, there is a need to provide a user interface that quickly allows HCPs to filter and sort through the person's records to identify medical issues that require discussion or treatment.
Furthermore, correlations between logged events may sometimes indicate deeper issues that require discussion or treatment, or may reveal insights into the root causes of persistent medical issues. For example, a consistent trend of undesirably high glucose levels (e.g., a relatively high number of hyperglycemic events) in a person's glucose record may be due to a large number of factors. Without pinpointing the root cause of such high glucose levels, a HCP may not be able to counsel the person effectively on how to avoid such hyperglycemic events in the future.
However, if the HCP observes that the person's hyperglycemic events tend to be correlated with days where the person manually overrides a calculated bolus dose downward (i.e., a downward dose override), the HCP may reasonably infer that the person suffers from a fear of hypoglycemia. In this scenario, the HCP may refer the person to education and/or resources that help the person overcome his/her fear of hypoglycemia and gain better judgment on when to override a bolus dose suggested by his/her bolus calculator.
On the other hand, if the HCP observes that the person's hyperglycemic events tend to be correlated with days where the person's automated insulin delivery device has a critical low insulin reservoir alarm (e.g., the device is running out of insulin), the HCP may reasonably infer that the person tends not to refill his/her insulin delivery device often enough. In this scenario, the proper course of action may be to better educate the person on how to maintain and/or refill his/her insulin delivery device, or potentially to inquire into whether the person requires financial assistance in obtaining needed insulin.
As yet another example, if the HCP observes that the person's hyperglycemic events tend to be correlated with days where the person has a missed bolus or a late bolus, the HCP may reasonably infer that the person has trouble remembering to take a bolus of insulin with every meal. Indeed, if the person's records indicate the person has no trouble taking a bolus at dinner time but tends to have trouble taking a bolus at lunch time, the HCP may infer that the person has difficulty taking a bolus at his/her work place in particular. In this scenario, the proper course of action may be to work with the person to devise a system or to form habits that help the person take boluses with every meal.
As this simple example illustrates, a single glucose event (e.g., a hyperglycemic event) may be caused by different root causes, each of which may be best addressed using different strategies. By correlating observed glucose events with contextual factors, HCPs may derive valuable insights into the root causes behind such glucose events and thereby devise effective strategies in preventing such glucose events in the future. Accordingly, there is a need to provide a user interface that quickly allows HCPs to correlate observed glucose events (e.g., hypoglycemic or hyperglycemic events) with contextual factors (e.g., manual dose overrides, or critical alarms related to the person's insulin delivery device). The systems, methods, and apparatus disclosed herein are configured to help address at least some of the above-described needs.
The HCP system 102 (including the display 120) is described from a physical-architecture standpoint more fully below in connection with
In various different embodiments, the HCP system 102 may implement a HCP portal application or interface that provides and supports functions such as prescribing medication-dosing regimens (e.g., insulin-dosing regimens such as basal-insulin-dosing regimens, bolus-insulin-dosing regimens, and/or the like), modifying existing dosing-regimen prescriptions, setting and/or modifying dosing-regimen parameters, and viewing individual patient data, among other examples that could be listed here. The prescription and parameter-setting with respect to dosing regimens by an HCP via the HCP system 102 assists patients in determining medication doses. Among other functions, the HCP system 102 provides the HCP with the capability to download patient EHR data from the health IT system 118 via the communication link 116 and view the EHR data in the HCP portal, view a selection of available medication-dosing regimens, select a dosing regimen to prescribe to the patient, and assign values to required parameters for the selected dosing regimen (such as starting dose, insulin-to-carb ratio, and the like, in the example case of an insulin-dosing regimen). The HCP portal on the HCP system 102 further provides data-visualization features that enable the HCP users to review patient historical data, as described in further detail below. In various embodiments, this patient historical data is viewable in chart form, graphical form, tabular form, and/or one or more other forms deemed suitable by those of skill in the art for a given implementation.
The mobile device 104 (including the display 122) is described from a physical-architecture standpoint more fully below in connection with
With respect to the C3-server system 106, an example one of the C3 servers 140-146 is described from a physical-architecture standpoint more fully below in connection with
It is noted that, as depicted in
As a general matter, the C3-server system 106 functions as “the cloud” as that term is used in the art with respect to entities such as the HCP system 102, the health IT system 118, and the mobile device 104 (and in particular to one or more applications executing on the mobile device 104). In some embodiments, a subset of C3 servers 140-146 may be dedicated to serving at least one of the HCP system 102, the health IT system 118, and the mobile device 104. In some embodiments, however, each of the C3 servers 140-146 may be capable of serving any of these three entities. Regardless of the specific architectural implementation, the C3-server system 106 functions as at least one cloud with particular purposes for those entities. As such, in at least one embodiment, all communication to and from the C3-server system 106 with any one or more other entities is secure communication—as examples, such communication could be encrypted and/or signed as is known in the art. Such communication could be inside a tunnel such as a VPN, among other communication-security and data-security options that could be implemented as deemed suitable by those of skill in the art in various contexts.
In various different embodiments, and as is further described below, the C3-server system 106 provides and supports functions—for the mentioned entities and perhaps others-such as secure and reliable transfer of information and data (related to, e.g., prescriptions, patient-tracked and shared health data) between the HCP system 102 and applications running on mobile devices associated with patients, data storage, management of relationships between patients and HCPs, Integrated Delivery Networks (IDNs, e.g., a network of health care organizations), and the like, and in some embodiments, instead or in addition, provides and supports one or more other functions deemed suitable by those of skill in the art for a given implementation. Moreover, in some embodiments, the C3-server system 106 facilitates data sharing that involves payers (e.g., insurance companies); in some such embodiments, such data sharing with payer entities is conditional upon the associated patients opting in to allow such communication. And other examples of provided and supported functions could be listed here as well.
The administrator-portal system 148 is described from a physical-architecture standpoint more fully below in connection with
As a general matter, in various different embodiments, the administrator-portal system 148 provides various services with respect to the HCP-portal 102, an application (e.g., a Mobile Medical Application, or MMA) executing on the mobile device 104, and/or the C3-server system 106. One example category of such services are those that pertain to user management, login, access level, and the like. In at least one embodiment, a user with sufficient permissions can use the administrator-portal system 148 to change and/or manage various settings of the HCP-portal 102, an MMA executing on the mobile device 104, and/or the C3-server system 106. In some cases, changes made via the administrator-portal system 148 affect only a single MMA, a single user, a single HCP, and/or the like; in other cases, such changes affect multiple MMAs, multiple user accounts, multiple HCPs, and/or the like. For example, an IDN may be provided with an administrator-portal system 148 that governs accounts of patients enrolled in the IDN. In some embodiments, the administrator-portal system 148 is operable to roll out updates, upgrades, and the like. In some embodiments, the administrator-portal system 148 is operable to manage individual HCP accounts, individual patient accounts, and/or the like. And certainly numerous other example administrative functions for which the administrator-portal system 148 could be used could be listed here.
In the example environment that is depicted in
As used herein, a “communication link” includes one or more wired-communication (e.g., Ethernet, Universal Serial Bus (USB), and/or the like) links and/or one or more wireless-communication (e.g., cellular, Wi-Fi, Bluetooth, and/or the like), and may also include any suitable number of relay devices such as routers, switches, bridges, and/or the like. The communication link 112 in particular may include at least one wireless-communication link to facilitate two-way data communication with the mobile device 104. Moreover, either or both of the communication links 128 and 136 may take the form of or at least include at least one of a near-field communication (NFC) link, a Bluetooth link, a radio-frequency identification (RFID) link, a direct radio frequency (RF) link, and/or one or more other types of wireless-communication links. Moreover, the communication links 128 and 136 could but need not be point-to-point links between (i) the mobile device 104 and (ii) the glucose meter 126 and connected injection device 134, respectively: in some embodiments, one or both of the communication links 128 and 136 are an indirect link via, e.g., a Wi-Fi or ZigBee router, or a cellular network or tower (not depicted). And other implementation examples could certainly be listed here as well.
In the example scenario that is depicted in
In the example scenarios described herein, the patient 124 has been diagnosed with diabetes and is being treated by an HCP that is associated with the HCP system 102, though this is purely by way of example and not limitation. In the described embodiments, both the mobile device 104 (and at least one MMA running thereon), the glucose meter 126, and the connected injection device 134 are each associated with the patient 124, and in at least that way with one another. The above-mentioned association arrow 125 is intended to represent a general association and a user-interface-level interaction of the patient 124 with the mobile device 104.
It is further noted that while
The glucose meter 126 is associated with the patient 124 for medical, diabetes-treatment purposes, and is communicatively connected with the mobile device 104 via the above-described communication link 128. The glucose meter 126 could include a blood-glucose meter (BGM), a continuous glucose meter (CGM), a flash glucose monitor (FGM), or other devices that measure the patient 124's blood glucose or other sources of glucose levels (e.g., contact lens devices, or devices that use near IR radiation to measure glucose levels). A BGM takes discrete spot measurements of the patient's blood-glucose level (e.g., by pricking the patient's finger to conduct spot measurements of the patient's capillary whole blood glucose level). Both CGM and FGM use sensors to measure interstitial glucose. A CGM system may include a sensor, transmitter and receiver/app. A CGM may take more frequent (i.e., more continuous) measurements of the patient's interstitial glucose levels and may optionally be continuously worn by the patient for relatively extended periods of time (e.g., several hours or days at a time). One example of such a CGM is the G6 sensor manufactured by Dexcom, Inc. A FGM system may comprise a sensor worn on or inserted into a portion of the patient's body, and a reader (e.g., a handheld reader) that, when activated or when placed in close proximity to the sensor, receives a glucose level reading from the sensor. One example of such a FGM is the FreeStyle Libre device, manufactured by Abbott Diabetes Care Inc. In some embodiments, a FGM does not require finger-stick calibration. Other types of glucose meters may be provided as well.
CGM and FGM systems may measure interstitial glucose levels, while BGM systems may measure blood glucose levels. For simplicity and readability, this disclosure refers simply to a “glucose” level, or “GL.” It is understood that such references may refer to either blood glucose or interstitial glucose, as appropriate.
The connected injection device 134 is also associated with the patient 124 for medical, diabetes-treatment purposes, and is communicatively connected with the mobile device 104 via the above-described communication link 136. Device 134 may further comprise a drug or medication. In some embodiments, a system may comprise one or more devices including device 134 and a drug or medication. The term “drug” or “medication” refers to one or more therapeutic agents including but not limited to insulins, insulin analogs such as insulin lispro or insulin glargine, insulin derivatives, glucagon, glucagon analogs, glucagon derivatives, and any therapeutic agent that is capable of delivery by the above device. The drug or medication as used in the device 134 may be formulated with one or more excipients. The device is operated in a manner generally as described herein by a patient, caregiver or healthcare professional to deliver the drug to a person.
In at least one embodiment, the connected injection device 134 is or at least includes what is referred to at times in the art as a connected insulin-delivery device (e.g., a connected insulin pen, such as a pen having integrated and/or attachable electronics to auto-detect and report to another electronic device an amount of injected insulin). In various different embodiments, the connected injection device 134 takes the form of or includes one or more of the insulin-delivery devices described in any of the following patent applications, each of which is hereby incorporated herein by reference in its respective entirety:
In some embodiments, the connected injection device 134 takes the form of an automated insulin delivery device, such as an insulin pump. Such automated insulin delivery devices may include a reservoir sized to carry sufficient basal and/or bolus insulin for multiple doses and may be configured to be worn on or attached to the patient 124's body. The device may automatically infuse such basal and/or bolus insulin into the patient's body via an infusion set attached to the patient's body, e.g., the patient's abdomen, back, or arm. One example of an automated insulin delivery device is the MiniMed™ 670G Insulin Pump System, manufactured and sold by Medtronic PLC. In yet other embodiments, the mobile device 104 may be communicably coupled to two or more injection devices 134, such as both a connected insulin pen as well as an automated insulin delivery device.
Moreover, in some cases, one or more of the capabilities of one of those two devices in this disclosure are also or instead covered by the other of those two devices and/or by one or more additional devices. In one example, a single device can both monitor glucose (and report back results) and inject insulin (and report back injected amounts). And certainly other combinations of capabilities could be listed here.
Furthermore, and as also described below, in some embodiments, an MMA executing on the mobile device 104 communicates for various reasons (e.g., sending dosing commands, receiving dosed-amount confirmation reports, requesting (e.g., glucose) readings, receiving one or more measured values, and/or the like) with one or more connected medical devices such as the example glucose meter 126 and connected injection device 134. Such communication may be in one-way or two-way manner with a given device. Additional examples of information that could be conveyed from a connected medical device to an MMA include error codes, device metrics, dosing records, and/or dosing confirmations. And certainly other examples could be listed here. Moreover, in some cases, direct communication links exist between various connected medical devices, such as between the glucose meter 126 and the connected injection device 134.
The conceptual-information-flow arrow 130 is meant to graphically and conceptually depict that, among other information and as is described more fully below, the HCP system 102 may transmit, either directly, via data network 108, via the C3-server system 106, or via some other intermediate component or network, HCP-selected medication-dosing-regimen (e.g., bolus-dosing-regimen) prescriptions to the MMA executing on the mobile device 104. Similarly, the conceptual-information-flow arrow 132 is meant to graphically and conceptually depict that, among other information and as is described more fully below, the MMA executing on the mobile device 104 may transmit, either directly or via the C3-server system 106, patient-tracked and patient-shared health data regarding the patient's diabetes and/or one or more other health-related conditions, topics, and the like.
As a general matter, it should be understood that any of the entities described herein, including but not limited to the HCP system 102, the health IT system 118, the mobile device 104 (including an MMA executing thereon), the C3-server system 106, and the administrator-portal system 148—may communicate in at least one embodiment with any other of those entities without being required to route that communication through one or more other entities. For example, in at least one embodiment, the HCP system 102 and the mobile device 104 can exchange information without that information having to pass through the C3-server system 106. In some embodiments, however, one or more entities communicate with one another via at least one additional entity; as an example, in at least one embodiment, data (e.g., HCP-selected-regimen data) is communicated from the HCP system 102 to the MMA executing on the mobile device 104 via the C3-server system 106.
Further details regarding and exemplary embodiments of communication context 100 are described in International App. No. PCT/US19/42507, filed Jul. 19, 2019 and entitled SYSTEMS AND METHODS FOR REMOTE PRESCRIPTION OF MEDICATION-DOSING REGIMENS, the entire contents of which are incorporated herein by reference.
An illustrative implementation of a computer system 200 that may be used to perform any of the aspects of the methods/processes and embodiments disclosed herein is shown in
In connection with techniques described herein, software or firmware code used to, for example, display logged data pertaining to a person with diabetes may be stored on one or more computer-readable storage media of computer system 200. Processor 210 may execute any such code to provide any techniques for planning an exercise as described herein. Any other software, programs or instructions described herein may also be stored and executed by computer system 200. It will be appreciated that computer code may be applied to any aspects of methods and techniques described herein.
The various methods or processes outlined herein may be coded as software that is executable on one or more processors that employ any one of a variety of operating systems or platforms. Additionally, such software may be written using any of numerous suitable programming languages and/or programming or scripting tools, and also may be compiled as executable machine language code or intermediate code that is executed on a virtual machine or a suitable framework.
In this respect, various inventive concepts may be embodied as at least one non-transitory computer readable storage medium (e.g., a computer memory, one or more floppy discs, compact discs, optical discs, magnetic tapes, flash memories, circuit configurations in Field Programmable Gate Arrays or other semiconductor devices, etc.) encoded with one or more programs that, when executed on one or more computers or other processors, implement the various embodiments of the present invention. The non-transitory computer-readable medium or media may be transportable, such that the program or programs stored thereon may be loaded onto any computer resource to implement various aspects of the present invention as discussed above.
The terms “logic”, “control logic”, “program”, “software”, “application”, “method” and/or “process” are used herein in a generic sense to refer to any type of computer code or set of computer-executable instructions that can be employed to program a computer or other processor to implement various aspects of embodiments as discussed above. Additionally, it should be appreciated that according to one aspect, one or more computer programs that when executed perform methods of the present disclosure need not reside on a single computer or processor, but may be distributed in a modular fashion among different computers or processors to implement various aspects of the present invention.
Computer-executable instructions may be in many forms, such as program modules, executed by one or more computers or other devices. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. Typically, the functionality of the program modules may be combined or distributed as desired in various embodiments. Such computer code or computer-executable instructions may take the form of software and/or firmware executing on one or more programmable processors, field-programmable gate arrays (FPGAs), and/or digital signal processors. All or a portion of such code or instructions may also alternatively be implemented in the form of hardwired circuitry on, for example, an application-specific integrated circuit (ASIC).
Also, data structures may be stored in non-transitory computer-readable storage media in any suitable form. Data structures may have fields that are related through location in the data structure. Such relationships may likewise be achieved by assigning storage for the fields with locations in a non-transitory computer-readable medium that convey relationship between the fields. However, any suitable mechanism may be used to establish relationships among information in fields of a data structure, including through the use of pointers, tags or other mechanisms that establish relationships among data elements.
At step 302, process 300 displays on the display screen of the computing device a plurality of panels, each panel displaying one or more glucose measurements for a person with diabetes recorded at different time periods. As used herein, a “panel” may refer to a group or collection of visual data including text, symbols, and/or graphics generated by a processor for display on a defined area of a visual display screen. The defined area of a “panel” need not be square or rectangular but may take any shape; furthermore, the defined area of a “panel” is not limited to a subset of the display screen but may, in some embodiments, encompass the entire visible area of the display screen. A “panel” may comprise multiple “sub-panels”, as discussed in further detail herein. Also as used herein, “glucose measurements” may refer to measurements taken of the person's blood glucose or interstitial glucose levels. Such glucose measurements may have been logged by mobile device 104 based on manual user input from patient 124, or from data received from glucose meter 126 via communication link 128. Also as used herein, a time at which a glucose measurement is “recorded” may refer to a time at which the glucose measurement was detected or measured by a glucose sensor, a time at which the glucose measurement was transmitted to a glucose sensor and/or received by a mobile device (e.g., a smartphone), a time at which the glucose measurement was input into a mobile device by a user, and/or a time at which the glucose measurement was uploaded by the mobile device to a cloud server.
For clarity,
Glucose measurement sub-panel 610 includes a horizontal time axis 612 which indicates the passage of time from 12 am in the morning until 12 am the next day. Sub-panel 610 also includes a vertical axis 614 which indicates glucose levels, e.g., in units of mg/dL. Sub-panel 610 includes a glucose measurement line 616 which displays glucose measurements taken of the person at different times on July 10. For example, such glucose measurements may be taken by glucose meter 126 and received and logged by mobile device 104 (see
Bolus dosing sub-panel 630 depicts a plurality of blocks 632 indicating corrective bolus doses administered to the person, and a plurality of blocks 636 indicating meal bolus doses administered to the person. As used herein, a “meal” bolus dose may refer to a bolus dose taken to counteract a rise or expected rise in glucose levels resulting from a meal. A “corrective” bolus dose may refer to a bolus dose not taken in association with a specific meal, but in order to counteract an abnormally high glucose level. Each block 632 and block 636 is arranged horizontally to correspond with the time scale depicted on horizontal time axis 612, such that each block's horizontal position relative to horizontal time axis 612 indicates the time at which that block's bolus dose was administered to the person. Each block's height is scaled in proportion to the amount of insulin administered at that bolus. In the example depicted in
Bolus dosing sub-panel 630 may further include one or more downward dose override indicators 634 (shaped as a downward pointing triangle shaded in solid black) and/or one or more upward dose override indicators 638 (shaped as an upward pointing triangle shaded in white). A downward dose override indicator 634 positioned on top of a particular bolus dose block indicates that a computing device (e.g., a device having a bolus advisor or bolus calculator implemented thereon) had recommended that the person take more insulin on a particular bolus based on various factors, such as the person's glucose levels, carb intake, and/or amount of active insulin from previous boluses—however, the person took less insulin on that bolus than recommended (e.g., the device had recommended the person take 12 units of insulin, but the person only took 10 units). An upward dose override indicator 638 positioned on top of a particular bolus dose block indicates that the computing device had recommended that the person take less insulin on a particular bolus (again based on various factors), but the person took more insulin on that bolus than recommended (e.g., the device had recommended the person take 10 units of insulin, but the person took 12 units). As discussed in further detail below, a downward dose override or an upward dose override are examples of contextual factors.
Bolus dosing sub-panel 630 may further include one or more carbohydrate indicators 640. The carbohydrate indicators may indicate the number of carbohydrates that the person ingested in a meal (e.g., 60 grams, 61 grams, and 66 grams at around 6 am, 10 am, and 4 pm respectively in the example depicted in
Basal dosing sub-panel 650 depicts a plurality of blocks 652 indicating auto basal micro-boluses administered to the person, and a plurality of blocks 654 indicating manual basal micro-boluses administered to the person. As used herein, an “auto” basal micro-bolus may refer to a micro-bolus (e.g., a small bolus of basal insulin, in the range of 0.025 units to 1 units) determined and administered automatically to the person by an automated insulin delivery device, such as an insulin pump. In some embodiments, such an “auto” basal micro-bolus may be determined and administered without any manual input by the person at the time the bolus is administered, e.g., without requiring that the person provide any instruction, respond to any prompt, or provide any information or confirmation. Instead, such “auto” basal micro-bolus may be automatically determined by the insulin delivery device based on pre-programmed parameters provided by the person with diabetes, a caregiver, or a health care provider. As used herein, a “manual” micro-bolus may refer to a micro-bolus manually requested by the person. Each block 652 and 654 is arranged horizontally to correspond with the time scale depicted on horizontal time axis 612, such that each block's position along horizontal time axis 612 indicates the time at which that block's micro-bolus was administered to the person. Each block's height is scaled in proportion to the amount of insulin administered during that micro-bolus. In the example depicted in
Basal dosing sub-panel 650 may further include a symbol or indicator 656 that indicates the occurrence of a Predictive Low Glucose Suspend (PLGS). A PLGS occurs when an automated insulin delivery device (e.g., an insulin pump) detects that the person's glucose levels are below or trending towards a hypoglycemic condition, in which case the delivery device may automatically suspend delivery of basal insulin until the person's glucose levels stabilize. Each PLGS indicator 656 is arranged horizontally to correspond with the time scale 612, such that each indicator's position along horizontal time axis 612 indicates the time at which that PLGS event occurred. As discussed in further detail below, a PLGS is an example of a contextual factor.
Although these features are not explicitly labeled in
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Each of the aforementioned glucose events is associated with a user-selectable radio button. A user, such as a health care professional (HCP), a care provider, the person with diabetes, and/or the person's caregiver or loved one, may select one or more of these glucose events by selecting these radio buttons.
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A missed bolus may include a situation where a person with diabetes that requires meal-time insulin has ingested food (such ingestion of food also referred to herein as a “meal event”) without taking an insulin bolus to compensate for an increase in glucose levels resulting from, or expected to result from, the ingested food. A “meal event” or “food” can include any type of food, drink, or meal that can be expected to result in an increase in the user's glucose levels, including without limitation breakfast, lunch, dinner, any snacks, and/or any drinks. A late bolus may include a situation where a person with diabetes that requires meal-time insulin ingests food at a meal event, but takes an insulin bolus too late in time to appropriately compensate for the meal event. This may result in an undesirable spike in the person's glucose levels before the insulin bolus takes effect. Missed boluses and late boluses may be detected by monitoring the person's glucose levels and/or glucose level trends over time and analyzing said glucose levels in conjunction with a log of the person's insulin boluses (e.g., the time and amount of previously administered insulin boluses).
Several exemplary and illustrative methods for detecting missed boluses and/or late boluses based on glucose measurements and insulin dosing information will now be discussed. At least one processor of the aforementioned computer systems may execute software and/or firmware code to implement these methods.
1. Glucose Increase Threshold Method
One exemplary method for detecting missed boluses, referred to herein as the “Glucose Increase Threshold” method, is to determine that the person may have missed an insulin bolus if the following conditions are fulfilled:
(i) the person's glucose level increases by more than a maximum allowable glucose increase threshold (ΔGmax, e.g., 20-60 mg/dL) within a predetermined glucose-consideration time window (TG, e.g., 5-10 minutes) of the current time; and
(ii) the person has not taken an insulin bolus within a predetermined bolus-consideration time period (TB, e.g., 2 hours) of the current time.
The parameters ΔGmax, TG, and TB may be adjusted to make the Glucose Increase Threshold method more or less sensitive. For example, increasing the maximum allowable glucose increase threshold (ΔGmax) would decrease the sensitivity, while decreasing ΔGmax would increase the sensitivity. Increasing the glucose-consideration time window (TG) would increase the sensitivity, while decreasing TG would decrease the sensitivity. Increasing the bolus-consideration time window (TB) would decrease the sensitivity, while decreasing TB would increase the sensitivity.
The Glucose Increase Threshold method may also be used to determine that the person may have taken a bolus late (i.e., that a late bolus event has occurred). The same conditions (i) and (ii) described above may be used to determine whether the person took a bolus late. In some embodiments, a shorter bolus-consideration time period TB may be used to detect late boluses than to detect missed boluses.
2. Glucose Rate-of-Change (“ROC”) Threshold Method
Another exemplary method for detecting missed boluses, referred to herein as the “Glucose ROC Threshold” method, is to determine that the person may have missed an insulin bolus if the following conditions are satisfied:
(i) the person's glucose levels exhibit a rate-of-change (ROCG) that is greater than a maximum allowable glucose rate-of-change threshold (ROCmax, e.g., 2 mg/dL/hr); and
(ii) the person has not taken an insulin bolus within a predetermined bolus-consideration time period (TB, e.g., 2 hours) of the current time.
ROCG may be provided or calculated by some commercially available Continuous Glucose Monitors (CGM), such as the G6 CGM sensor manufactured and sold by Dexcom, Inc. For example, if a glucose sensor records three consecutive glucose readings, each spaced no more than 5 minutes apart from its closest neighbor reading in time, ROCG may be calculated by dividing the difference between the last and the first glucose reading by the amount of time that has elapsed between the first and the last glucose reading. Other methods or devices for calculating ROCG may also be used.
The parameters ROCmax and TB may be adjusted to make the Glucose ROC Threshold method more or less sensitive. For example, increasing ROCmax would decrease the sensitivity, while decreasing ROCmax would increase the sensitivity. Increasing the bolus-consideration time window (TB) would decrease the sensitivity, while decreasing TB would increase the sensitivity.
The Glucose ROC Threshold method may also be used to determine that the person may have taken a bolus late (i.e., that a late bolus event has occurred). The same conditions (i) and (ii) described above may be used to determine whether the person took a bolus late. In some embodiments, a shorter bolus-consideration time period TB may be used to detect late boluses than to detect missed boluses.
3. Absolute Glucose Level Threshold Method
Yet another exemplary method for detecting missed boluses, referred to herein as the “Absolute Glucose Level Threshold” method, is to determine that the person may have missed an insulin bolus if the following conditions are satisfied:
(i) the person's glucose levels exceed an absolute glucose level threshold (Gmax, e.g., 180 mg/dL); and
(ii) the person has not taken an insulin bolus within a predetermined bolus-consideration time period (TB, e.g., 2 hours)
The parameters Gmax and TB may be adjusted to make the Absolute Glucose Level Threshold method more or less sensitive. For example, increasing the maximum allowable glucose threshold (Gmax) would decrease the sensitivity, while decreasing Gmax would increase the sensitivity. Increasing the bolus-consideration time window (TB) would decrease the sensitivity, while decreasing TB would increase the sensitivity.
The Absolute Glucose Level Threshold method may also be used to determine that the person may have taken a bolus late (i.e., that a late bolus event has occurred). The same conditions (i) and (ii) described above may be used to determine whether the person took a bolus late. In some embodiments, a shorter bolus-consideration time period TB may be used to detect late boluses than to detect missed boluses.
A manual bolus may include a situation where a person with diabetes provides manual user input instructing an insulin delivery device (e.g., an insulin pump) to provide a specified bolus of insulin at a specified time. As previously discussed, a manual bolus may be contrasted with an “auto” basal micro-bolus determined and administered automatically to the person by an automated insulin delivery device.
A critical alarm may include a situation where an insulin delivery device detects a technical error or problem with its operation. Such errors or problems include an occlusion in the fluid pathway between an insulin reservoir and a site of insulin administration, damage or incorrect operation of some component of the insulin delivery device (e.g., the pump, dose determination sensors, etc.), low battery power, lack of connectivity with a mobile device and/or glucose sensor (e.g., due to electromagnetic interference, or too much distance between the devices), excessive heat or cold, insufficient insulin in the delivery device's reservoir, or other types of technical issues that prevent smooth, error-free, and/or efficient operation of the insulin delivery device.
A site change may include a situation where a user temporarily removes the insulin delivery device in order to change the injection site, e.g., from the person's abdomen to the person's back. Site changes may be detected based on manual user input indicating that the user is changing his/her injection site. In some embodiments, a site change may be inferred each time the insulin delivery device is powered off and on.
A suspension may include the occurrence of a Predictive Low Glucose Suspend (PLGS), as previously described in relation to
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In this way, the disclosed systems, methods and processes allow the user to filter logged data pertaining to a person with diabetes according to both (i) glucose events and (ii) contextual factors. Panels displaying data that exhibit both the selected glucose events and the contextual factors are visually highlighted and/or emphasized. This allows the user, such as a HCP, to quickly identify, analyze, and/or compare time periods in which the person with diabetes exhibited not just one type of event, but different combinations of events. For example, the user may quickly determine by filtering for both hypoglycemic events and upward dose overrides whether the person with diabetes has a tendency to manually direct his/her automatic insulin delivery device to deliver too much insulin, thus sending the person into hypoglycemia. If filtering for both hypoglycemic events and upward dose overrides reveal that the person has a consistent tendency to manually and inappropriately increase his/her dose, this may be the basis of a discussion between the person and his/her health care provider to explore root causes and solutions for this tendency.
When none of the panels of the plurality of panels 410 are visually emphasized, the “Compare Days” button 440 may be grayed out or deactivated, as shown in
Glucose measurement sub-panel 910 includes a horizontal time axis 912 that is analogous to horizontal time axis 612, which indicates the passage of time from 12 am in the morning until 12 am the next day. Sub-panel 910 also includes a vertical axis 914 that is analogous to vertical axis 614, which indicates glucose levels in units of mg/dL. Sub-panel 910 also includes two or more glucose measurement lines 916. Each glucose measurement line displays multiple glucose measurements taken of the person at different times on the selected time periods. In this example, panel 900 is comparing data from the two panels that were visually emphasized in
Bolus dosing sub-panel 930 is analogous to bolus dosing sub-panel 630. However, whereas sub-panel 630 only displays data pertaining to one time period, sub-panel 930 may display data pertaining to each time period that corresponds to one of the selected or visually emphasized panels (in this example, the panels pertaining to July 10 and July 18). Similar to bolus dosing sub-panel 630, the displayed data may comprise meal boluses blocks 632, corrective bolus blocks 636, downward dose override indicators 634, upward dose override indicators 638, and/or carbohydrate indicators 640.
Basal dosing sub-panel 950 is analogous to bolus dosing sub-panel 640. Similarly, however, whereas sub-panel 650 only displays data pertaining to one time period, sub-panel 950 may display data pertaining to each time period that corresponds to one of the selected or visually emphasized panels (e.g., July 10 and July 18). This displayed data may comprise auto basal micro-bolus blocks 652, auto basal micro-bolus blocks 654, and/or one or more PLGS symbols or indicators 656.
The terms “first”, “second”, “third” and the like, whether used in the description or in the claims, are provided for distinguishing between similar elements and not necessarily for describing a sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances (unless clearly disclosed otherwise) and that the embodiments of the disclosure described herein are capable of operation in other sequences and/or arrangements than are described or illustrated herein. In particular, while
While this invention has been described as having exemplary designs, the present invention can be further modified within the spirit and scope of this disclosure. This application is therefore intended to cover any variations, uses, or adaptations of the invention using its general principles. Further, this application is intended to cover such departures from the present disclosure as come within known or customary practice in the art to which this invention pertains.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/US2020/059126 | 11/5/2020 | WO |
| Number | Date | Country | |
|---|---|---|---|
| 62934080 | Nov 2019 | US |
