Field of the Invention
The present invention relates generally to apparatuses, methods and systems for sensing or measuring physiological data, analyzing the data, and outputting user-friendly information providing an interpretation of the data for improved management of one or more physiological conditions.
Description of Related Art
With reference to blocks 10 and 12 of FIG. 1, continuous glucose monitors (CGMs) provide a user such as a patient, clinician or caregiver with a patient's glucose measurements throughout the day (e.g., a glucose measurement every one to five minutes 24 hours per day). Accordingly, the quantity of data provided to the CGM user is tremendous. This data is typically presented to the end user as a graphical display wherein the glucose values measured by the CGM are plotted as a function of time of day. Examples of such data are the graphical display of blood glucose measurements over a 14 hour period shown in FIGS. 20A and 20B of U.S. Pat. No. 7,905,833, and the tabular display shown in FIG. 10 of U.S. Pat. No. 7,890,295 of a continuous electrical current signal (ISIG) (i.e., table column E) measured at various times (i.e., table column D) by a glucose sensor.
The user can usually set what time period to view his measured data (e.g., the x-axis in FIG. 2 of U.S. Pat. No. 6,882,940), thereby adjusting the time period of viewable measured data to one hour, or 24 hours, or 72 hours, for example. The user can also set alarm levels to generate audible alarms, for example, when a measured glucose value is below a low glucose alarm level or above a high glucose alarm level.
Nonetheless, the graphical, tabular or numerical display of measured physiological data (e.g., blood glucose measurements from a CGM) is difficult and, in many cases, cumbersome for a user to interpret and decide what action(s) is needed to manage a physiological condition, as depicted in blocks 14 and 16 of FIG. 1. Further, even relatively simple alphanumeric displays such as the device screens depicted in FIGS. 6A-6D of U.S. Pat. No. 7,022,072 can be difficult for a user to interpret, that is, specific outlier data (e.g., measured values outside a threshold) are merely reported, but no user-friendly information is provided to indicate, for example, what the outlier data signifies about the user's monitored physiological condition or how such data can be mitigated. In other words, a need exists for a device that interprets measured data to provide information to the user in a convenient and more easily comprehended manner such as a video display on a user device that provides a virtual coach (e.g., a video and/or graphical and/or audible presentation with audio and/or visual output) that provides user-friendly interpretation of specific outlier data, for example, and an explanation of why the outlier data occurred and, optionally, suggestions for user actions to mitigate the effects of the outlier data such as in the context of a monitored physiological condition (e.g., an automatically generated output that states “Hypoglycemic events were measured during this time on 3 of the last 5 days. A mid-morning snack can help prevent or lessen the impact of future AM hypoglycemic events.”).
In existing physiological condition monitors or measuring devices, measured physiological data is merely presented as data, leaving the user with the difficult task of interpreting what the data means. Even with availability of alarms to advise a user of measured data being outside a selected threshold, a multitude of other data may need to be considered and interpreted to determine a course of action, if any, that should be taken in response to that alarm. A need exists for a physiological condition measuring and/or monitoring device that automatically analyzes and interprets measured data, along with any other user data that may impact a physiological condition, to select and output information regarding the measured data that is determined to be what the user needs to know (e.g., selected outliers or patterns and why they likely occurred and/or actions to offset or correct the outliers or patterns, or prospectively determined data and/or actions to prevent predicted outlier data sets).
The T1D Exchange Clinical Registry currently enrolls approximately 15,000 persons with Type 1 Diabetes across approximately 65 diabetes centers in the United States from whom to collect and store data to create a biobanking dataset and Type 1 diabetes portal.
According to downloading trend information available via this portal, less than 5% of these persons download data (e.g., their blood glucose values collected from their monitoring devices) on a weekly basis. Only about 12% of these persons download their data on a monthly basis. An astonishing 88% of these participants never view their downloaded data. The majority of T1D Exchange participants are reluctant to download and view their data because it takes too much time and they do not receive meaningful information from the data. T1D Exchange participants find the data simply too difficult to interpret and use in a meaningful manner and prefer to manage their diabetes test by test, injection by injection, relying instead on their healthcare provider to advise them when they need to make significant changes to their diabetes management regimens.
The EV1000 clinical platform from Edwards Lifesciences further illustrates problems with current methods of presenting physiological status of a patient in a clinical setting. Although the EV1000 clinical platform is intended to be the state of the art in providing patient physiological data in a more intuitive and meaningful way (e.g., in an operating room (OR) or in an intensive care unit (ICU)), the monitored data is merely graphically represented without any interpretation and determination of what information a clinician needs to know about the monitored data or recommended course of action or display of clinically acceptable courses of actions based on the monitored data. The display of more monitored data, even if done in an attractive graphical manner, does not necessarily make that data useful to a healthcare provider, particularly in a critical care setting such as an OR or ICU. Some form of interpretation of that data is often needed, and the cognitive load on the practitioner actually increases with added data.
A need therefore exists, in both ambulatory and non-ambulatory healthcare settings, for physiological condition monitoring devices that remove cognitive load/burden from the user when interpreting the data and deciding on a course of action. That is, a need exists for a monitoring method and/or apparatus that takes digital output from a device (e.g., downloaded data) and interprets the data for the user to provide the user with useful information (e.g., a determination of what information the user needs to know about retrospective data or a prospective data analysis).