Abstract: Techniques for detection of occurrence of a meal are provided. In some embodiments, the techniques may involve obtaining a plurality of glucose measurements indicative of a glucose level in a body of a patient during an analysis interval. The techniques may involve determining one or more glucose measurement statistics based on the plurality of glucose measurements. The techniques may involve determining a likelihood of the patient having consumed a meal during the analysis interval based on the one or more glucose measurement statistics that are correlative to an occurrence of a meal for the patient. The techniques may involve detecting an occurrence of the meal during the analysis interval based on the likelihood of the patient having consumed the meal during the analysis interval.

Abstract: Disclosed herein are techniques related to making trend based adjustments to insulin dosage. In some embodiments, the techniques may involve obtaining, based on glucose measurements performed on a person, a glucose value and a glucose rate of change (ROC). An initial insulin amount to deliver to the person is calculated based on this glucose value. However, an adjustment value can be obtained in response to a determination that the glucose value exceeds a glucose threshold, and that the glucose ROC exceeds an ROC threshold. The adjustment value represents an adjustment to be applied to the initial insulin amount when the glucose threshold and the ROC threshold are both exceeded. The adjustment value can be predetermined, based on earlier glucose measurements performed on the person. For instance, the adjustment value and the thresholds can be jointly determined through a computer simulation using a person-specific physiological model.

Abstract: Techniques for detection of occurrence of a meal are provided. In some embodiments, the techniques may involve obtaining a plurality of glucose measurements indicative of a glucose level in a body of a patient during an analysis interval. The techniques may involve determining one or more glucose measurement statistics based on the plurality of glucose measurements. The techniques may involve determining a likelihood of the patient having consumed a meal during the analysis interval based on the one or more glucose measurement statistics that are correlative to an occurrence of a meal for the patient. The techniques may involve detecting an occurrence of the meal during the analysis interval based on the likelihood of the patient having consumed the meal during the analysis interval.

Abstract: Disclosed herein are techniques related to blood glucose estimation based on rate of change information. In some embodiments, the techniques may involve obtaining a sensor glucose value. The techniques may also involve calculating a sensor glucose rate of change based on the sensor glucose value. The techniques may further involve determining an estimated glucose bias value corresponding to the sensor glucose rate of change. The determining may be based on applying, to the sensor glucose rate of change, a predictive model for estimating glucose bias values corresponding to differences between blood glucose measurements and sensor glucose values. Additionally, the techniques may involve adjusting the sensor glucose value based on accounting for the estimated glucose bias value.

Abstract: A fecal collection apparatus includes a main body including an insertion end and a removal end opposite the insertion end, the main body defining a main body cavity between the insertion end and the removal end, a sample collection member positionable within the main body cavity through the insertion end, the sample collection member defining a fecal engagement portion for holding a fecal sample and a handle portion spaced apart from the fecal engagement portion, and a plug provided at a removal end of the main body, the plug positionable from a closed position in which the plug restricts fluid from passing from the main body cavity through the removal end, to an open position.

Abstract: A computer-implemented therapy management system is operated to collect patient data associated with medical device users. Treatment of the users is managed by healthcare professionals (HCPs), which include a customer HCP and a plurality of non-customer HCPs. The system receives a first set of attributes for a first individual patient or a first group of patients under care of the customer HCP, and a second set of attributes for a second individual patient or a second group of patients. The system identifies a first set of patient records associated with the customer HCP that satisfy the received first attributes, and a second set of patient records that satisfy the received second attributes, and compares patient outcomes from the first set of records against patient outcomes from the second set of records. A comparative therapy report is generated and communicated to a client device associated with the customer HCP.

Abstract: Disclosed herein are techniques related to event-oriented predictions of glycemic responses. In some embodiments, the techniques may involve accessing a prediction model that correlates a person's glycemic responses to events and the person's physiological parameters during the events. The techniques may also involve obtaining a glucose level measurement of the person during an event. Additionally, the techniques may involve determining, based on the glucose level measurement, a physiological parameter of the person during the event. Furthermore, the techniques may involve predicting the person's glycemic response to the event based on applying the prediction model to the physiological parameter.

Abstract: A system for monitoring a patient includes one or more processors and a sensor device implemented in circuitry. The system is configured to measure, using the sensor device, a blood glucose status of the patient, and determine, using one or more processors, an initial insulin dose for the patient based on the blood glucose status of the patient. The system is further configured to optimize the initial insulin dose for the patient, based at least in part on a correction factor, to create an optimized insulin dose for the patient. The system is configured to facilitate therapy, using the one or more processors, based on the determined optimized insulin dose.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.

Abstract: A computer-implemented system and related method of managing use of a diabetes management device are presented here. An embodiment of the method obtains input data for a user of the diabetes management device, and compares the input data against historical event/outcome combinations maintained for the user. Each of the event/outcome combinations includes insight event data indicative of a glycemic event and a glycemic outcome corresponding to the insight event data. The method determines, based on the comparing, a correlation between the input data and a glycemic outcome. The method continues by generating a glycemic insight message for delivery to the user, wherein the glycemic insight message includes information regarding a relationship between at least some of the input data and the glycemic outcome.

Abstract: Medical devices and related patient management systems and event detection methods are provided. An exemplary method of detecting events pertaining to operation of a medical device, such as an infusion device, involves obtaining measurements indicative of a condition in a body of a patient, determining statistics for an analysis interval based on the measurements, and determining an event probability associated with the analysis interval based on historical event data associated with the patient. An event detection model associated with the patient is obtained and applied to the statistics and the event probability to identify occurrence of the event using the event detection model, and in response, an indication of the event associated with the analysis interval is provided, for example, by tagging or marking data in a database, displaying graphical indicia of the event, or the like.

Abstract: Medical devices and related patient management systems and event detection methods are provided. An exemplary method of detecting events pertaining to operation of a medical device, such as an infusion device, involves obtaining measurements indicative of a condition in a body of a patient, determining statistics for an analysis interval based on the measurements, and determining an event probability associated with the analysis interval based on historical event data associated with the patient. An event detection model associated with the patient is obtained and applied to the statistics and the event probability to identify occurrence of the event using the event detection model, and in response, an indication of the event associated with the analysis interval is provided, for example, by tagging or marking data in a database, displaying graphical indicia of the event, or the like.

Abstract: A computer-implemented therapy management system is operated to collect patient data associated with medical device users. Treatment of the users is managed by healthcare professionals (HCPs), which include a customer HCP and a plurality of non-customer HCPs. The system receives a first set of attributes for a first individual patient or a first group of patients under care of the customer HCP, and a second set of attributes for a second individual patient or a second group of patients. The system identifies a first set of patient records associated with the customer HCP that satisfy the received first attributes, and a second set of patient records that satisfy the received second attributes, and compares patient outcomes from the first set of records against patient outcomes from the second set of records. A comparative therapy report is generated and communicated to a client device associated with the customer HCP.

Abstract: The system disclosed here includes a computer-implemented patient therapy management and coaching system, a database system to collect and maintain patient data associated with a plurality of medical device users that includes a trainee patient assigned to a coach, and a user device communicatively coupled to the patient therapy management and coaching system and associated with the coach. The management and coaching system is operative to: receive a patient request for coaching; process the request to automatically identify goals to be achieved by the trainee patient; communicate the goals to the coach's user device; receive an accepted goal selected from the identified goals; create a patient coaching program for the accepted goal; generate insight messages based on patient data collected for the trainee patient, the generated insight messages related to the patient coaching program; and deliver the generated insight messages to the user device associated with the coach.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of monitoring a physiological condition of a patient involves obtaining measurement data pertaining to the physiological condition of the patient from a sensing arrangement, obtaining medical record data associated with the patient from a database, determining a risk score associated with the patient for a medical condition based at least in part on the measurement data, the medical record data, and one or more relationships between population measurement data and population medical record data, and initiating one or more actions based at least in part on the risk score.

Abstract: Infusion devices and related medical devices, patient data management systems, and methods are provided for monitoring a physiological condition of a patient. An exemplary method of querying a database involves receiving an input query from a client device, identifying a logical layer of a plurality of different logical layers of the database for searching based at least in part on the input query, generating a query statement for searching the identified logical layer of the plurality of different logical layers of the database based at least in part on the input query, querying the identified logical layer of the database using the query statement to obtain result data, and providing a search result influenced by the result data.

Abstract: A computer-implemented system and related method of managing use of a diabetes management device are presented here. An embodiment of the method obtains a number of glycemic insight messages for delivery to a user device associated with a user of the diabetes management device, each of the glycemic insight messages conveying information regarding a relationship between an insight event derived from patient-specific historical input data and a glycemic outcome. The glycemic insight messages are culled and prioritized to identify a group of insight messages intended for delivery. The method continues by queuing the group of insight messages based on the culling and prioritizing, and communicating at least one of the queued insight messages to the user device.

Abstract: Medical devices and related patient management systems and event detection methods are provided. An exemplary method of detecting events pertaining to operation of a medical device, such as an infusion device, involves obtaining measurements indicative of a condition in a body of a patient, determining statistics for an analysis interval based on the measurements, and determining an event probability associated with the analysis interval based on historical event data associated with the patient. An event detection model associated with the patient is obtained and applied to the statistics and the event probability to identify occurrence of the event using the event detection model, and in response, an indication of the event associated with the analysis interval is provided, for example, by tagging or marking data in a database, displaying graphical indicia of the event, or the like.

Abstract: A computer-implemented system and related method of managing use of a diabetes management device are presented here. An embodiment of the method obtains input data for a user of the diabetes management device, and compares the input data against historical event/outcome combinations maintained for the user. Each of the event/outcome combinations includes insight event data indicative of a glycemic event and a glycemic outcome corresponding to the insight event data. The method determines, based on the comparing, a correlation between the input data and a glycemic outcome. The method continues by generating a glycemic insight message for delivery to the user, wherein the glycemic insight message includes information regarding a relationship between at least some of the input data and the glycemic outcome.