Roche Diabetes Care, Inc.

Roche Diagnostics Gmbh

F. Hoffmann-la Roche Ag

Christen A Rees

Paul J Galley

Eric Stephen Carlsgaard

Igor Gejdos

Matthias Koehler

Robin S Wagner

Timothy Nicholas Aykroyd

Scott A Wooldridge

Sheldon A White

Nathan Wegmann

Horst Merkle

Michelle M Stevens

Peter B Carlsgaard

Amy C Day

Michael L Long

Samer Dajani

Robin Wagner

Ann Buskirk

A system and technique are enclosed for determining the effectiveness of a blood glucose therapy treatment. Examples of this technique include analyzing sufficiency of blood glucose data collected from a patient with a computing device, analyzing hypoglycemic risk based on the blood glucose data with the computing device, analyzing glycemic control for the blood glucose data with the computing device, analyzing glycemic variability of the blood glucose data with the computing device, and outputting results from said analyzing the sufficiency, said analyzing the hypoglycemic risk, said analyzing the glycemic control, and said analyzing the glycemic variability with the computing device.

System and methods for analyzing blood glucose data and quantifying the success or failure of insulin therapy

A computer implemented method for transmitting messages generated by a continuous glucose monitor (CGM), the method comprising: generating a first message at the CGM at a first time, the first message being related to blood glucose measuring; generating a second message at the CGM at a second time, the second time being after the first time, the second message being related to blood glucose measuring; determining an elapsed time since a transmitter of the CGM has transmitted data; determining whether the elapsed time is greater than a threshold; determining whether the second message is to be transmitted before the first message, in response to the elapsed time being greater than the threshold; and transmitting data corresponding with the second message before transmitting data corresponding with the first message to a diabetes management device, in response to determining that the second message is to be transmitted before the first message.

Presenting data generated by a continuous glucose monitor

A computer-implemented method is presented for recommending insulin dosage adjustments for a patient having diabetes. The method includes: identifying a plurality of bolus events from patient data; grouping bolus events having a recommended bolus dosage substantially equivalent to the amount of administered insulin into a first subset of bolus events; determining a bolus outcome for each of the bolus events in the first subset of bolus events, where the bolus outcome is expressed in relation to a target range of blood glucose values and is selected from a group including above the target range, in the target range and below the target range; determining whether one of the bolus outcomes is predominant amongst the bolus events in the first subset of bolus events; and generating a recommendation pertaining to insulin dosage for the patient in response to a determination that one of the bolus outcomes is predominant.

Insulin dosage assessment and recommendation system

A method includes: measuring a blood glucose (bG) level in a blood sample; storing the bG level and a time of receipt of the blood sample; storing a classification of the blood sample; in response to the receipt of the blood sample, selecting a group of stored bG levels having the classification of the blood sample and that were received within a predetermined period before receipt of the blood sample; calculating a bG evaluation parameter from the selected bG levels; evaluating the bG evaluation parameter in relation to first predetermined criteria, the first predetermined criteria including a first threshold indicative of a high bG level or a low bG level; selectively displaying an indication of recognition of a pattern in the selected bG levels when the bG evaluation parameter is greater than or less than the first threshold; and selectively removing the indication from the display.

Reminder, classification, and pattern identification systems and methods for handheld diabetes management devices

Growing community of inventors

Indianapolis, IN, United States of America

Christen A Rees