US 11,749,408 B2
Individualized multiple-day simulation model of type 1 diabetic patient decision-making for developing, testing and optimizing insulin therapies driven by glucose sensors
Martina Vettoretti, Valla di Riesse P (IT); Andrea Facchinetti, Trissino (IT); Giovanni Sparacino, Padua (IT); and Claudio Cobelli, Padua (IT)
Assigned to DEXCOM, INC., San Diego, CA (US)
Filed by DexCom, Inc., San Diego, CA (US)
Filed on Oct. 20, 2021, as Appl. No. 17/451,609.
Application 17/451,609 is a division of application No. 15/158,047, filed on May 18, 2016, granted, now 11,183,301.
Claims priority of provisional application 62/163,091, filed on May 18, 2015.
Prior Publication US 2022/0044813 A1, Feb. 10, 2022
Int. Cl. G08B 21/04 (2006.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G16H 20/17 (2018.01); G16H 40/60 (2018.01); A61M 5/172 (2006.01)
CPC G16H 50/20 (2018.01) [A61M 5/1723 (2013.01); G16H 20/17 (2018.01); G16H 40/60 (2018.01); G16H 50/50 (2018.01); A61M 2205/50 (2013.01); A61M 2230/005 (2013.01); A61M 2230/201 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A method for providing a real-time therapeutic recommendation for use in type 1 diabetes management in a patient, comprising:
inputting, to a decision support module, data including continuous glucose monitoring data obtained from a glucose sensor, insulin pump data, and other diabetes management data;
generating, based on the input data, a first therapeutic recommendation;
displaying the first therapeutic recommendation to the patient;
inputting, to the decision support module, data indicative of an action taken by the patient in response to receiving the displayed first therapeutic recommendation, the data including continuous glucose monitoring data obtained from the glucose sensor and insulin pump data;
comparing the data indicative of an action taken by the patient responsive to the first therapeutic recommendation to determine if the patient has taken the first therapeutic recommendation, has ignored the first therapeutic recommendation, or has taken an action similar to the first therapeutic recommendation; and
generating, based on the input data and the data indicative of an action taken by the patient, a second therapeutic recommendation, wherein the action taken by the patient is employed to modify a decision-making module configured to simulate real-life situations and behaviors of the patient, and wherein the decision-making module utilizes data of the patient to assess glycemic control or efficacy of the decision support module and to suggest modifications to improve performance of the decision support module.