THERAPEUTIC ZONE ASSESSOR
Systems and methods are provided for identifying therapeutic zones where there is glycemic dysfunction of a specific type that can be addressed by making strategic changes to behavior and/or therapy parameters. Systems and methods described herein evaluate large historical data sets to: identify a therapeutic zone or zones with glycemic dysfunction that are most readily addressable; quantify the glycemic impact of a plurality of different therapeutic adjustments in terms of either adjustments to historical doses or the parameters of a prospective dosing strategy to determine the highest possible improvement; and/or identify patient dosing strategies to provide therapy recommendations adapted for the patient's preferred behavioral dosing strategy.
1 . A method comprising:
receiving at least one of glucose data, insulin data, or other-diabetes related data of a patient;
identifying a therapeutic improvement opportunity using the at least one of glucose data, insulin data, or other-diabetes related data;
identifying an insulin dosing strategy of the patient;
scoring the insulin dosing strategy for patient compliance;
performing optimization for the insulin dosing strategy; and
providing an output comprising optimized insulin strategy parameters to a user.
2 . The method of claim 1 , wherein the other diabetes-related data comprises at least one of meal information, specificity of meals, timing of meals, sizing of meals, carbohydrate estimates, composition information, or exercise information.
3 . The method of claim 1 , wherein the at least one of glucose data, insulin data, or other-diabetes related data is received from at least one of a patient or a connected system or device.
4 . The method of claim 1 , wherein identifying the therapeutic improvement opportunity comprises receiving a user selection of at least one of a mealtime, a time of day, or a parameter setting.
5 . The method of claim 4 , wherein the parameter setting is a carb ratio.
6 . The method of claim 1 , wherein the insulin dosing strategy comprises a diabetes management or insulin strategy being implemented by the patient in practice as determined from the at least one of glucose data, insulin data, or other-diabetes related data of a patient.
7 . The method of claim 1 , wherein performing optimization for the insulin dosing strategy determines whether the patient adheres to a known insulin strategy and analyzes the effect of percentage changes to the parameters of the identified insulin strategy.
8 . The method of claim 1 , wherein the user is at least one of a clinician, a patient, or a connected device or system.
9 . The method of claim 1 , wherein the output is provided by a natural language processor to describe a candidate change and an optimized risk outcome.
10 . The method of claim 1 , wherein providing the output comprises providing an output in the form of a graph illustrating the optimized insulin strategy parameters to a user interface or connected device.
11 . The method of claim 10 , wherein the connected device comprises a bolus calculator.
12 . A system comprising:
a therapeutic improvement identifier configured to evaluate collated glucose and insulin data of a patient to identify areas for therapy optimization in a diabetes management routine of the patient, and to generate a therapeutic improvement;
an insulin strategy optimizer configured to determine whether the patient adheres to a known insulin strategy and analyze the effect of percentage changes to the parameters of the identified insulin strategy; and
a therapy identifier optimizer report generator that provides an output.
13 . The system of claim 12 , wherein the insulin strategy optimizer comprises:
an insulin strategy identifier configured to identify a diabetes management or insulin strategy being implemented by the patient in practice as determined from the collated glucose and insulin data;
a compliance scorer configured to quantify a compliance of the patient with the identified insulin strategy; and
an insulin strategy optimizer within identified behavior configured to perform optimization for the identified insulin strategy.
14 . The system of claim 13 , wherein the diabetes data comprises insulin data and meal data.
15 . The system of claim 13 , wherein the insulin strategy identifier is configured to identify patterns in dosing and characterizes the identified insulin strategy of the patient based thereon.
16 . The system of claim 13 , wherein the insulin strategy is the behavioral methodology that the patient applies in diabetes management, comprising at least one of types of insulin pump usage, multiple daily injections, or type 2 therapies.
17 . The system of claim 13 , wherein the compliance scorer is configured to generate a score computed for a degree of compliance of the patient with the identified insulin strategy.
18 . The system of claim 13 , wherein the insulin strategy optimizer within identified behavior is configured to iteratively propose percentage changes to the parameters of the strategy in a selected therapeutic zone or zone group.
19 . The system of claim 12 , wherein the output comprises optimized insulin strategy parameters.
20 . The system of claim 12 , wherein the therapy identifier optimizer report generator is configured to output a candidate therapy change to a user.
21 . The system of claim 20 , wherein the user is at least one of a clinician, a patient, or a connected device or system.
22 . The system of claim 12 , wherein the output is provided by a natural language processor to describe a candidate change and an optimized risk outcome.
23 . A system comprising:
at least one processor; and
a non-transitory computer readable medium comprising instructions that, when executed by the at least one processor, cause the system to:
receive at least one of glucose data, insulin data, or other-diabetes related data of a patient;
identify a therapeutic improvement opportunity using the at least one of glucose data, insulin data, or other-diabetes related data;
identify an insulin dosing strategy of the patient;
score the insulin dosing strategy for patient compliance;
perform optimization for the insulin dosing strategy; and
provide an output comprising optimized insulin strategy parameters to a user.
24 . The system of claim 23 , wherein the other diabetes-related data comprises at least one of meal information, specificity of meals, timing of meals, sizing of meals, carbohydrate estimates, composition information, or exercise information.
25 . The system of claim 23 , wherein the at least one of glucose data, insulin data, or other-diabetes related data is received from at least one of a patient or a connected system or device.
26 . The system of claim 23 , wherein identifying the therapeutic improvement opportunity comprises receiving a user selection of at least one of a mealtime, a time of day, or a parameter setting.
27 . The system of claim 26 , wherein the parameter setting is a carb ratio.
28 . The system of claim 23 , wherein the insulin dosing strategy comprises a diabetes management or insulin strategy being implemented by the patient in practice as determined from the at least one of glucose data, insulin data, or other-diabetes related data of a patient.
29 . The system of claim 23 , wherein performing optimization for the insulin dosing strategy determines whether the patient adheres to a known insulin strategy and analyzes the effect of percentage changes to the parameters of the identified insulin strategy.
30 . The system of claim 23 , wherein the user is at least one of a clinician, a patient, or a connected device or system.
31 . The system of claim 23 , wherein the output is provided by a natural language processor to describe a candidate change and an optimized risk outcome.
32 . The system of claim 23 , wherein providing the output comprises providing an output in the form of a graph illustrating the optimized insulin strategy parameters to a user interface or connected device.
33 . The system of claim 32 , wherein the connected device comprises a bolus calculator.