Insulin dosage assessment and recommendation system

• US 9,990,581 B2
• Filed: 07/11/2012
• Issued: 06/05/2018
• Est. Priority Date: 07/11/2012
• Status: Active Grant

• Current Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Original Assignee: Roche Diabetes Care Inc. (Roche Holding AG)
• Inventors: Carlsgaard, Peter B., Rees, Christen, Wagner, Robin S.
• Primary Examiner(s): Vanni, G. Steven
• Application Number:
  US13/546,447
• Publication Number:
  US 20140019396A1
• Time in Patent Office: 2,155 Days
• Field of Search: None
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 40/60 for the operation of medical equipment or devices
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients

Abstract

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.

Claims

1. A non-transitory processor-readable medium storing instructions that, when executed by a processor, cause the processor to perform operations, comprising:

receiving patient data pertaining to diabetes care of a patient;

identifying a plurality of bolus events from the patient data, each of the identified bolus events having associated therewith a bolus dosage of insulin recommended to the patient, an amount of insulin administered to the patient in response to the recommended bolus dosage, and a glucose measure taken during an acting time of the administered insulin;

grouping, from the plurality of bolus events, bolus events having a recommended bolus dosage that differs from 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 glucose values and is selected from a category including above the target range, in the target range and below the target range;

calculating a percentage of bolus outcomes in each category of bolus outcomes in relation to a number of bolus events in the first subset of bolus events; and

generating a recommendation pertaining to insulin dosage for the patient using the percentage of bolus outcomes in each category,

wherein the recommendation indicates changing a patient'"'"'s insulin dosages according to those bolus events having a recommended bolus dosage that differed from the amount of administered insulin and determined to have a bolus outcome in the target range.

2. A computer-implemented method for recommending insulin dosage adjustments for a patient having diabetes, comprising:

receiving patient data pertaining to diabetes care of the patient;

identifying a plurality of bolus events from the patient data, each of the identified bolus events having associated therewith a bolus dosage of insulin recommended to the patient, an amount of insulin administered to the patient in response to the recommended bolus dosage, and a glucose measure taken during an acting time of the administered insulin;

grouping, from the plurality of bolus events, bolus events having a recommended bolus dosage substantially equivalent to the amount of administered insulin into a first subset of bolus events;

grouping, from the plurality of bolus events, bolus events having a recommended bolus dosage that differs from the amount of administered insulin, into a second subset of bolus events;

determining a bolus outcome for each of the bolus events in the second subset of bolus events, where the bolus outcome is expressed in relation to a target range of glucose values and is selected from a category including above the target range, in the target range and below the target range;

determining whether bolus outcomes in the category of in the target range is a majority of bolus outcomes for bolus events in the second subset of bolus events; and

generating a recommendation pertaining to insulin dosage for the patient in response to a determination that bolus outcomes in the category of in the target range is a majority of bolus outcomes for bolus events in the second subset of bolus events,

wherein the recommendation indicates changing a patient'"'"'s insulin dosages according to those bolus events having a recommended bolus dosage that differed from the amount of administered insulin and determined to have a bolus outcome in the target range, and wherein the steps of identifying, grouping and determining are executed by a processor of a computing device.

3. The method of claim 2 wherein the step of determining whether the bolus outcomes is predominant further comprises calculating a percentage of bolus outcomes in the target range in relation to a number of bolus events in the second subset of bolus events and deeming the bolus outcomes are predominant when the percentage of bolus outcomes exceeds a predefined threshold.

4. The method of claim 2 wherein generating a recommendation further comprises calculating coefficients of a linear equation using the bolus events in the second subset of bolus events, where the linear equation computes the bolus dosage of insulin recommended to the patient.

5. A computer-implemented method for recommending insulin dosage adjustments for a patient having diabetes, comprising:

receiving patient data pertaining to diabetes care of the patient;

identifying a plurality of fasting periods from the patient data, each of the identified fasting periods having associated therewith at least one glucose measure;

determining a basal outcome for each of the fasting periods in the plurality of fasting periods, where the basal outcome is expressed in relation to a target range of glucose values and selected from a group including above the target range, in the target range and below the target range;

determining whether one of the basal outcomes is predominant amongst the fasting periods in the plurality of fasting periods; and

evaluating a bolus dosage of insulin prescribed for the patient in response to a determination that basal outcomes for the patient are predominantly in the target range of glucose values, wherein evaluating a bolus dosage includes;

identifying a plurality of bolus events from the patient data, each of the identified bolus events having associated therewith a bolus dosage of insulin recommended to the patient, an amount of insulin administered to the patient in response to the recommended bolus dosage, and a glucose measure taken during an acting time of the administered insulin;

grouping, from the plurality of bolus events, bolus events having a recommended bolus dosage that differs from 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 glucose values and is selected from a category including above the target range, in the target range and below the target range;

determining whether bolus outcomes in the category of in the target range is a majority of bolus outcomes for 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 bolus outcomes in the category of in the target range is a majority of bolus outcomes for bolus events in the first subset of bolus events,

wherein the recommendation indicates changing a patient'"'"'s insulin dosages the according to those bolus events having a recommended bolus dosage that differed from the amount of administered insulin and determined to have a bolus outcome in the target range, and wherein the steps of identifying, grouping and determining are executed by a processor of a computing device.

6. The method of claim 5 wherein the step of determining whether one of the basal outcomes is predominant further comprises calculating a percentage of basal outcomes in each grouping of basal outcomes in relation to a number of basal outcomes in the plurality of fasting periods.

7. The method of claim 6 further comprises deeming a given group of basal outcomes is predominant when the percentage of the given group of basal outcomes exceeds a predefined threshold.

8. The method of claim 5 further comprises recommending to maintain current insulin dosage in response to a determination that basal outcomes for the patient are predominantly in the target range of glucose values.

9. The method of claim 5 further comprises recommending an increase in insulin dosage in response to a determination that basal outcomes for the patient are predominantly above the target range of glucose values.

10. The method of claim 5 further comprises recommending a decrease in insulin dosage in response to a determination that basal outcomes for the patient are predominantly below the target range of glucose values.

11. The method of claim 5 further comprises recommending, in response to a determination that basal outcomes are predominantly outside the target range of glucose values, to acquire glucose measures from the patient in accordance with a structured collection procedure, where the structured collection procedure specifies timing for one or more collection events for obtaining glucose measures from the patient.

12. The method of claim 5 wherein each of the identified fasting periods having associated therewith a starting glucose measure taken proximate to a start of the fasting period, an ending glucose measure taken proximate to an end of the fasting period and at least one intermediate glucose measure taken between the starting glucose measure and the ending glucose measure.

13. The method of claim 5 further comprises adjusting the bolus dosage of insulin administered to the patient in accordance with the recommendation.