Advising diabetes treatments

1. A computer-implemented method for managing glucose levels of a patient under the supervision of a healthcare professional (HCP), the method when executed by data processing hardware causes the data processing hardware to perform operations comprising:

obtaining patient information for the patient, the patient information comprising:

patient medication data comprising a current medications list including a list of medications the patient is currently prescribed;

patient monitoring data; and

patient characteristic data;

for each corresponding medication in the current medications list, determining corresponding risk profile characteristic data indicating a list of patient characteristics associated with hyperglycemia for patients receiving the corresponding medication;

creating a patient risk profile for the patient based on the patient monitoring data, the patient characteristic data, and the corresponding risk profile characteristic data determined for each corresponding medication in the current medications list;

determining a likelihood that the patient will experience hyperglycemic effects based on the patient risk profile;

determining an optimum treatment plan for the patient based on the patient risk profile and the likelihood that the patient will experience hyperglycemic effects, the optimum treatment plan comprising a recommended dosage of a particular medication, the particular medication comprising an anti-diabetes medication or insulin;

transmitting the optimum treatment plan to one of a HCP device associated with the HCP or a patient device associated with the patient; and

transmitting instructions to an administration device associated with the patient to administer the particular dosage of the particular medication to the patient, the instructions causing the administration device to administer the recommended dosage of the particular medication to the patient.

2. The method of claim 1 , wherein the type of diabetes associated with the patient comprises Type 1 diabetes mellitus, Type 2 diabetes mellitus, gestational diabetes mellitus, non-diabetic stress hyperglycemia, Maturity Onset Diabetes of the Young (MODY), Latent Autoimmune Diabetes in Adults (LADA), or unknown.

3. The method of claim 1 , wherein the patient medication data further comprises corresponding dosages for the list of medications the patient is currently prescribed.

4. The method of claim 3 , wherein the patient medication data comprises a drug name, a dosage, a route of administration, a frequency, and a datetime of administration of any medications in the current medications list known to impact patient blood glucose levels that the patient is currently prescribed.

5. The method of claim 1 , wherein the patient information further comprises at least one of:

current medical conditions associated with the patient;

permanent medical conditions associated with the patient;

one or more glucose values for the patient; or

an A1c value for the patient.

6. The method of claim 1 , wherein the patient characteristic data comprises at least one of:

nutrition order data associated with the patient;

a medical administration record (MAR) associated with the patient;

an electronic medical record (EMR) associated with the patient; or

laboratory information system (LIS) data associated with the patient.

7. The method of claim 1 , wherein the patient medication data comprises a drug name, a dosage, a route of administration, a frequency, and a datetime of administration of any medications in the current medications list known to impact patient blood glucose levels that the patient is currently prescribed.

8. The method of claim 1 , wherein the patient risk profile is created further based on medical literature.

9. The method of claim 1 , wherein the patient risk profile is created by matching the patient information to a previously-created patient risk profile for a patient with similar patient information.

10. A computer-implemented method for managing glucose levels of a patient under the supervision of a healthcare professional (HCP), the method when executed by data processing hardware, causes the data processing hardware to perform operations comprising:

obtaining patient information for the patient, the patient information comprising:

patient medication data comprising a current medications list including a list of medications the patient is currently prescribed;

patient monitoring data; and

patient characteristic data;

for each corresponding medication in the current medications list, determining corresponding risk profile characteristic data indicating a list of patient characteristics associated with hyperglycemia for patients receiving the corresponding medication;

creating a patient risk profile for the patient based on the patient monitoring data, the patient characteristic data, and the corresponding risk profile characteristic data determined for each corresponding medication in the current medications list;

determining a likelihood that the patient will experience hyperglycemic effects based on the patient risk profile;

determining an optimum treatment plan for the patient based on the patient risk profile and the likelihood that the patient will experience hyperglycemic effects, the optimum treatment plan comprising a recommended dosage of a particular medication, the particular medication comprising an anti-diabetes medication or insulin; and

transmitting instructions to an administration device associated with the patient to administer the recommended dosage of the particular medication to the patient, the instructions causing the administration device to administer the recommended dosage of the particular medication to the patient.

11. The method of claim 10 , wherein the administration device comprises at least one of an insulin pump, a smart pen, a smart pill bottle, a smart pill, or an insulin inhaler.

12. The method of claim 10 , wherein the type of diabetes associated with the patient comprises Type 1 diabetes mellitus, Type 2 diabetes mellitus, gestational diabetes mellitus, non-diabetic stress hyperglycemia, Maturity Onset Diabetes of the Young (MODY), Latent Autoimmune Diabetes in Adults (LADA), or unknown.

13. The method of claim 10 , wherein the patient medication data further comprises:

corresponding dosages for the list of medications the patient is currently prescribed; and

a drug name, a dosage, a route of administration, a frequency, and a datetime of administration of any medications in the list of medications known to impact patient blood glucose levels that the patient is currently prescribed.

14. The method of claim 10 , wherein the patient information further comprises at least one of:

current medical conditions associated with the patient;

permanent medical conditions associated with the patient;

one or more glucose values for the patient; or

an A1c value for the patient.

15. The method of claim 10 , wherein the patient characteristic data comprises at least one of:

nutrition order data associated with the patient;

a medical administration record (MAR) associated with the patient;

an electronic medical record (EMR) associated with the patient; or

laboratory information system (LIS) data associated with the patient.

16. The method of claim 10 , wherein the patient medication data comprises a drug name, a dosage, a route of administration, a frequency, and a datetime of administration of any medications in the list of medications known to impact patient blood glucose levels that the patient is currently prescribed.

17. The method of claim 10 , wherein the patient risk profile is created further based on medical literature.

18. The method of claim 10 , wherein the patient risk profile is created by matching the patient information to a previously-created patient risk profile for a patient with similar patient information.

19. The method of claim 1 , wherein the administration device comprises at least one of an insulin pump, a smart pen, a smart pill bottle, a smart pill, or an insulin inhaler.

20. A system comprising:

data processing hardware; and

memory hardware in communication with the data processing hardware and storing instructions that when executed on the data processing hardware causes the data processing hardware to perform operations comprising:

obtaining patient information for a patient, the patient information comprising:

patient medication data comprising a current medications list including a list of medications the patient is currently prescribed;

patient monitoring data; and

patient characteristic data;

for each corresponding medication in the current medications list, determining corresponding risk profile characteristic data indicating a list of patient characteristics associated with hyperglycemia for patients receiving the corresponding medication;

creating a patient risk profile for the patient based on the patient information monitoring data, the patient characteristic data, and the corresponding risk profile characteristic data determined for each corresponding medication in the current medications list;

determining a likelihood that the patient will experience hyperglycemic effects based on the patient risk profile;

determining an optimum treatment plan for the patient based on the patient risk profile and the likelihood that the patient will experience hyperglycemic effects, the optimum treatment plan comprising a recommended dosage of a particular medication, the particular medication comprising an anti-diabetes medication or insulin; and

transmitting the optimum treatment plan to one of a healthcare professional (HCP) device associated with a HCP or a patient device associated with the patient; and

transmitting instructions to an administration device associated with the patient to administer the particular dosage of the particular medication to the patient, the instructions when received by the administration device causing the administration device to administer the recommended dosage of the particular medication to the patient.