Abstract: A method of diabetes analysis includes receiving a plurality of glucose level readings for a user. A common event occurrence in at least two of the glucose level readings is determined. The at least two glucose level readings from the common event occurrence onwards in time for a time period is analyzed. A glucose level pattern formed by the at least two glucose level readings having a similar shape is determined. At least one anomalous glucose level reading having the similar shape and not conforming to the glucose level pattern is analyzed. The at least one anomalous glucose level reading is adapted to the pattern to form an adapted glucose level pattern. An insulin dosage for the time period beginning at the common event occurrence is calculated based on the adapted glucose level pattern.

Abstract: A diabetes data management system selects variable parameters and one or more devices with data that are utilized in a report. The diabetes data management system analyzes data during a selected period. The system generates reports which highlight data from one or more device during the selected period including carbohydrate, insulin, and glucose data, reports which highlight data around and during meal events and other user-defined events, reports which overlay multiple data based on time of day and other factors, and automatically prepared logbook reports.

Abstract: A method of diabetes analysis includes obtaining average glucose level information for a time period over a plurality of days. A current event occurrence is determined. An event occurrence in the average glucose level information within the time period corresponding to the current event occurrence is determined, where the current event occurrence is at a different time of day than the event occurrence. The average glucose level information starting in time from the event occurrence within the time period is analyzed. A notification event in the average glucose level information starting in time from the event occurrence within the time period is determined. A current notification event in time from the current event occurrence is predicted based on a time span from the event occurrence to the notification event in the average glucose level information. An action is initiated in advance of the predicted current notification event.

Abstract: A method of diabetes analysis includes receiving a plurality of glucose level readings for a user. A common event occurrence in at least two of the glucose level readings is determined. The at least two glucose level readings from the common event occurrence onwards in time for a time period is analyzed. A glucose level pattern formed by the at least two glucose level readings having a similar shape is determined. At least one anomalous glucose level reading having the similar shape and not conforming to the glucose level pattern is analyzed. The at least one anomalous glucose level reading is adapted to the pattern to form an adapted glucose level pattern. An insulin dosage for the time period beginning at the common event occurrence is calculated based on the adapted glucose level pattern.

Abstract: A diabetes data management system selects variable parameters and one or more devices with data that are utilized in a report. The diabetes data management system analyzes data during a selected period. The system generates reports which highlight data from one or more device during the selected period including carbohydrate, insulin, and glucose data, reports which highlight data around and during meal events and other user-defined events, reports which overlay multiple data based on time of day and other factors, and automatically prepared logbook reports.

Abstract: A system to assist an individual in developing a therapy in diabetes treatment of a patient includes a user interface control module, a simulation engine, a charting and display module. The user interface control module receives an input related to the patient and captures a current time of the simulation. The simulation engine receives the input, generates a plurality of blood glucose readings for the patient up to the current time of the simulation based on the input, and to transfers the plurality of blood glucose readings. The charting and display module receives the plurality of blood glucose readings and display the plurality of blood glucose readings. The simulation engine receives patient parameters from a patient parameter library based on a selected patient model.