Roche Diabetes Care, Inc.

Roche Diagnostics Operations, Inc.

F. Hoffmann-la Roche Ag

Steven Bousamra

Stefan Weinert

Abhishek S Soni

Paul J Galley

Juergen Rasch-Menges

P Douglas Walling

Alan Greenburg

David L Duke

James R Long

Siva Chittajallu

Christoph Eisenhardt

Ajay Thukral

Ulrich Porsch

John F Price

Heino Eikmeier

Karl Werner

Birgit Kraeling

Mark Gilmore Mears

Eric R Diebold

Harvey Buck

Robin S Wagner

Paul Douglas Walling

Erica Diebold

Matthew W Percival

Stefhan Weinert

Kym Marco

Walling P Douglas

Matt Percival

James Robert Long

Systems and methods for automatically displaying patterns in biological data may include one or more processors, and machine readable instructions. The machine readable instructions can cause the one or more processors to divide biological data into segments of interest. The one or more processers can transform, automatically, each of the segments of interest into a set of features according to a mathematical algorithm. Further, the one or more processers can cluster, automatically, the segments of interest into groups of clustered segments according to a clustering algorithm. The segments of interest can be grouped in the groups of clustered segments based at least in part upon the set of features. A cluster center can be associated with one of the groups of clustered segments. Moreover, the one or more processers can present, automatically, the cluster center on a human machine interface.

Systems and methods for automatically displaying patterns in biological monitoring data

A structured testing method for diagnostic or therapy support of a patient with a chronic disease and devices thereof are disclosed which implement a structured collection procedure based on a medical use case and/or question which provides at least one or more parameters defining entry criterion, a schedule of events, adherence criterion, and exit criterion. The entry criterion establish conditions needed to be met prior to obtaining biomarker data from the patient. Each event can include one or more of a performance time, patient guidance to perform the event, a request for information from the patient a request for patient action, and a request for collection of biomarker data from the patient. The adherence criterion can be used to assess whether an event performed is acceptable to addressing the medical use case and/or question, and the exit criterion establishes conditions needed to be met prior to exiting the collection procedure.

Structured testing method for diagnostic or therapy support of a patient with a chronic disease and devices thereof

A method is provided for constructing a structured test having user-defined adherence criteria. The method includes: presenting a patient with a plurality of contextual criterion for a structured test; receiving selection of one or more contextual criterion from the plurality of contextual criterion; and constructing a structured test that includes the contextual criterion selected by the patient. During administration of the structured test, each of the contextual criteria selected by the patient is evaluated. Sample data acquired during the structured test is reported as compliant when each of the context criterion selected by the patient was met during the administration of the structured test or tagged as non-compliant when at least one contextual criterion was not met during the administration of the structured test.

User-defined structured testing for use in diabetes care

Embodiments related to a system and method managing the implementation, execution, data collection, data analysis and status reporting of a structured collection procedure running on a portable, hand-held collection device are disclosed. The collection device performing the structured collection procedure has program instructions that when executed by a processor cause the processor to initiate automatically a schedule of events of the structured collection procedure upon one or more entry criteria being met at some unknown time, store in memory patient data collected in accordance to the schedule of events, end automatically the structured collection procedure upon one or more exit criteria being met at some unknown time. Status reporting can be provided throughout the execution of the collection procedure.

Status reporting of a structured collection procedure

Embodiments related to a system and method managing the implementation, execution, data collection, and data analysis of a structured collection procedure running on a portable, hand-held collection device are disclosed. The collection device performing the structured collection procedure has program instructions that when executed by a processor causes the processor to initiate automatically a schedule of events of the structured collection procedure upon one or more entry criterions being met at some unknown time, store in memory patient data collected in accordance to the schedule of events, end automatically the structured collection procedure upon one or more exit criterions being met at some unknown time, and mark/indicate the structured collection procedure as completed if no exception occurred during performance of an event in the schedule of events.

Management method and system implementation, execution, data collection, and data analysis of a structured collection procedure which runs on a collection device

Methods for performing a structured collection procedure by utilizing a collection device are disclosed herein, in which a collection procedure is initiated for performing one or more data collections for one or more data event instances occurring according to a schedule of events. Each data event instance is determined to be successful or unsuccessful on the basis of actual performance of the data collection and meeting certain conditions of the predetermined adherence criteria for the data event instance. Contextual information for successful data collections is generated and a data file generated for storing records relating to successful data collections. For unsuccessful data event instances, substitute data relating to data collections performed separately from the collection procedure are included in the data file records for the collection procedure if the substitute data is determined to meet conditions of the predetermined adherence criterion for the corresponding data event instance.

Management method and system for implementation, execution, data collection, and data analysis of a structured collection procedure which runs on a collection device

Embodiments of a testing method for diabetics to optimize their administered insulin dosage comprise collecting sampling sets of biomarker data, each sampling set comprising a sufficient plurality of non-adverse sampling instances and each sampling instance comprising an acceptable biomarker reading at a single point in time recorded upon compliance with adherence criteria, determining a biomarker sampling parameter from each sampling set, comparing the biomarker sampling parameter to a target biomarker range, calculating an insulin adjustment parameter associated with the biomarker sampling parameter if the biomarker sampling parameter falls outside the target biomarker range, adjusting the insulin dosage by the insulin adjustment parameter if the biomarker sampling parameter falls outside the target biomarker range and the insulin dosage does not exceed maximum dosage, and exiting the testing method if the adjusted insulin dosage is optimized. The insulin dosage is optimized when biomarker sampling parameters fall within the target biomarker range.

Systems and methods for optimizing insulin dosage

Methods for performing a structured collection procedure by utilizing a collection device are disclosed herein, in which a collection procedure is initiated for performing one or more data collections for one or more data event instances occurring according to a schedule of events. Each data event instances comprises a data collection pertaining to a biomarker to be performed according to one or more conditions of an adherence criterion. Each data event instance is determined to be successful or unsuccessful on the basis of actual performance of the data collection and meeting certain conditions of the predetermined adherence criteria for the data event instance. Contextual information for successful data collections is generated and a data file generated for storing records relating to successful data collections. For unsuccessful data event instances, substitute data relating to data collections performed separately from the collection procedure are included in the data file records for the collection procedure if the substitute data is determined to meet conditions of the predetermined adherence criterion for the corresponding data event instance.

Embodiments of a testing method suitable for diabetic persons to optimize their administered insulin dosage comprise collecting one or more sampling sets of biomarker data, wherein each sampling set comprises a sufficient plurality of non-adverse sampling instances and wherein each sampling instance comprises an acceptable biomarker reading at a single point in time recorded upon compliance with adherence criteria, determining a biomarker sampling parameter from each sampling set, comparing the biomarker sampling parameter to a target biomarker range, calculating an insulin adjustment parameter associated with the biomarker sampling parameter if the biomarker sampling parameter falls outside the target biomarker range, adjusting the insulin dosage by the insulin adjustment parameter if the biomarker sampling parameter falls outside the target biomarker range and if the insulin dosage does not exceed maximum dosage, and exiting the testing method if the adjusted insulin dosage is optimized. The insulin dosage is optimized when one or more biomarker sampling parameters fall within a target biomarker range.

A collection device for performing a structured collection procedure may include a processor that executes program instructions communicably coupled to at least one memory. The processor can initiate a schedule of events of the structured collection procedure upon one or more entry criterions being met and segregate the at least one memory into a primary data store and a secondary data store. The processor can write structured patient data collected in accordance to the schedule of events to the secondary data store. The processor can transform a relevant portion of the structured patient data into an evaluated data object. The processor can generate a data abstraction based in part upon the evaluated data object. The processor can link the primary data store and the secondary data store with the data abstraction.

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Carmel, IN, United States of America

Steven Bousamra