Literature DB >> 15857228

A graphical user interface for diabetes management that integrates glucose prediction and decision support.

A Michael Albisser1.   

Abstract

BACKGROUND: The promise of the Diabetes Control and Complications Trial (DCCT) has yet to be realized in clinical practice. Notwithstanding intensive education and intensified therapy, there is a distinct lack of a suitable alternative to the intensive decision support that was also provided in the DCCT. Recently, a novel glucose predicting engine has been developed and validated. Use of its predictions in decision support in respect to medication dosing, diet, exercise, and stress promises to empower patients to achieve better diabetes control while reducing hypoglycemia and preventing body weight gain. A graphical user interface (GUI) suitable for these purposes is here described.
METHODS: The kernel of the GUI is a registry database located on a server accessible to both patients and their providers. The patient-GUI includes the resources of the glucose predicting engine and user-friendly, intuitive means to enter body weight and all home-monitored blood glucose levels. In response, means to modify medication dosages (dosing decision support) and modify planned diet and physical activity (lifestyle decision support) are afforded the user. Each action is animated so that the patient can visually see the impact of his or her changes on predicted glucose outcomes and the pending risks of hypoglycemia.
RESULTS: A staged sequence of screens supports the self-management tasks, including selection of the current meal period, the entry of data, and documentation. The GUI returns current medications and presents up-down buttons for adjusting dosages, for changing carbohydrates, for changing exercise, and for predicting the effects of stress. For each adjustment, the impact on medications or predicted glycemia outcomes is animated.
CONCLUSIONS: A new GUI that incorporates a novel glucose predicting engine is intended for all insulin-treated patients with diabetes. It may help patients and their providers to realize better glycemic control and thereby achieve the promise of the DCCT.

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Year:  2005        PMID: 15857228     DOI: 10.1089/dia.2005.7.264

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  6 in total

1.  Development of the Likelihood of Low Glucose (LLG) algorithm for evaluating risk of hypoglycemia: a new approach for using continuous glucose data to guide therapeutic decision making.

Authors:  Timothy C Dunn; Gary A Hayter; Ken J Doniger; Howard A Wolpert
Journal:  J Diabetes Sci Technol       Date:  2014-04-17

Review 2.  Nutrition Informatics Applications in Clinical Practice: a Systematic Review.

Authors:  Jennifer C North; Kristine C Jordan; Julie Metos; John F Hurdle
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

3.  Closing the circle of care with new firmware for diabetes: MyDiaBase+RxChecker.

Authors:  A Michael Albisser; Rodolfo Alejandro; Marianne Sperlich; Camillo Ricordi
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

4.  Prescription checking device promises to resolve intractable hypoglycemia.

Authors:  A Michael Albisser; Rodolfo Alejandro; Marianne Sperlich; Camillo Ricordi
Journal:  J Diabetes Sci Technol       Date:  2009-05-01

5.  Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor.

Authors:  Carmen Pérez-Gandía; Gema García-Sáez; David Subías; Agustín Rodríguez-Herrero; Enrique J Gómez; Mercedes Rigla; M Elena Hernando
Journal:  J Diabetes Sci Technol       Date:  2018-03

6.  Home blood glucose prediction: clinical feasibility and validation in islet cell transplantation candidates.

Authors:  A M Albisser; D Baidal; R Alejandro; C Ricordi
Journal:  Diabetologia       Date:  2005-06-03       Impact factor: 10.122

  6 in total

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