These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: A graphical user interface for diabetes management that integrates glucose prediction and decision support.
    Author: Albisser AM.
    Journal: Diabetes Technol Ther; 2005 Apr; 7(2):264-73. PubMed ID: 15857228.
    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.
    [Abstract] [Full Text] [Related] [New Search]