@inproceedings{03b244f6dd0549918819831a01a2f992,
title = "IDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences",
abstract = "Diabetes is a complex disease affecting 29.1 million (9.3%) US citizens [1]. It is a chronic illness that needs continual medical care and ongoing patient self-management, education, and support [2]. There is no cure for diabetes, requiring patients to conduct frequent self-monitoring of blood glucose and dosing of insulin in many cases. Evidence has shown that patients are more adherent to their diabetes management plan when they incorporate personal lifestyle choices [3]. To address the challenge of empowering patients to better manage their diabetes, we have developed a novel mobile application prototype, iDECIDE, that refines rapid-acting insulin dose calculations by incorporating two important patient variables in addition to carbohydrates consumed that are not a part of standard insulin dose calculation algorithms: exercise and alcohol intake [4, 5]. A retrospective analysis for the calibration and evaluation of iDECIDE is underway by comparing recommendations made by the application against dosing recommendations made by insulin pumps.",
keywords = "Clinical decision support systems Mobile application Disease self-management, Diabetes mellitus, Insulin dosing",
author = "Buffy Lloyd and Danielle Groat and Cook, {Curtiss B.} and David Kaufman and Maria Grando",
note = "Publisher Copyright: {\textcopyright} 2015 IMIA and IOS Press.; 15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 ; Conference date: 19-08-2015 Through 23-08-2015",
year = "2015",
doi = "10.3233/978-1-61499-564-7-93",
language = "English (US)",
series = "Studies in Health Technology and Informatics",
publisher = "IOS Press",
pages = "93--97",
editor = "Andrew Georgiou and Sarkar, {Indra Neil} and {de Azevedo Marques}, {Paulo Mazzoncini}",
booktitle = "MEDINFO 2015",
}