IDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences

Buffy Lloyd, Danielle Groat, Curtiss B. Cook, David Kaufman, Maria Grando

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)

    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.

    Original languageEnglish (US)
    Title of host publicationStudies in Health Technology and Informatics
    PublisherIOS Press
    Pages93-97
    Number of pages5
    Volume216
    ISBN (Print)9781614995630
    DOIs
    StatePublished - 2015
    Event15th World Congress on Health and Biomedical Informatics, MEDINFO 2015 - Sao Paulo, Brazil
    Duration: Aug 19 2015Aug 23 2015

    Publication series

    NameStudies in Health Technology and Informatics
    Volume216
    ISSN (Print)09269630
    ISSN (Electronic)18798365

    Other

    Other15th World Congress on Health and Biomedical Informatics, MEDINFO 2015
    CountryBrazil
    CitySao Paulo
    Period8/19/158/23/15

    Fingerprint

    Mobile Applications
    Patient Preference
    Insulin
    Medical problems
    Short-Acting Insulin
    Blood Glucose Self-Monitoring
    Carbohydrates
    Self Care
    Health care
    Calibration
    Glucose
    Life Style
    Patient Care
    Alcohols
    Blood
    Chronic Disease
    Education
    Pumps
    Exercise
    Monitoring

    Keywords

    • Clinical decision support systems Mobile application Disease self-management
    • Diabetes mellitus
    • Insulin dosing

    ASJC Scopus subject areas

    • Biomedical Engineering
    • Health Informatics
    • Health Information Management

    Cite this

    Lloyd, B., Groat, D., Cook, C. B., Kaufman, D., & Grando, M. (2015). IDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. In Studies in Health Technology and Informatics (Vol. 216, pp. 93-97). (Studies in Health Technology and Informatics; Vol. 216). IOS Press. https://doi.org/10.3233/978-1-61499-564-7-93

    IDECIDE : A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. / Lloyd, Buffy; Groat, Danielle; Cook, Curtiss B.; Kaufman, David; Grando, Maria.

    Studies in Health Technology and Informatics. Vol. 216 IOS Press, 2015. p. 93-97 (Studies in Health Technology and Informatics; Vol. 216).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Lloyd, B, Groat, D, Cook, CB, Kaufman, D & Grando, M 2015, IDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. in Studies in Health Technology and Informatics. vol. 216, Studies in Health Technology and Informatics, vol. 216, IOS Press, pp. 93-97, 15th World Congress on Health and Biomedical Informatics, MEDINFO 2015, Sao Paulo, Brazil, 8/19/15. https://doi.org/10.3233/978-1-61499-564-7-93
    Lloyd B, Groat D, Cook CB, Kaufman D, Grando M. IDECIDE: A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. In Studies in Health Technology and Informatics. Vol. 216. IOS Press. 2015. p. 93-97. (Studies in Health Technology and Informatics). https://doi.org/10.3233/978-1-61499-564-7-93
    Lloyd, Buffy ; Groat, Danielle ; Cook, Curtiss B. ; Kaufman, David ; Grando, Maria. / IDECIDE : A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences. Studies in Health Technology and Informatics. Vol. 216 IOS Press, 2015. pp. 93-97 (Studies in Health Technology and Informatics).
    @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",
    year = "2015",
    doi = "10.3233/978-1-61499-564-7-93",
    language = "English (US)",
    isbn = "9781614995630",
    volume = "216",
    series = "Studies in Health Technology and Informatics",
    publisher = "IOS Press",
    pages = "93--97",
    booktitle = "Studies in Health Technology and Informatics",

    }

    TY - GEN

    T1 - IDECIDE

    T2 - A Mobile Application for Insulin Dosing Using an Evidence Based Equation to Account for Patient Preferences

    AU - Lloyd, Buffy

    AU - Groat, Danielle

    AU - Cook, Curtiss B.

    AU - Kaufman, David

    AU - Grando, Maria

    PY - 2015

    Y1 - 2015

    N2 - 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.

    AB - 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.

    KW - Clinical decision support systems Mobile application Disease self-management

    KW - Diabetes mellitus

    KW - Insulin dosing

    UR - http://www.scopus.com/inward/record.url?scp=84951982158&partnerID=8YFLogxK

    UR - http://www.scopus.com/inward/citedby.url?scp=84951982158&partnerID=8YFLogxK

    U2 - 10.3233/978-1-61499-564-7-93

    DO - 10.3233/978-1-61499-564-7-93

    M3 - Conference contribution

    C2 - 26262017

    AN - SCOPUS:84951982158

    SN - 9781614995630

    VL - 216

    T3 - Studies in Health Technology and Informatics

    SP - 93

    EP - 97

    BT - Studies in Health Technology and Informatics

    PB - IOS Press

    ER -