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Hypoglycemia Prediction Model

Primary Purpose

Hypoglycemia

Status
Completed
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
Hypoglycemia prediction alert
Sponsored by
University of California, San Francisco
About
Eligibility
Locations
Arms
Outcomes
Full info

About this trial

This is an interventional prevention trial for Hypoglycemia focused on measuring inpatient diabetes, hypoglycemia

Eligibility Criteria

18 Years - undefined (Adult, Older Adult)All SexesDoes not accept healthy volunteers

Inclusion Criteria:

  • All adult inpatients having glucoses measured (point of care)

Exclusion Criteria:

  • adults admitted to obstetrics

Sites / Locations

    Arms of the Study

    Arm 1

    Arm 2

    Arm Type

    Active Comparator

    No Intervention

    Arm Label

    Alert

    No alert

    Arm Description

    If glucose <90 mg/dl and hypoglycemia prediction score >35, then alert with suggestion for intervention sent to treating team

    Routine standard care. If glucose <90 mg/dl and hypoglycemia prediction score >35, then report for investigators will be collected, but no active alert will be sent to teams.

    Outcomes

    Primary Outcome Measures

    The proportion of patients (in each group) who ultimately have a hypoglycemic event

    Secondary Outcome Measures

    Full Information

    First Posted
    December 28, 2016
    Last Updated
    October 1, 2021
    Sponsor
    University of California, San Francisco
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    1. Study Identification

    Unique Protocol Identification Number
    NCT03006510
    Brief Title
    Hypoglycemia Prediction Model
    Official Title
    Leveraging the Power of the EMR: Using a Real Time Prediction Model to Decrease Inpatient Hypoglycemic Events
    Study Type
    Interventional

    2. Study Status

    Record Verification Date
    October 2021
    Overall Recruitment Status
    Completed
    Study Start Date
    January 2017 (undefined)
    Primary Completion Date
    June 1, 2018 (Actual)
    Study Completion Date
    June 1, 2018 (Actual)

    3. Sponsor/Collaborators

    Responsible Party, by Official Title
    Sponsor
    Name of the Sponsor
    University of California, San Francisco

    4. Oversight

    Data Monitoring Committee
    No

    5. Study Description

    Brief Summary
    Our goal for this Learning Healthcare System Demonstration Project is to reduce the rate of inpatient hypoglycemia. Hypoglycemia can result in longer lengths of stay and increased morbidity and mortality (ie falls and cardiovascular or cerebral events). The group at Washington University (WSL) developed a predictive hypoglycemia risk score. Using current glucose, body weight, creatinine clearance, insulin type and dosing, and oral diabetic therapy, they identified patients at high risk for hypoglycemia and then provided in-person education to the providers of these patients. This resulted in a 68% reduction in severe hypoglycemia (blood glucose < 40 mg/dL). This approach required significant personnel hours and is difficult to replicate in other systems. The investigators will implement an EHR-based intervention at UCSF to predict which patients are at high risk of inpatient hypoglycemia and take action to prevent the hypoglycemic event. In real time, all adult (non OB) patients with a glucose < 90, and a high risk of future hypoglycemia (based on the WSL formula) will be identified. Patients will be randomly assigned to intervention or no intervention (current standard care). The intervention will consist of an automated provider alert with recommendations on what adjustments could be made to avoid a potentially serious hypoglycemic event. The outcomes that will be measured include: 1) reductions in serious hypoglycemic events, 2) monitor the changes made by providers as a result of alerts in order to study provider behavior and identify future areas of intervention, and 3) provider satisfaction with the alert system.

    6. Conditions and Keywords

    Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
    Hypoglycemia
    Keywords
    inpatient diabetes, hypoglycemia

    7. Study Design

    Primary Purpose
    Prevention
    Study Phase
    Not Applicable
    Interventional Study Model
    Parallel Assignment
    Masking
    Care Provider
    Allocation
    Randomized
    Enrollment
    498 (Actual)

    8. Arms, Groups, and Interventions

    Arm Title
    Alert
    Arm Type
    Active Comparator
    Arm Description
    If glucose <90 mg/dl and hypoglycemia prediction score >35, then alert with suggestion for intervention sent to treating team
    Arm Title
    No alert
    Arm Type
    No Intervention
    Arm Description
    Routine standard care. If glucose <90 mg/dl and hypoglycemia prediction score >35, then report for investigators will be collected, but no active alert will be sent to teams.
    Intervention Type
    Other
    Intervention Name(s)
    Hypoglycemia prediction alert
    Intervention Description
    In real time, for a patient with a glucose <90 mg/d, using a hypoglycemia prediction model that takes into account patient weight, renal function, eating and insulin dosing a risk score is produced. If the Risk score is >35, then the patient is determined to be at risk for hypoglycemia in the next 72 hours. If a patient is determined to be at risk for hypoglycemia, the following will occur: Alert will be generated and sent via "careweb" a pager alert system that sends the alert specifically to the current oncall provider The "alert" also points the provider to the EMR order section where a formal more detailed alert gives recommendationsd for changes in insulin dosing to potentially prevent hypoglycemia.
    Primary Outcome Measure Information:
    Title
    The proportion of patients (in each group) who ultimately have a hypoglycemic event
    Time Frame
    72 hours

    10. Eligibility

    Sex
    All
    Minimum Age & Unit of Time
    18 Years
    Accepts Healthy Volunteers
    No
    Eligibility Criteria
    Inclusion Criteria: All adult inpatients having glucoses measured (point of care) Exclusion Criteria: adults admitted to obstetrics
    Overall Study Officials:
    First Name & Middle Initial & Last Name & Degree
    Robert J Rushakoff, MD
    Organizational Affiliation
    University of California, San Francisco
    Official's Role
    Principal Investigator

    12. IPD Sharing Statement

    Citations:
    PubMed Identifier
    19564471
    Citation
    Turchin A, Matheny ME, Shubina M, Scanlon JV, Greenwood B, Pendergrass ML. Hypoglycemia and clinical outcomes in patients with diabetes hospitalized in the general ward. Diabetes Care. 2009 Jul;32(7):1153-7. doi: 10.2337/dc08-2127.
    Results Reference
    background
    PubMed Identifier
    22937877
    Citation
    Nirantharakumar K, Marshall T, Kennedy A, Narendran P, Hemming K, Coleman JJ. Hypoglycaemia is associated with increased length of stay and mortality in people with diabetes who are hospitalized. Diabet Med. 2012 Dec;29(12):e445-8. doi: 10.1111/dme.12002.
    Results Reference
    background
    PubMed Identifier
    12912719
    Citation
    Kagansky N, Levy S, Rimon E, Cojocaru L, Fridman A, Ozer Z, Knobler H. Hypoglycemia as a predictor of mortality in hospitalized elderly patients. Arch Intern Med. 2003 Aug 11-25;163(15):1825-9. doi: 10.1001/archinte.163.15.1825.
    Results Reference
    background
    PubMed Identifier
    23065370
    Citation
    Carey M, Boucai L, Zonszein J. Impact of hypoglycemia in hospitalized patients. Curr Diab Rep. 2013 Feb;13(1):107-13. doi: 10.1007/s11892-012-0336-x.
    Results Reference
    background
    PubMed Identifier
    23248192
    Citation
    Garg R, Hurwitz S, Turchin A, Trivedi A. Hypoglycemia, with or without insulin therapy, is associated with increased mortality among hospitalized patients. Diabetes Care. 2013 May;36(5):1107-10. doi: 10.2337/dc12-1296. Epub 2012 Dec 17.
    Results Reference
    background
    PubMed Identifier
    12716809
    Citation
    Desouza C, Salazar H, Cheong B, Murgo J, Fonseca V. Association of hypoglycemia and cardiac ischemia: a study based on continuous monitoring. Diabetes Care. 2003 May;26(5):1485-9. doi: 10.2337/diacare.26.5.1485.
    Results Reference
    background
    PubMed Identifier
    18056893
    Citation
    Schwartz AV, Vittinghoff E, Sellmeyer DE, Feingold KR, de Rekeneire N, Strotmeyer ES, Shorr RI, Vinik AI, Odden MC, Park SW, Faulkner KA, Harris TB; Health, Aging, and Body Composition Study. Diabetes-related complications, glycemic control, and falls in older adults. Diabetes Care. 2008 Mar;31(3):391-6. doi: 10.2337/dc07-1152. Epub 2007 Dec 4. Erratum In: Diabetes Care. 2008 May;31(5):1089.
    Results Reference
    background
    PubMed Identifier
    24936545
    Citation
    Dendy JA, Chockalingam V, Tirumalasetty NN, Dornelles A, Blonde L, Bolton PM, Meadows RY, Andrews SS. Identifying risk factors for severe hypoglycemia in hospitalized patients with diabetes. Endocr Pract. 2014 Oct;20(10):1051-6. doi: 10.4158/EP13467.OR.
    Results Reference
    background
    PubMed Identifier
    25667368
    Citation
    Ulmer BJ, Kara A, Mariash CN. Temporal occurrences and recurrence patterns of hypoglycemia during hospitalization. Endocr Pract. 2015 May;21(5):501-7. doi: 10.4158/EP14355.OR. Epub 2015 Feb 9.
    Results Reference
    background
    PubMed Identifier
    22538139
    Citation
    Elliott MB, Schafers SJ, McGill JB, Tobin GS. Prediction and prevention of treatment-related inpatient hypoglycemia. J Diabetes Sci Technol. 2012 Mar 1;6(2):302-9. doi: 10.1177/193229681200600213.
    Results Reference
    background
    PubMed Identifier
    24898687
    Citation
    Kilpatrick CR, Elliott MB, Pratt E, Schafers SJ, Blackburn MC, Heard K, McGill JB, Thoelke M, Tobin GS. Prevention of inpatient hypoglycemia with a real-time informatics alert. J Hosp Med. 2014 Oct;9(10):621-6. doi: 10.1002/jhm.2221. Epub 2014 Jun 5.
    Results Reference
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    Hypoglycemia Prediction Model

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