Hypoglycemia Prediction Model
Leveraging the Power of the EMR: Using a Real Time Prediction Model to Decrease Inpatient Hypoglycemic Events
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.
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
Accepts Healthy Volunteers
Genders Eligible for Study
Description
Inclusion Criteria:
- All adult inpatients having glucoses measured (point of care)
Exclusion Criteria:
- adults admitted to obstetrics
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: Single
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
Active Comparator: Alert
If glucose <90 mg/dl and hypoglycemia prediction score >35, then alert with suggestion for intervention sent to treating team
|
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. |
|
No Intervention: No alert
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.
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Time Frame |
|---|---|
|
The proportion of patients (in each group) who ultimately have a hypoglycemic event
Time Frame: 72 hours
|
72 hours
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Principal Investigator: Robert J Rushakoff, MD, University of California, San Francisco
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Study record dates
Study Major Dates
Study Start
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Estimate)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- 16-20565
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