Hypoglycemia Prediction Model

NCT ID: NCT03006510

Last Updated: 2021-10-08

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

498 participants

Study Classification

INTERVENTIONAL

Study Start Date

2017-01-31

Study Completion Date

2018-06-01

Brief Summary

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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.

Detailed Description

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Conditions

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Hypoglycemia

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

PREVENTION

Blinding Strategy

SINGLE

Caregivers

Study Groups

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Alert

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

Group Type ACTIVE_COMPARATOR

Hypoglycemia prediction alert

Intervention Type OTHER

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 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.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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Hypoglycemia prediction alert

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.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

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

Exclusion Criteria

* adults admitted to obstetrics
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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University of California, San Francisco

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Principal Investigators

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Robert J Rushakoff, MD

Role: PRINCIPAL_INVESTIGATOR

University of California, San Francisco

References

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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.

Reference Type BACKGROUND
PMID: 19564471 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22937877 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 12912719 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23065370 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 23248192 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 12716809 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 18056893 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24936545 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 25667368 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 22538139 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 24898687 (View on PubMed)

Other Identifiers

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16-20565

Identifier Type: -

Identifier Source: org_study_id

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