Development and Implementation of a Subcutaneous Insulin Clinical Decision Support Tool for Hospitalized Patients

Nestoras Nicolas Mathioudakis, Rebecca Jeun, Gerald Godwin, Annette Perschke, Swaytha Yalamanchi, Estelle Everett, Peter Schuyler Greene, Amy M Knight, Christina Yuan, Sherita Hill Golden

Research output: Contribution to journalArticle

Abstract

Background: Insulin is one of the highest risk medications used in hospitalized patients. Multiple complex factors must be considered in determining a safe and effective insulin regimen. We sought to develop a computerized clinical decision support (CDS) tool to assist hospital-based clinicians in insulin management. Methods: Adapting existing clinical practice guidelines for inpatient glucose management, a design team selected, configured, and implemented a CDS tool to guide subcutaneous insulin dosing in non–critically ill hospitalized patients at two academic medical centers that use the EpicCare® electronic medical record (EMR). The Agency for Healthcare Research and Quality (AHRQ) best practices in CDS design and implementation were followed. Results: A CDS tool was developed in the form of an EpicCare SmartForm, which generates an insulin regimen by integrating information about the patient’s body weight, diabetes type, home and hospital insulin requirements, and nutritional status. Total daily recommended insulin doses are distributed into respective basal and nutritional doses with a tailored correctional insulin scale. Preimplementation, several approaches were used to communicate this new tool to clinicians, including emails, lectures, and videos. Postimplementation, a support team was available to address user technical issues. Feedback from stakeholders has been used to continuously refine the tool. Inclusion of the programming in the EMR vendor’s community library has allowed dissemination of the tool outside our institution. Conclusions: We have developed an EMR-based tool to guide SQ insulin dosing in non–critically ill hospitalized patients. Further studies are needed to evaluate adoption and clinical effectiveness of this intervention.

Original languageEnglish (US)
JournalJournal of diabetes science and technology
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Clinical Decision Support Systems
Insulin
Electronic medical equipment
Electronic Health Records
Practice Guidelines
Health Services Research
Electronic mail
Medical problems
Nutritional Status
Libraries
Glucose
Inpatients
Body Weight

Keywords

  • clinical decision support systems
  • diabetes mellitus
  • hospital management insulin
  • subcutaneous (SQ)

ASJC Scopus subject areas

  • Internal Medicine
  • Endocrinology, Diabetes and Metabolism
  • Bioengineering
  • Biomedical Engineering

Cite this

@article{e5894801a7df4a54889a9139abf6c903,
title = "Development and Implementation of a Subcutaneous Insulin Clinical Decision Support Tool for Hospitalized Patients",
abstract = "Background: Insulin is one of the highest risk medications used in hospitalized patients. Multiple complex factors must be considered in determining a safe and effective insulin regimen. We sought to develop a computerized clinical decision support (CDS) tool to assist hospital-based clinicians in insulin management. Methods: Adapting existing clinical practice guidelines for inpatient glucose management, a design team selected, configured, and implemented a CDS tool to guide subcutaneous insulin dosing in non–critically ill hospitalized patients at two academic medical centers that use the EpicCare{\circledR} electronic medical record (EMR). The Agency for Healthcare Research and Quality (AHRQ) best practices in CDS design and implementation were followed. Results: A CDS tool was developed in the form of an EpicCare SmartForm, which generates an insulin regimen by integrating information about the patient’s body weight, diabetes type, home and hospital insulin requirements, and nutritional status. Total daily recommended insulin doses are distributed into respective basal and nutritional doses with a tailored correctional insulin scale. Preimplementation, several approaches were used to communicate this new tool to clinicians, including emails, lectures, and videos. Postimplementation, a support team was available to address user technical issues. Feedback from stakeholders has been used to continuously refine the tool. Inclusion of the programming in the EMR vendor’s community library has allowed dissemination of the tool outside our institution. Conclusions: We have developed an EMR-based tool to guide SQ insulin dosing in non–critically ill hospitalized patients. Further studies are needed to evaluate adoption and clinical effectiveness of this intervention.",
keywords = "clinical decision support systems, diabetes mellitus, hospital management insulin, subcutaneous (SQ)",
author = "Mathioudakis, {Nestoras Nicolas} and Rebecca Jeun and Gerald Godwin and Annette Perschke and Swaytha Yalamanchi and Estelle Everett and Greene, {Peter Schuyler} and Knight, {Amy M} and Christina Yuan and Golden, {Sherita Hill}",
year = "2018",
month = "1",
day = "1",
doi = "10.1177/1932296818798036",
language = "English (US)",
journal = "Journal of diabetes science and technology",
issn = "1932-2968",
publisher = "Diabetes Technology Society",

}

TY - JOUR

T1 - Development and Implementation of a Subcutaneous Insulin Clinical Decision Support Tool for Hospitalized Patients

AU - Mathioudakis, Nestoras Nicolas

AU - Jeun, Rebecca

AU - Godwin, Gerald

AU - Perschke, Annette

AU - Yalamanchi, Swaytha

AU - Everett, Estelle

AU - Greene, Peter Schuyler

AU - Knight, Amy M

AU - Yuan, Christina

AU - Golden, Sherita Hill

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: Insulin is one of the highest risk medications used in hospitalized patients. Multiple complex factors must be considered in determining a safe and effective insulin regimen. We sought to develop a computerized clinical decision support (CDS) tool to assist hospital-based clinicians in insulin management. Methods: Adapting existing clinical practice guidelines for inpatient glucose management, a design team selected, configured, and implemented a CDS tool to guide subcutaneous insulin dosing in non–critically ill hospitalized patients at two academic medical centers that use the EpicCare® electronic medical record (EMR). The Agency for Healthcare Research and Quality (AHRQ) best practices in CDS design and implementation were followed. Results: A CDS tool was developed in the form of an EpicCare SmartForm, which generates an insulin regimen by integrating information about the patient’s body weight, diabetes type, home and hospital insulin requirements, and nutritional status. Total daily recommended insulin doses are distributed into respective basal and nutritional doses with a tailored correctional insulin scale. Preimplementation, several approaches were used to communicate this new tool to clinicians, including emails, lectures, and videos. Postimplementation, a support team was available to address user technical issues. Feedback from stakeholders has been used to continuously refine the tool. Inclusion of the programming in the EMR vendor’s community library has allowed dissemination of the tool outside our institution. Conclusions: We have developed an EMR-based tool to guide SQ insulin dosing in non–critically ill hospitalized patients. Further studies are needed to evaluate adoption and clinical effectiveness of this intervention.

AB - Background: Insulin is one of the highest risk medications used in hospitalized patients. Multiple complex factors must be considered in determining a safe and effective insulin regimen. We sought to develop a computerized clinical decision support (CDS) tool to assist hospital-based clinicians in insulin management. Methods: Adapting existing clinical practice guidelines for inpatient glucose management, a design team selected, configured, and implemented a CDS tool to guide subcutaneous insulin dosing in non–critically ill hospitalized patients at two academic medical centers that use the EpicCare® electronic medical record (EMR). The Agency for Healthcare Research and Quality (AHRQ) best practices in CDS design and implementation were followed. Results: A CDS tool was developed in the form of an EpicCare SmartForm, which generates an insulin regimen by integrating information about the patient’s body weight, diabetes type, home and hospital insulin requirements, and nutritional status. Total daily recommended insulin doses are distributed into respective basal and nutritional doses with a tailored correctional insulin scale. Preimplementation, several approaches were used to communicate this new tool to clinicians, including emails, lectures, and videos. Postimplementation, a support team was available to address user technical issues. Feedback from stakeholders has been used to continuously refine the tool. Inclusion of the programming in the EMR vendor’s community library has allowed dissemination of the tool outside our institution. Conclusions: We have developed an EMR-based tool to guide SQ insulin dosing in non–critically ill hospitalized patients. Further studies are needed to evaluate adoption and clinical effectiveness of this intervention.

KW - clinical decision support systems

KW - diabetes mellitus

KW - hospital management insulin

KW - subcutaneous (SQ)

UR - http://www.scopus.com/inward/record.url?scp=85059353942&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85059353942&partnerID=8YFLogxK

U2 - 10.1177/1932296818798036

DO - 10.1177/1932296818798036

M3 - Article

C2 - 30198324

AN - SCOPUS:85059353942

JO - Journal of diabetes science and technology

JF - Journal of diabetes science and technology

SN - 1932-2968

ER -