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 language | English (US) |
|---|---|
| Journal | Journal of diabetes science and technology |
| DOIs | |
| State | Accepted/In press - Jan 1 2018 |
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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
Development and Implementation of a Subcutaneous Insulin Clinical Decision Support Tool for Hospitalized Patients. / Mathioudakis, Nestoras Nicolas; Jeun, Rebecca; Godwin, Gerald; Perschke, Annette; Yalamanchi, Swaytha; Everett, Estelle; Greene, Peter Schuyler; Knight, Amy M; Yuan, Christina; Golden, Sherita Hill.
In: Journal of diabetes science and technology, 01.01.2018.Research output: Contribution to journal › Article
}
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 -