Literature DB >> 26121456

DAILY INPATIENT GLYCEMIC SURVEY (DINGS): A PROCESS TO REMOTELY IDENTIFY AND ASSIST IN THE MANAGEMENT OF HOSPITALIZED PATIENTS WITH DIABETES AND HYPERGLYCEMIA.

Carlos E Mendez, Ashar Ata, Joanne M Rourke, Steven C Stain, Guillermo Umpierrez.   

Abstract

OBJECTIVE: Hyperglycemia, hypoglycemia, and glycemic variability have been associated with increased morbidity, mortality, and overall costs of care in hospitalized patients. At the Stratton VA Medical Center in Albany, New York, a process aimed to improve inpatient glycemic control by remotely assisting primary care teams in the management of hyperglycemia and diabetes was designed.
METHODS: An electronic query comprised of hospitalized patients with glucose values <70 mg/dL or >350 mg/dL is generated daily. Electronic medical records (EMRs) are individually reviewed by diabetes specialist providers, and management recommendations are sent to primary care teams when applicable. Glucose data was retrospectively examined before and after the establishment of the daily inpatient glycemic survey (DINGS) process, and rates of hyperglycemia and hypoglycemia were compared.
RESULTS: Patient-day mean glucose slightly but significantly decreased from 177.6 ± 64.4 to 173.2 ± 59.4 mg/dL (P<.001). The percentage of patient-days with any value >350 mg/dL also decreased from 9.69 to 7.36% (P<.001), while the percentage of patient-days with mean glucose values in the range of 90 to 180 mg/dL increased from 58.1 to 61.4% (P<.001). Glycemic variability, assessed by the SD of glucose, significantly decreased from 53.9 to 49.8 mg/dL (P<.001). Moreover, rates of hypoglycemia (<70 mg/dL) decreased significantly by 41% (P<.001).
CONCLUSION: Quality metrics of inpatient glycemic control improved significantly after the establishment of the DINGS process within our facility. Prospective controlled studies are needed to confirm a causal association.

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Year:  2015        PMID: 26121456     DOI: 10.4158/EP14577.OR

Source DB:  PubMed          Journal:  Endocr Pract        ISSN: 1530-891X            Impact factor:   3.443


  7 in total

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Authors:  Kristen Kulasa; Patricia Juang
Journal:  Curr Diab Rep       Date:  2017-09       Impact factor: 4.810

Review 2.  Common Models Used for Inpatient Diabetes Management.

Authors:  Andjela T Drincic; Padmaja Akkireddy; Jon T Knezevich
Journal:  Curr Diab Rep       Date:  2018-02-14       Impact factor: 4.810

3.  Closing the Loop: Optimizing Diabetes Care in the Hospital by Addressing Dispersed Information in Electronic Health Records and Using Clinical Decision Support.

Authors:  Ariana R Pichardo-Lowden; Paul M Haidet
Journal:  J Diabetes Sci Technol       Date:  2018-12-10

Review 4.  Remote Monitoring and Consultation of Inpatient Populations with Diabetes.

Authors:  Robert J Rushakoff; Joshua A Rushakoff; Zachary Kornberg; Heidemarie Windham MacMaster; Arti D Shah
Journal:  Curr Diab Rep       Date:  2017-09       Impact factor: 4.810

Review 5.  The Case for Diabetes Population Health Improvement: Evidence-Based Programming for Population Outcomes in Diabetes.

Authors:  Sherita Hill Golden; Nisa Maruthur; Nestoras Mathioudakis; Elias Spanakis; Daniel Rubin; Mihail Zilbermint; Felicia Hill-Briggs
Journal:  Curr Diab Rep       Date:  2017-07       Impact factor: 4.810

Review 6.  The Financial Impact of an Inpatient Diabetes Management Service.

Authors:  Waqas Zia Haque; Andrew Paul Demidowich; Aniket Sidhaye; Sherita Hill Golden; Mihail Zilbermint
Journal:  Curr Diab Rep       Date:  2021-01-15       Impact factor: 4.810

7.  Electronic dashboard-based remote glycemic management program reduces length of stay and readmission rate among hospitalized adults.

Authors:  Yi-Jing Sheen; Chien-Chung Huang; Shih-Che Huang; Ching-Heng Lin; I-Te Lee; Wayne H-H Sheu
Journal:  J Diabetes Investig       Date:  2021-02-20       Impact factor: 4.232

  7 in total

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