Literature DB >> 28248127

A Pediatric Intensive Care Unit Bedside Computer Clinical Decision Support Protocol for Hyperglycemia Is Feasible, Safe and Offers Advantages.

Eliotte L Hirshberg1,2,3,4, Michael J Lanspa1,3, Emily L Wilson1,2, Katherine A Sward5,6, Al Jephson1, Gitte Y Larsen4, Alan H Morris1,3,5.   

Abstract

BACKGROUND: Computer clinical decision support (CDS) systems are uncommon in the pediatric intensive care unit (PICU), despite evidence suggesting they improve outcomes in adult ICUs. We reasoned that a bedside CDS protocol for intravenous insulin titration, eProtocol-insulin, would be feasible and safe in critically ill children.
METHODS: We retrospectively reviewed data from non-diabetic children admitted to the PICU with blood glucose (BG) ≥140 mg/dL who were managed with intravenous insulin by either unaided clinician titration or eProtocol-insulin. Primary outcomes were BG measurements in target range (80-110 mg/dL) and severe hypoglycemia (BG ≤40 mg/dL); secondary outcomes were 60-day mortality and PICU length of stay. We assessed bedside nurse satisfaction with the eProtocol-insulin protocol by using a 5-point Likert scale and measured clinician compliance with eProtocol-insulin recommendations.
RESULTS: Over 5 years, 69 children were titrated with eProtocol-insulin versus 104 by unaided clinicians. eProtocol-insulin achieved target range more frequently than clinician titration (41% vs. 32%, P < 0.001). Severe hypoglycemia was uncommon in both groups (4.3% of patients in eProtocol-insulin, 8.7% in clinician titration, P = 0.37). There were no differences in mean time to BG target or median BG between the groups. Mortality was 23% in both groups. Clinician compliance with eProtocol-insulin recommendations was 89%. Nurses believed that eProtocol-insulin was easy to understand and safer than clinician titration.
CONCLUSIONS: eProtocol-insulin is safe for titration of intravenous insulin in critically ill children. Clinical research protocols and quality improvement initiatives aimed at optimizing BG control should utilize detailed computer protocols that enable replicable clinician decisions.

Entities:  

Keywords:  Computer; Decision support; Glucose; Hyperglycemia; Pediatric; Protocol

Mesh:

Substances:

Year:  2017        PMID: 28248127      PMCID: PMC5359657          DOI: 10.1089/dia.2016.0423

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  39 in total

1.  Effects of two different levels of computerized decision support on blood glucose regulation in critically ill patients.

Authors:  Saeid Eslami; Nicolette F de Keizer; Dave A Dongelmans; Evert de Jonge; Marcus J Schultz; Ameen Abu-Hanna
Journal:  Int J Med Inform       Date:  2011-11-08       Impact factor: 4.046

2.  Effects of computer-based clinical decision support systems on physician performance and patient outcomes: a systematic review.

Authors:  D L Hunt; R B Haynes; S E Hanna; K Smith
Journal:  JAMA       Date:  1998-10-21       Impact factor: 56.272

Review 3.  Closed-loop insulin delivery - what lies between where we are and where we are going?

Authors:  Garry M Steil; Kerstin Rebrin
Journal:  Expert Opin Drug Deliv       Date:  2005-03       Impact factor: 6.648

4.  A trial of hyperglycemic control in pediatric intensive care.

Authors:  Duncan Macrae; Robert C Tasker; Diana Elbourne
Journal:  N Engl J Med       Date:  2014-04-03       Impact factor: 91.245

5.  Comparison of the effectiveness and safety of two insulin infusion protocols in the management of hyperglycemia in critically ill children.

Authors:  Claudiu Faraon-Pogaceanu; Kenneth J Banasiak; Eliotte L Hirshberg; Edward Vincent S Faustino
Journal:  Pediatr Crit Care Med       Date:  2010-11       Impact factor: 3.624

6.  The Pediatric Risk of Mortality III--Acute Physiology Score (PRISM III-APS): a method of assessing physiologic instability for pediatric intensive care unit patients.

Authors:  M M Pollack; K M Patel; U E Ruttimann
Journal:  J Pediatr       Date:  1997-10       Impact factor: 4.406

7.  Management of hyperglycemia in the pediatric intensive care unit; implementation of a glucose control protocol.

Authors:  Jennifer J Verhoeven; Jeannette B Brand; Mirjam M van de Polder; Koen F M Joosten
Journal:  Pediatr Crit Care Med       Date:  2009-11       Impact factor: 3.624

Review 8.  Clinical decision support systems in the pediatric intensive care unit.

Authors:  Elizabeth H Mack; Derek S Wheeler; Peter J Embi
Journal:  Pediatr Crit Care Med       Date:  2009-01       Impact factor: 3.624

9.  A replicable method for blood glucose control in critically Ill patients.

Authors:  Alan H Morris; James Orme; Jonathon D Truwit; Jay Steingrub; Colin Grissom; Kang H Lee; Guoliang L Li; B Taylor Thompson; Roy Brower; Mark Tidswell; Gordon R Bernard; Dean Sorenson; Katherine Sward; Hui Zheng; David Schoenfeld; Homer Warner
Journal:  Crit Care Med       Date:  2008-06       Impact factor: 7.598

10.  Alterations in glucose homeostasis in the pediatric intensive care unit: Hyperglycemia and glucose variability are associated with increased mortality and morbidity.

Authors:  Eliotte Hirshberg; Gitte Larsen; Heather Van Duker
Journal:  Pediatr Crit Care Med       Date:  2008-07       Impact factor: 3.624

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  2 in total

Review 1.  Hypoglycemia Prevention by Algorithm Design During Intravenous Insulin Infusion.

Authors:  Susan Shapiro Braithwaite; Lisa P Clark; Thaer Idrees; Faisal Qureshi; Oluwakemi T Soetan
Journal:  Curr Diab Rep       Date:  2018-03-26       Impact factor: 4.810

2.  Performance of an Electronic Decision Support System as a Therapeutic Intervention During a Multicenter PICU Clinical Trial: Heart and Lung Failure-Pediatric Insulin Titration Trial (HALF-PINT).

Authors:  Eliotte L Hirshberg; Jamin L Alexander; Lisa A Asaro; Kerry Coughlin-Wells; Garry M Steil; Debbie Spear; Cheryl Stone; Vinay M Nadkarni; Michael S D Agus
Journal:  Chest       Date:  2021-04-29       Impact factor: 9.410

  2 in total

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