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Appl Clin Inform 2017; 08(02): 529-540
DOI: 10.4338/ACI-2016-11-RA-0187
Research Article
Schattauer GmbH

Insulin Bolus Calculator in a Pediatric Hospital

Safety and User Perceptions
Mohammad B. Ateya
1   Health Information Technology & Services, University of Michigan Health System, Ann Arbor, MI
,
Ranjit Aiyagari
2   Department of Pediatrics and Communicable Diseases, University of Michigan Health System, Ann Arbor, MI
,
Colleen Moran
3   Division of Pediatric Endocrinology, Department of Pediatrics and Communicable Diseases, University of Michigan Health System, Ann Arbor, MI
,
Kanakadurga Singer
3   Division of Pediatric Endocrinology, Department of Pediatrics and Communicable Diseases, University of Michigan Health System, Ann Arbor, MI
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Publikationsverlauf

01. November 2016

06. März 2017

Publikationsdatum:
21. Dezember 2017 (online)

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Summary

Background: Insulin dosing in hospitalized pediatric patients is challenging and requires dosing to be matched with the specific clinical and nutritional circumstances. We implemented a customized subcutaneous insulin bolus dose calculator tool integrated with the electronic health record to improve patient care. Here we describe this tool, its utilization and safety, and assess user satisfaction and perceptions of the tool.

Methods: Blood glucose results for all patients who received insulin with and without the calculator tool were compared to assess safety. To assess user perceptions and satisfaction, a survey was sent to all identified users who interacted with the tool during the period from May 2015 to the end of November 2015. Survey responses were summarized, mean user satisfaction calculated, and correlation of Likert scale items with overall satisfaction assessed.

Results: Hypoglycemia rates (2.2% and 2.9%, p = 0.17) and severe hypoglycemia rates (0.04% and 0.1%, p = 0.21) were similar for the groups that received insulin with and without the calculator tool. Overall satisfaction for all survey respondents was high (4.05, SD = 0.83). Physicians indicated a slightly higher satisfaction than nurses (4.33 versus 3.94, p = 0.04). User agreement with improvement of quality of care showed the highest correlation with overall satisfaction (r = 0.80, 95% CI 0.7 –0.87).

Conclusion: Implementation of an insulin calculator tool streamlined ordering and administration of insulin in a pediatric academic institution while maintaining patient safety. Users indicated high overall satisfaction with the tool.

Citation: Ateya MB, Aiyagari R, Moran C, Singer K. .:Insulin bolus calculator in a pediatric hospital: Safety and user perceptions. Appl Clin Inform 2017; 8: 529–540 https://doi.org/10.4338/ACI-2016-11-RA-0187

Keywords

Diabetes mellitus - electronic health records and systems - inpatient CPOE - medication administration records - orderset - clinical decision support - satisfaction

Protection of Human and Animal Subjects

The Institutional Review Board determined that this study is exempt from review.


 

  • References

  • 1 Moghissi ES, Korytkowski MT, DiNardo M, Einhorn D, Hellman R, Hirsch IB, Inzucchi S, Ismail-Beigi F, Kirkman M, Umpierrez G. American Association of Clinical Endocrinologists and American Diabetes Association consensus statement on inpatient glycemic control. Diabetes Care 2009; 32 (06) 1119-1131.
    CrossrefPubMedGoogle Scholar
  • 2 Ly TT, Maahs DM, Rewers A, Dunger D, Oduwole A, Jones TW. Assessment and management of hypoglycemia in children and adolescents with diabetes. Pediatr Diabetes 2014; 15 S20 180-192.
    CrossrefPubMedGoogle Scholar
  • 3 Gross TM, Kayne D, King A, Rother C, Juth S. A Bolus Calculator Is an Effective Means of Controlling Postprandial Glycemia in Patients on Insulin Pump Therapy. Diabetes Technol Ther 2003; 5 (03) 365-369.
    CrossrefPubMedGoogle Scholar
  • 4 Schmidt S, Meldgaard M, Serifovski N, Storm C, Christensen TM, Gade-Rasmussen B, Nørgaard K. Use of an Automated Bolus Calculator in MDI-Treated Type 1 Diabetes. Diabetes Care 2012; 35 (05) 984-990.
    CrossrefPubMedGoogle Scholar
  • 5 Lehmann CU, Conner KG, Cox JM. Preventing Provider Errors: Online Total Parenteral Nutrition Calculator. Pediatrics 2004; 113: 748-753.
    CrossrefPubMedGoogle Scholar
  • 6 Lehmann CU, Kim GR, Gujral R, Veltri MA, Clark JS, Miller MR. Decreasing errors in pediatric continuous intravenous infusions. Pediatr Crit Care Med 2006; 7 (03) 225-230.
    CrossrefPubMedGoogle Scholar
  • 7 Lee F, Teich JM, Spurr CD, Bates DW. Implementation of Physician Order Entry: User Satisfaction and Self-Reported Usage Patterns. J Am Med Informatics Assoc. The Oxford University Press 1996; 3 (01) 42-55.
    PubMedGoogle Scholar
  • 8 R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org
    PubMed
  • 9 Jason Bryer and Kimberly Speerschneider (2015). Likert: Functions to Analyze and Visualize Likert Type Items. http://jason.bryer.org/likert . http://github.com/jbryer/likert
    PubMed
  • 10 Weiner M, Gress T, Thiemann DR, Jenckes M, Reel SL, Mandell SF, Bass EB. Contrasting Views of Physicians and Nurses about an Inpatient Computer-based Provider Order-entry System. J Am Med Informatics Assoc 1999; 6 (03) 234-244.
    CrossrefPubMedGoogle Scholar
  • 11 Klonof DC. The Current Status of Bolus Calculator Decision-Support Software. J Diabetes Sci Technol 2012; 6 (05) 990-994.
    CrossrefPubMedGoogle Scholar