Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-22T00:41:17.336Z Has data issue: false hasContentIssue false

RISKS IN THE IMPLEMENTATION AND USE OF SMART PUMPS IN A PEDIATRIC INTENSIVE CARE UNIT: APPLICATION OF THE FAILURE MODE AND EFFECTS ANALYSIS

Published online by Cambridge University Press:  28 April 2014

Silvia Manrique-Rodríguez
Affiliation:
Pharmacy Service, Gregorio Marañón University Hospital
Amelia C Sánchez-Galindo
Affiliation:
Pediatric Intensive Care Unit, Gregorio Marañón University Hospital
Jesús López-Herce
Affiliation:
Pediatric Intensive Care Unit, Gregorio Marañón University Hospital
Miguel Ángel Calleja-Hernández
Affiliation:
Pharmacy Service, Virgen de las Nieves University Hospital
Irene Iglesias-Peinado
Affiliation:
Faculty of Pharmacy, Complutense University of Madrid, Ciudad Universitaria
Ángel Carrillo-Álvarez
Affiliation:
Pediatric Intensive Care Unit, Gregorio Marañón University Hospital
María Sanjurjo Sáez
Affiliation:
Pharmacy Service, Gregorio Marañón University Hospital
Cecilia M Fernández-Llamazares
Affiliation:
Pharmacy Service, Gregorio Marañón University Hospital

Abstract

Objectives: The aim of this study was to identify risk points in the different stages of the smart infusion pump implementation process to prioritize improvement measures.

Methods: Failure modes and effects analysis (FMEA) in the pediatric intensive care unit (PICU) of a General and Teaching Hospital. A multidisciplinary team was comprised of two intensive care pediatricians, two clinical pharmacists and the PICU nurse manager. FMEA was carried out before implementing CareFusion infusion smart pumps and eighteen months after to identify risk points during three different stages of the implementation process: creating a drug library; using the technology during clinical practice and analyzing the data stored using Guardrails® CQI v4.1 Event Reporter software.

Results: Several actions for improvement were taken. These included carrying out periodical reviews of the drug library, developing support documents, and including a training profile in the system so that alarms set off by real programming errors could be distinguished from those caused by incorrect use of the system. Eighteen months after the implementation, these measures had helped to reduce the likelihood of each risk point occurring and increase the likelihood of their detection.

Conclusions: Carrying out an FMEA made it possible to detect risk points in the use of smart pumps, take action to improve the tool, and adapt it to the PICU. Providing user training and support tools and continuously monitoring results helped to improve the usefulness of the drug library, increased users’ compliance with the drug library, and decreased the number of unnecessary alarms.

Type
Assessments
Copyright
Copyright © Cambridge University Press 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Leape, LL, Bates, DW, Cullen, DJ, et al. Systems analysis of adverse drug events. ADE prevention study group. JAMA. 1995;274:3543.CrossRefGoogle ScholarPubMed
2. Pepper, GA. Errors in drug administration by nurses. Am J Health Syst Pharm. 1995;52:390395.Google Scholar
3. Chapuis, C, Roustit, M, Bal, G, et al. Automated drug dispensing system reduces medication errors in an intensive care setting. Crit Care Med. 2010;38:22752281.Google Scholar
4. Oswald, S, Caldwell, R. Dispensing error rate after implementation of an automated pharmacy carousel system. Am J Health Syst Pharm. 2007;64:14271431.Google Scholar
5. Bates, DW, Leape, LL, Cullen, DJ, et al. Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA. 1998;280:13111316.CrossRefGoogle Scholar
6. Poon, EG, Keohane, CA, Yoon, CS, et al. Effect of bar-code technology on the safety of medication administration. N Engl J Med. 2010;362:16981707.CrossRefGoogle ScholarPubMed
7. KLAS. Smart pumps: In an area where decimal-point medication errors can be fatal, smart infusion pumps are adding a line of defense. Healthc Inform. 2008;25:20.Google Scholar
8. Wilson, K, Sullivan, M. Preventing medication errors with smart infusion technology. Am J Health Syst Pharm. 2004;61:177183.Google Scholar
9. Scanlon, M. The role of “smart” infusion pumps in patient safety. Pediatr Clin North Am. 2012;59:12571267.Google Scholar
10. Agius, CR. Intelligent infusion technologies: Integration of a smart system to enhance patient care. J Infus Nurs. 2012;35:364368.Google Scholar
11. Skledar, SJ, Niccolai, CS, Schilling, D, et al. Quality-improvement analytics for intravenous infusion pumps. Am J Health Syst Pharm. 2013;70:680686.Google Scholar
12. Manrique-Rodriguez, S, Sanchez-Galindo, A, Fernandez-Llamazares, CM, et al. Smart pump alerts: All that glitters is not gold. Int J Med Inform. 2012;81:344350.Google Scholar
13. Joint Commission on Accreditation of Healthcare Organizations. Complying with the FMEA requirements of the new patient safety standards (online monograph). http://www.jointcommission.org/ (accessed May 29, 2013).Google Scholar
14. Alonso-Ovies, A, Alvarez-Rodriguez, J, del Mar Garcia-Galvez, M, et al. Usefulness of failure mode and effects analysis to improve patient safety during the process of incorporating new nurses in an intensive care unit. Med Clin (Barc). 2010;135(Suppl 1):4553.CrossRefGoogle Scholar
15. Arvanitoyannis, IS, Varzakas, TH. Application of failure mode and effect analysis (FMEA) and cause and effect analysis in conjunction with ISO 22000 to a snails (helix aspersa) processing plant: A case study. Crit Rev Food Sci Nutr. 2009;49:607625.Google Scholar
16. Moss, J. Reducing errors during patient-controlled analgesia therapy through failure mode and effects analysis. Jt Comm J Qual Patient Saf. 2010;36:359364.Google Scholar
17. Institute for Healthcare Improvement. All failure modes and effects analysis tools (online monograph). Cambridge (Massachusetts). http://www.ihi.org/ihi/workspace/tools/fmea/AllTools.aspx#10 (accessed May 29, 2013).Google Scholar
18. Shebl, NA, Franklin, BD, Barber, N. Is failure mode and effect analysis reliable? J Patient Saf. 2009;5:8694.Google Scholar
19. Shebl, NA, Franklin, BD, Barber, N. Failure mode and effects analysis outputs: Are they valid? BMC Health Serv Res. 2012;12:150.Google Scholar
20. Kunac, DL, Reith, DM. Identification of priorities for medication safety in neonatal intensive care. Drug Saf. 2005;28:251261.Google Scholar
21. Wetterneck, TB, Skibinski, KA, Roberts, TL, et al. Using failure mode and effects analysis to plan implementation of smart i.v. pump technology. Am J Health Syst Pharm. 2006;63:15281538.CrossRefGoogle ScholarPubMed
22. Imhoff, M, Kuhls, S, Gather, U, Fried, R. Smart alarms from medical devices in the OR and ICU. Best Pract Res Clin Anaesthesiol. 2009;23:3950.Google Scholar
23. Manrique-Rodriguez, S, Sanchez-Galindo, A, Fernandez-Llamazares, CM, et al. Developing a drug library for smart pumps in a pediatric intensive care unit. Artif Intell Med. 2012;54:155161.Google Scholar
24. Manrique-Rodriguez, S, Sanchez-Galindo, A, Mora-Garcia, T, et al. Development of a compatibility chart for intravenous Y-site drug administration in a pediatric intensive care unit. J Infus Nurs. 2012;35:109114.CrossRefGoogle Scholar
25. Harding, AD. Intravenous smart pumps. J Infus Nurs. 2013;36:191194.CrossRefGoogle ScholarPubMed
26. Franklin, BD, Shebl, NA, Barber, N. Failure mode and effects analysis: Too little for too much? BMJ Qual Saf. 2012;21:607611.Google Scholar
27. Card, AJ, Ward, JR, Clarkson, PJ. Beyond FMEA: The structured what-if technique (SWIFT). J Healthc Risk Manag. 2012;31:2329.Google Scholar
28. Ashley, L, Armitage, G, Neary, M, Hollingsworth, G. A practical guide to failure mode and effects analysis in health care: Making the most of the team and its meetings. Jt Comm J Qual Patient Saf. 2010;36:351358.Google Scholar
29. Shebl, N, Franklin, B, Barber, N, Burnett, S, Parand, A. Failure mode and effects analysis: Views of hospital staff in the UK. J Health Serv Res Policy. 2012;17:3743.Google Scholar