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Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward.

Publication ,  Journal Article
Marsack, WJ; De Gagne, JC; Reid, J; Pakieser-Reed, K; Francisco, MA; Kang, HS
Published in: Nursing open
July 2023

This quality improvement project involved developing, implementing and evaluating an educational intervention using computer-based training (CBT) and high-fidelity simulation (HFS) to increase knowledge, confidence and compliance of nurses identifying sepsis. A one-group pretest-posttest design was used. Participants were nurses on a general ward of an academic medical centre. Study variables were measured over three timepoints: 2 weeks before, immediately after and 90 days after implementation. Data were collected from January 30, 2018, to June 22, 2018. SQUIRE 2.0 checklist for quality improvement reporting used. Improvements in knowledge of sepsis (F(2,83)  = 18.14, p < 0.001, ηp2  = 0.30) and confidence in early recognition of sepsis (F(2,83)  = 13.67, p < 0.001, ηp2  = 0.25) were found. Additionally, compliance with sepsis screening improved between the preimplementation and postimplementation period (χ2  = 13.633, df = 1, p < 0.001). Overall, the nurses evaluated their experience with the CBT and HFS as strongly positive. When designing and implementing an educational intervention on sepsis, a process for follow-up which provides reinforcement should be considered to retain nurses' knowledge.

Duke Scholars

Published In

Nursing open

DOI

EISSN

2054-1058

ISSN

2054-1058

Publication Date

July 2023

Volume

10

Issue

7

Start / End Page

4880 / 4887

Related Subject Headings

  • Sepsis
  • Patients' Rooms
  • Nurses
  • Humans
  • High Fidelity Simulation Training
  • Computers
  • Clinical Competence
  • Adult
  • 4205 Nursing
  • 4204 Midwifery
 

Citation

APA
Chicago
ICMJE
MLA
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Marsack, W. J., De Gagne, J. C., Reid, J., Pakieser-Reed, K., Francisco, M. A., & Kang, H. S. (2023). Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward. Nursing Open, 10(7), 4880–4887. https://doi.org/10.1002/nop2.1718
Marsack, William J., Jennie C. De Gagne, Joseph Reid, Katherine Pakieser-Reed, Mary Ann Francisco, and Hee Sun Kang. “Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward.Nursing Open 10, no. 7 (July 2023): 4880–87. https://doi.org/10.1002/nop2.1718.
Marsack WJ, De Gagne JC, Reid J, Pakieser-Reed K, Francisco MA, Kang HS. Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward. Nursing open. 2023 Jul;10(7):4880–7.
Marsack, William J., et al. “Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward.Nursing Open, vol. 10, no. 7, July 2023, pp. 4880–87. Epmc, doi:10.1002/nop2.1718.
Marsack WJ, De Gagne JC, Reid J, Pakieser-Reed K, Francisco MA, Kang HS. Evaluation of computer-based training and high-fidelity simulation to improve early recognition of sepsis on the adult general ward. Nursing open. 2023 Jul;10(7):4880–4887.
Journal cover image

Published In

Nursing open

DOI

EISSN

2054-1058

ISSN

2054-1058

Publication Date

July 2023

Volume

10

Issue

7

Start / End Page

4880 / 4887

Related Subject Headings

  • Sepsis
  • Patients' Rooms
  • Nurses
  • Humans
  • High Fidelity Simulation Training
  • Computers
  • Clinical Competence
  • Adult
  • 4205 Nursing
  • 4204 Midwifery