Authors:

Research Videos ( author1@researchvideos.net )

Abstract :

The literature indicates that E-learning has the potential to mitigate barriers associated with time restrictions for trainers and trainees and evidence shows it to be more flexible, and convenient for learners in healthcare settings. This study aimed to develop and carry out a preliminary evaluation via a case study of an e-learning training platform designed for a novel neonatal sepsis risk monitor system (Digi-NewB). This study developed an online training platform to train clinicians in the use of a critical care medical device and carried out a preliminary evaluation of the platform via a case study. The e-learning platform was designed to supplement and enhance other training approaches. Further research is required to evaluate the effectiveness of this approach.

Keywords :

["E-learning","Patient monitoring system","Medical equipment","Training","Sepsis"]

Disciplines :

Social Sciences

Subdisciplines :

E-Learning, Health

Video Type :

2D

Publishing Licence :

Open-access

Submitted On :

2024/04/14

References :

{Borowski, M., Görges, M., Fried, R., Such, O., Wrede, C., Imhoff, M., 2011. Med. Dev. Alarms 56 (2), 73–83. https://doi.org/10.1515/bmt.2011.005. Apr.
Brand, D., 2012. Just a piece of equipment? The importance of medical device education.
J. Perioperat. Pract. 22 (12), 380–382. https://doi.org/10.1177/175045891602201202. Dec.
Brand, D., 2015. Attendance at NHS mandatory training sessions, 1987 Nurs. Stand. R. Coll. Nurs. G. B. 29 (24), 42–48. https://doi.org/10.7748/ns.29.24.42.e9139. Feb.
Brantley, A., et al., 2016. Clinical trial of an educational program to decrease monitor alarms in a medical intensive care unit. AACN Adv. Crit. Care 27 (3), 283–289. https://doi.org/10.4037/aacnacc2016110. Jul.
Braun, V., Clarke, V., 2006. Using thematic analysis in psychology. Qual. Res. Psychol. 3 (2), 77–101. https://doi.org/10.1191/1478088706qp063oa.
Challapalli, S.S.N., Kaushik, P., Suman, S., Shivahare, B.D., Bibhu, V., Gupta, A.D., 2021. Web development and performance comparison of web development technologies in Node.js and Python. In: 2021 International Conference on Technological Advancements and Innovations (ICTAI), pp. 303–307. https://doi.org/10.1109/
ICTAI53825.2021.9673464. Nov.
Digi-NewB - a new generation monitoring system in neonatology. http://www.digi-newb.eu/. (Accessed 22 October 2022).
Doyle, P.A., 2016. Improving safety of medical device use through training. In: Agrawal, A. (Ed.), Safety of Health IT: Clinical Case Studies. Springer International Publishing, Cham, pp. 241–252. https://doi.org/10.1007/978-3-319-31123-4_19.
Ewertsson, M., Gustafsson, M., Blomberg, K., Holmström, I.K., Allvin, R., 2015. Use of technical skills and medical devices among new registered nurses: a questionnaire study. Nurse Educ. Today 35 (12), 1169–1174. https://doi.org/10.1016/j.nedt.2015.05.006. Dec.
Fidler, R., et al., 2015. Human factors approach to evaluate the user interface of physiologic monitoring. J. Electrocardiol. 48 (6), 982–987. https://doi.org/10.1016/j.jelectrocard.2015.08.032. Dec.
Graham, K.C., Cvach, M., 2010. Monitor alarm fatigue: standardizing use of physiological monitors and decreasing nuisance alarms. Am. J. Crit. Care 19 (1), 28–34. https://doi.org/10.4037/ajcc2010651. Jan.
Grundgeiger, T., Kolb, L., Korb, M.O., Mengelkamp, C., Held, V., 2016. Training students to use syringe pumps: an experimental comparison of e-learning and classroom training. Biomed. Tech. 61 (2), 211–220. https://doi.org/10.1515/bmt-2014-0116. Apr.
IEC, 2015. IEC 62366-1. Medical devices — Part 1: Application of usability engineering to medical devices.
IEC, 2016. IEC/TR 62366-2. Medical devices - Part 2: Guidance on the application of usability engineering to medical devices.
Jang, H.W., Kim, K.-J., 2014. Use of online clinical videos for clinical skills training for medical students: benefits and challenges. BMC Med. Educ. 14 (1), 56. https://doi.org/10.1186/1472-6920-14-56. Mar.
Keers, R.N., Williams, S.D., Cooke, J., Ashcroft, D.M., 2013. Causes of medication administration errors in hospitals: a systematic review of quantitative and qualitative evidence. Drug Saf. 36 (11), 1045–1067. https://doi.org/10.1007/s40264-013-0090-2. Nov.
Lahti, M., Hätönen, H., Välimäki, M., 2014. Impact of e-learning on nurses’ and student nurses knowledge, skills, and satisfaction: a systematic review and meta-analysis. Int. J. Nurs. Stud. 51 (1), 136–149. https://doi.org/10.1016/j.ijnurstu.2012.12.017. Jan.
Lawn, S., Zhi, X., Morello, 2017. An integrative review of e-learning in the delivery of self-management support training for health professionals. BMC Med. Educ. 17 (183) https://doi.org/10.1186/s12909-017-1022-0.
Litman, L., Davachi, L., 2008. Distributed learning enhances relational memory consolidation. Learn. Mem. 15 (9), 711–716. https://doi.org/10.1101/lm.1132008. Sep.
Miller, G.E., 1990. The assessment of clinical skills/competence/performance. Acad. Med. J. Assoc. Am. Med. Coll. 65 (9 Suppl. l), S63–S67. https://doi.org/10.1097/00001888-199009000-00045. Sep.
Regmi, K., Jones, L., 2020. A systematic review of the factors – enablers and barriers –affecting e-learning in health sciences education. BMC Med. Educ. 20 (1), 91. https://doi.org/10.1186/s12909-020-02007-6. Mar.
Scalese, R.J., Obeso, V.T., Issenberg, S.B., 2008. Simulation technology for skills training and competency assessment in medical education. J. Gen. Intern. Med. 23 (1), 46–49. https://doi.org/10.1007/s11606-007-0283-4. Jan.
Sinclair, P.M., Kable, A., Levett-Jones, T., Booth, D., 2016. The effectiveness of Internet-based e-learning on clinician behaviour and patient outcomes: a systematic review. Int. J. Nurs. Stud. 57, 70–81. https://doi.org/10.1016/j.ijnurstu.2016.01.011. May.
Son, L.K., Simon, D.A., 2012. Distributed learning: data, metacognition, and educational implications. Educ. Psychol. Rev. 24 (3), 379–399. https://doi.org/10.1007/s10648-012-9206-y. Sep.
Sowan, A.K., et al., 2021. Improving the safety, effectiveness, and efficiency of clinical alarm systems: simulation-based usability testing of physiologic monitors. JMIR Nurs. 4 (1), e20584 https://doi.org/10.2196/20584. Mar.
Sowan, A.K., Vera, A.G., Fonseca, E.I., Reed, C.C., Tarriela, A.F., Berndt, A.E., 2017. Nurse competence on physiologic monitors use: toward eliminating alarm fatigue in intensive care units. Open Med. Inf. J. 11, 1–11. https://doi.org/10.2174/1874431101711010001. Apr.
Vallée, A., Blacher, J., Cariou, A., Sorbets, E., 2020. Blended learning compared to traditional learning in medical education: systematic review and meta-analysis. J. Med. Internet Res. 22 (8), e16504 https://doi.org/10.2196/16504. Aug.
Värri, A., Kallonen, A., Helander, E., Ledesma, A., Pladys, P., 2018. The Digi-NewB project for preterm infant sepsis risk and maturity analysis. Finn. J. EHealth EWelfare 10 (2–3). https://doi.org/10.23996/fjhw.69152. Art. no. 2–3, May.
Walsh, K., 2018. Cost and value in e-learning: the perspective of the learner. BMJ Simul. Technol. Enhanc. Learn. https://doi.org/10.1136/bmjstel-2017-000239.
Wung, S.-F., Schatz, M.R., 2018. Critical care nurses’ cognitive ergonomics related to medical device alarms. Crit. Care Nurs. Clin. 30 (2), 191–202. https://doi.org/10.1016/j.cnc.2018.02.002. Jun.}

RVOI :

DOI :

Scan this QR code :