Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-23T23:04:57.430Z Has data issue: false hasContentIssue false
  • English
  • Français

Implementing and integrating a radiation oncology information system as a pedagogical tool for undergraduate radiation therapy training

Published online by Cambridge University Press:  18 January 2017

Crispen Chamunyonga ,
Peta Rutledge ,
Peter Caldwell  and
Julie Burbery
Crispen Chamunyonga*
Affiliation:
School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Peta Rutledge
Affiliation:
School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Peter Caldwell
Affiliation:
School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
Julie Burbery
Affiliation:
School of Clinical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
*
Correspondence to: Crispen Chamunyonga, Lecturer, School of Clinical Sciences, Medical Radiation Sciences, Queensland University of Technology, QUT, 2 George Street, GPO Box 2434, Brisbane, QLD 4001, Australia. Tel: +61 7 31382273. E-mail: crispen.chamunyonga@qut.edu.au
Get access Rights & Permissions [Opens in a new window]

Abstract

Purpose

Radiation oncology information systems (OIS) play a crucial role in radiation therapy by ensuring accurate and safe delivery of treatment. A MOSAIQ OIS system is currently used to support undergraduate radiation therapist training at Queensland University of Technology. This review addresses the rationale for implementation and integration in teaching environments and explores the pedagogical benefits supported by educational theory.

Discussion

A review of MOSAIQ functionality shows potential to transform learning through the development of authentic and engaging learning tasks. It provides students with an opportunity to learn two-dimensional image matching through the use of digitally reconstructed radiographs and electronic portal images as well as three-dimensional image matching using computed tomography (CBCT) data in a safe learning environment without clinical time pressures. In addition, this provides the students with knowledge of quality assurance (QA) checks through the verification of treatment parameters and the transfer of information from the planning system to the treatment units. However, there are several potential challenges and practical considerations that need to be overcome.

Conclusion

The application of MOSAIQ OIS could potentially transform teaching and learning strategies for student radiation therapists. Increased knowledge and hands-on skills at undergraduate levels in areas such as image matching and QA can be powerful tools to drive the standards of practice a step further.

Keywords

critical pedagogyoncology information systemsradiation therapyteaching and learning
Type
Literature Review
Information
Journal of Radiotherapy in Practice , Volume 16 , Issue 2 , June 2017 , pp. 199 - 206
Check for updates
Copyright
© Cambridge University Press 2017 

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

1. Chan, A J, Islam, M K, Rosewall, T, Jaffray, D A, Easty, AC, Cafazzo, J A. The use of human factors methods to identify and mitigate safety issues in radiation therapy. Radiother Oncol 2010; 97 (3): 596–600.CrossRefGoogle ScholarPubMed
2. Mandal, A, Asthana, A, Aggarwal, L. Development of an electronic radiation oncology patient information management system. J Cancer Res Ther 2008; 4 (4): 178–185.CrossRefGoogle ScholarPubMed
3. Kirkpatrick, J P, Light, K L, Walker, R M et al. Implementing and integrating a clinically driven electronic medical record for radiation oncology in a large medical enterprise. Front Oncol 2013; 3: 69.CrossRefGoogle Scholar
4. Shakeshaft, J, Perez, M, Tremethick, L, Ceylan, A, Bailey, M. ACPSEM ROSG oncology-PACS and OIS working group recommendations for quality assurance. Australas Phys Eng Sci Med 2014; 37 (1): 3–13.CrossRefGoogle Scholar
5. Macklis, R, Meier, T, Barrett, P, Winehouse, M. 2175 analysis of error patterns in clinical radiotherapy. Int J Radiat Oncol Biol Phys 1996; 36 (1): 363–363.CrossRefGoogle Scholar
6. Amols, H I. New technologies in radiation therapy: ensuring patient safety, radiation safety and regulatory issues in radiation oncology. Health Phys 2008; 95 (5): 658–665.CrossRefGoogle ScholarPubMed
7. Barthelemy-Brichant, N, Sabatier, J, Dewé, W, Albert, A, Deneufbourg, J. Evaluation of frequency and type of errors detected by a computerized record and verify system during radiation treatment. Radiother Oncol 1999; 53 (2): 149–154.CrossRefGoogle ScholarPubMed
8. Patton, G, Gaffney, D, Moeller, J. Facilitation of radiotherapeutic error by computerized record and verify systems. Int J Radiat Oncol Biol Phys 2003; 56 (1): 50–57.CrossRefGoogle ScholarPubMed
9. Marks, L B, Light, K L, Hubbs, J L et al. The impact of advanced technologies on treatment deviations in radiation treatment delivery. Int J Radiat Oncol Biol Phys 2007; 69 (5): 1579–1586.CrossRefGoogle ScholarPubMed
10. IAEA. Human Health Reports No. 7. Record and Verify Systems for Radiation Treatment of Cancer: Acceptance Testing, Commissioning and Quality Control. Vienna: International Atomic Energy Agency, 2013.Google Scholar
11. Bridge, P, Gunn, T, Kastanis, L et al. The development and evaluation of a medical imaging training immersive environment. J Med Radiat Sci 2014; 61 (3): 159–165.CrossRefGoogle ScholarPubMed
12. Kane, J P. The impact of the VERT virtual reality system on teaching and learning associated with radiation therapy planning skills in the second year of the bachelor of radiation therapy. Thesis, Master of Health Sciences, University of Otago, 2014. http://hdl.handle.net/10523/5027. Accessed on 9th September 2016.Google Scholar
13. Montgomerie, D, Kane, J P, Leong, A, Mudie, B. Enhancing conceptual knowledge: an approach to using virtual environment for radiotherapy training in the classroom. J Radiother Pract 2016; 15 (2): 203–204.CrossRefGoogle Scholar
14. Laur, D. Authentic Learning Experiences: A Real-World Approach to Project-Based Learning. New York and London: Routledge, 2013; p. 2.CrossRefGoogle Scholar
15. Eady, M J, Lockyer, L. ‘Tools for learning: technology and teaching strategies’, Learning to Teach in the Primary School, Queensland University of Technology, Australia, 2013, p. 71.Google Scholar
16. Cuban, L, Ebray, I. Oversold and Underused: Computers in the Classroom. Cambridge, MA: Harvard University Press, 2001.CrossRefGoogle Scholar
17. HEA. Engaged student learning; high-impact strategies to enhance student achievement. York: Higher Education Academy, 2015. https://www.heacademy.ac.uk/system/files/engaged_student_learning_high-impact_pedagogies.pdf. Accessed on 9th September 2016.Google Scholar
18. Edwards-Groves, C. Interactive creative technologies: changing learning practices and pedagogies in the writing classroom. Australian Journal of Language and Literacy 2012; 35 (1): 99–113.CrossRefGoogle Scholar
19. Feenberg, A, Jan, P. The bursting boiler of digital education; critical pedagogy and philosophy of technology. Knowledge Cultures 2015; 3 (5): 132–148.Google Scholar
20. Okojie, M C, Olinzock, A A, Okojie-Boulder, T C. The pedagogy of technology integration. J Technol Stud 2006; 32 (1/2): 66–71.CrossRefGoogle Scholar
21. Biggs, J B, Tang, C S. Society for Research into Higher Education. Teaching for Quality Learning at University: Maidenhead, UK: McGraw-Hill/Society for Research into Higher Education/Open University Press, 2011.Google Scholar
22. IAEA. A handbook for the education of radiation therapists (RTTs). IAEA-TCS 2015; 58: 7–19.Google Scholar
23. Anderson, L W, Krathwohl, D R, Airasian, P W et al. A Taxonomy for Learning, Teaching, and Assessing: A Revision of Bloom’s Taxonomy of Educational Objectives (Complete edition). New York, NY: Longman, 2001.Google Scholar
24. Heppell, S. Discussion of how a pedagogical lens can assist teachers in making choices relating to ICT integration in the classroom 2012. https://tcameronne.wordpress.com/2012/10/17/pedagogicallenstechnology/. Accessed on 9th September 2016.Google Scholar
25. Miyata, C. SAMR: Bloom’s Taxonomy for Technology Education. ACI Information Group, Literacy Teaching and Teacher Education, 2015.Google Scholar
26. Tinto, V, Pusser, B. Moving from Theory to Action: Building a Model of Institutional Action for Student Success. Washington, DC: National Postsecondary Education Cooperative, 2016.Google Scholar
27. Hart, C, Hammer, S, Collins, P, Chardon, T. The real deal: using authentic assessment to promote student engagement in the first and second years of a regional law program. Legal Educ Rev 2011; 21 (1/2): 97–121.CrossRefGoogle Scholar
28. Welte, G K. Putting Students in Charge of Finding Real-World Examples Makes for a More Engaging Classroom. Faculty Focus, Higher Ed Teaching Strategies. Magna Publications, 2010. http://www.facultyfocus.com/articles/teaching-and-learning/putting-students-in-charge-of-finding-real-world-examples-makes-for-a-more-engaging-classroom/. Accessed on 16th October 2016.Google Scholar
29. Sambell, K, McDowell, L, Montgomery, C. Assessment for Learning in Higher Education. Abingdon, Oxon: Routledge, 2013.Google Scholar
30. Harvey, L. Transitions from higher education to work. A briefing paper prepared by Lee Harvey (Centre for Research and Evaluation, Sheffield Hallam University), with advice from ESECT and LTSN Generic Centre colleagues (2003). https://www.qualityresearchinternational.com/esecttools/esectpubs/harveytransitions.pdf. Accessed on 9th September 2016.Google Scholar
31. Little, B M. Employability for the workers: what does this mean? Education and Training 2011; 53 (1): 57–66.CrossRefGoogle Scholar
32. Bourner, T, Millican, J. Student-community engagement and graduate employability. Widening Partic Lifelong Learn 2011; 13 (2): 68–85.CrossRefGoogle Scholar
33. Medical Radiation Practice Board (MRPBA). Professional capabilities for medical radiation practice, Australia, p. 9. http://www.medicalradiationpracticeboard.gov.au/Registration/Professional-Capabilities.aspx. Accessed on 9th September.Google Scholar
34. Australian institute of Radiography (AIR). Professional practice standards for the accredited practitioner, 2013, p. 48. http://www.air.asn.au/cms_files/10_Publications/policies_guidelines/pps_air_dec2013.pdf. Accessed on 14th September 2016.Google Scholar
35. HCPC. Standards of proficiency – radiographers, 2013, p. 17. http://www.hcpcuk.org/assets/documents/10000DBDStandards_of_Proficiency_Radiographers.pdf. Accessed on 9th September 2016.Google Scholar
36. Hew, K F, Brush, T. Integrating technology into K-12 teaching and learning: current knowledge gaps and recommendations for future research. Educ Technol Res Dev 2007; 55 (3): 223–252.CrossRefGoogle Scholar