Modelling a Computed Tomography service using mixed Operational Research methods

References

• Ackermann, F. (2012). Problem structuring methods “in the Dock”: Arguing the case for Soft or European. Journal of Operational Research, 219(3), 652–658. https://doi.org/10.1016/j.ejor.2011.11.014
   Google Scholar
• Ackoff, R. L. (2010). Systems thinking for curious managers. Triarchy Press.
   Google Scholar
• Adam, E. J. (2006). Changes in the computed tomography patient population. European Radiology, Supplement, 16(4), 38–42. https://doi.org/10.1007/s10406-006-0186-1
   Google Scholar
• Bell, S., Berg, T., & Morse, S. (2019). Towards an understanding of rich picture interpretation. Systemic Practice and Action Research, 32(6), 601–614. https://doi.org/10.1007/s11213-018-9476-5
   Web of Science ®Google Scholar
• Berg, T. (2015). Rich Picture: The role of the facilitator. Systemic Practice and Action Research, 28(1), 67–77. https://doi.org/10.1007/s11213-014-9318-z
   Web of Science ®Google Scholar
• Bleiker, J., Knapp, K. M., Morgan-Trimmer, S., & Hopkins, S. J. (2018). “It’s what’s behind the mask”: Psychological diversity in compassionate patient care. Radiography, 24, S28–32. https://doi.org/10.1016/J.RADI.2018.06.004
   PubMed Web of Science ®Google Scholar
• Boland, G. W. L. (2008). Enhancing CT productivity: Strategies for increasing capacity. American Journal of Roentgenology, 191(1), 3–10. https://doi.org/10.2214/AJR.07.3208
   PubMed Web of Science ®Google Scholar
• Booker, M. T., O’Connell, R. J., Desai, B., & Duddalwar, V. A. (2016). Quality improvement with discrete event simulation: A primer for radiologists. Journal of the American College of Radiology, 13(4), 417–423. https://doi.org/10.1016/j.jacr.2015.11.028
   PubMed Web of Science ®Google Scholar
• Brady A P. (2011). Measuring Consultant Radiologist workload: method and results from a national survey. Insights Imaging, 2(3), 247–260. doi:10.1007/s13244-011-0094-3.
   PubMedGoogle Scholar
• Brailsford, S., & Vissers, J. (2011). OR in healthcare: A European perspective. European Journal of Operational Research, 212(2), 223–234. https://doi.org/10.1016/j.ejor.2010.10.026
   Web of Science ®Google Scholar
• Checkland, P. (1999). Systems thinking, systems practice. John Wiley. https://books.google.ie/books?id=Ct0PAQAAMAAJ
   Google Scholar
• Conlon, M., & Molloy, O. (2019). Knowledge management in healthcare: Information requirements when creating a decision support tool in radiology. IC3K 2019 - Proceedings of the 11th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 3(Ic3k), 317–324. https://doi.org/10.5220/0008352703170324
   Google Scholar
• Crowe, S., Brown, K., Tregay, J., Wray, J., Knowles, R., Ridout, D. A., Bull, C., & Utley, M. (2017). Combining qualitative and quantitative operational research methods to inform quality improvement in pathways that span multiple settings. BMJ Quality & Safety, 26(8), 641–652. https://doi.org/10.1136/bmjqs-2016-005636
   PubMed Web of Science ®Google Scholar
• Crowe S, Knowles R, Wray J, Tregay J, Ridout D A, Utley M, Franklin R, Bull C L and Brown K L. (2016). Identifying improvements to complex pathways: evidence synthesis and stakeholder engagement in infant congenital heart disease. BMJ Open, 6(6), e010363. doi:10.1136/bmjopen-2015-010363.
   PubMed Web of Science ®Google Scholar
• CSO. (2015). Regional Population Projections 2016 - 2031 - CSO -. Central Statistics Office. http://www.cso.ie/en/releasesandpublications/er/rpp/regionalpopulationprojections2016-2031/
   Google Scholar
• Cullen, P. (2020). Outpatient waiting list surpasses 600,000 for first time. The Irish Times. https://www.irishtimes.com/news/health/outpatient-waiting-list-surpasses-600-000-for-first-time-1.4330620
   Google Scholar
• Currie, C. S., Fowler, J. W., Kotiadis, K., Monks, T., Stephan Onggo, B., Robertson, D. A., Tako, A. A., & Currie, S. (2020). How simulation modelling can help reduce the impact of COVID-19. https://doi.org/10.1080/17477778.2020.1751570
   Google Scholar
• Dodds, S., & Debenham, P. (2016). Learning anti-chaos design in emergency flow. Journal of Improvement Science, 32, 1–14. http://www.journalofimprovementscience.net
   Google Scholar
• Drucker, P. F. (1998). The discipline of innovation. Harvard Business Review, 76(6), 149–157.
   PubMed Web of Science ®Google Scholar
• ESR. (2019). Patient safety in medical imaging: A joint paper of the European Society of Radiology (ESR) and the European Federation of Radiographer Societies (EFRS). Radiography, 25(2), e26–38. https://doi.org/10.1016/J.RADI.2019.01.009
   PubMed Web of Science ®Google Scholar
• Famiglietti, R. M., Norboge, E. C., Boving, V., Langabeer, J. R., Buchholz, T. A., & Mikhail, O. (2017). Using discrete-event simulation to promote quality improvement and efficiency in a radiation oncology treatment center. Quality Management in Health Care, 26(4), 184–189. https://doi.org/10.1097/QMH.0000000000000145
   PubMed Web of Science ®Google Scholar
• Flood, R., & Wright, L. (2022). Measuring utilisation of CT scanners within an acute trust. Authors. Journal of Improvement Science, 93, 1–19. ISSN 2054–6629.
   Google Scholar
• Fone, D., Hollinghurst, S., Temple, M., Round, A., Lester, N., Weightman, A., Roberts, K., Coyle, E., Bevan, G., & Palmer, S. (2003). Systematic review of the use and value of computer simulation modelling in population health and health care delivery. Journal of Public Health Medicine, 25(4), 325–335. https://doi.org/10.1093/pubmed/fdg075
   PubMedGoogle Scholar
• Forrester, J. W. (1994). System dynamics, systems thinking, and soft or. System Dynamics Review, 10(2), 245–256. https://doi.org/10.1002/sdr.4260100211
   Web of Science ®Google Scholar
• Greenhalgh, T., Hinton, L., Finlay, T., Ma, A. M., Fahy, N., Clyde, B., & Chant, A. (2019). Frameworks for supporting patient and public involvement in research: Systematic review and co-design pilot. Health Expectations, 22(4), 785–801. https://doi.org/10.1111/hex.12888
   PubMed Web of Science ®Google Scholar
• Gunal, M. M. (2012). A guide for building hospital simulation models. Health Systems, 1(1), 17–25. https://doi.org/10.1057/hs.2012.8
   Google Scholar
• Harper, A., Mustafee, N., & Yearworth, M. (2021). Facets of trust in simulation studies. European Journal of Operational Research, 289(1), 197–213. https://doi.org/10.1016/j.ejor.2020.06.043
   Web of Science ®Google Scholar
• Hyde, E., & Hardy, M. (2021). Patient centred care in diagnostic radiography (Part 2): A qualitative study of the perceptions of service users and service deliverers. Radiography, 27(2), 322–331. https://doi.org/10.1016/j.radi.2020.09.008
   PubMed Web of Science ®Google Scholar
• Irish Cancer Society. (2016). Access to Diagnostics Used to Detect Cancer. http://health.gov.ie/future-health/financial-reform/private-health-insurance-2/
   Google Scholar
• Kotiadis, K., & Tako, A. A. (2017). Facilitated post-model coding in discrete event simulation (DES): A case study in healthcare. European Journal of Operational Research, 266(3), 1120–1133. https://doi.org/10.1016/j.ejor.2017.10.047
   Web of Science ®Google Scholar
• Kotiadis, K., Tako, A. A., & Vasilakis, C. (2014). A participative and facilitative conceptual modelling framework for discrete event simulation studies in healthcare. The Journal of the Operational Research Society, 65(2), 197–213. https://doi.org/10.1057/jors.2012.176
   Web of Science ®Google Scholar
• Kunc, M., Malpass, J., & White, L. (2016). Behavioral Operational Research (J. M. Martin Kunc & L. White, Eds. Palgrave Macmillan UK. https://doi.org/10.1057/978-1-137-53551-1
   Google Scholar
• Lamé, G., Crowe, S., & Barclay, M. (2020). “What’s the evidence?”—towards more empirical evaluations of the impact of or interventions in healthcare. Health Systems, 00(00), 1–9. https://doi.org/10.1080/20476965.2020.1857663
   Google Scholar
• Lamé, G., Jouini, O., & Stal Le Cardinal, J. (2020). Combining soft systems methodology, ethnographic observation, and discrete-event simulation: A case study in cancer care. The Journal of the Operational Research Society, 71(10), 1545–1562. https://doi.org/10.1080/01605682.2019.1610339
   Web of Science ®Google Scholar
• Law, A., & Kelton, D. (1991). Simulation modeling and analysis. 2nd. ed. In W. D. Kelton, Ed. . New York: McGraw-Hill.
   Google Scholar
• Mingers, J., & Rosenhead, J. (2004). Problem structuring methods in action. European Journal of Operational Research, 152(3), 530–554. https://doi.org/10.1016/S0377-2217(03)00056-0
   Web of Science ®Google Scholar
• Monks, T., Currie, C. S. M., Onggo, B. S., Robinson, S., Kunc, M., & Taylor, S. J. E. (2019). Strengthening the reporting of empirical simulation studies: Introducing the STRESS guidelines. Journal of Simulation, 13(1), 55–67. https://doi.org/10.1080/17477778.2018.1442155
   Web of Science ®Google Scholar
• Monks, T., Robinson, S., & Kotiadis, K. (2014). Learning from discrete-event simulation: Exploring the high involvement hypothesis. European Journal of Operational Research, 235(1), 195–205. https://doi.org/10.1016/j.ejor.2013.10.003
   Web of Science ®Google Scholar
• Monks, T., Robinson, S., & Kotiadis, K. (2016). Can involving clients in simulation studies help them solve their future problems? A transfer of learning experiment. European Journal of Operational Research, 249(3), 919–930. https://doi.org/10.1016/j.ejor.2015.08.037
   Web of Science ®Google Scholar
• Morgan, J. S., Belton, V., & Howick, S. (2016). Lessons from mixing or methods in practice: Using DES and SD to explore a radiotherapy treatment planning process. Health Systems, 5(3), 166–177. https://doi.org/10.1057/hs.2016.4
   Web of Science ®Google Scholar
• Murray, T. E., Halligan, J. J., & Lee, M. J. (2017). Inefficiency, dignity and patient experience: Is it time for separate outpatient diagnostics? The British Journal of Radiology, 90(1080), 4–6. https://doi.org/10.1259/bjr.20170574
   Web of Science ®Google Scholar
• Naylor, A. F. (1992). Quantitative assessment of radiology workload and facilities requirements. European Journal of Radiology, 15(3), 270–275. https://doi.org/10.1016/0720-048X(92)90121-O
   PubMed Web of Science ®Google Scholar
• Oliva R and Sterman J D. (2001). Cutting Corners and Working Overtime: Quality Erosion in the Service Industry. Management Science, 47(7), 894–914. doi:10.1287/mnsc.47.7.894.9807.
   Web of Science ®Google Scholar
• Ondategui-Parra, S., Bhagwat, J. G., Gill, I. E., Nathanson, E., Seltzer, S., & Ros, P. R. (2004). Essential practice performance measurement. Journal of the American College of Radiology, 1(8), 559–566. https://doi.org/10.1016/j.jacr.2004.03.020
   PubMedGoogle Scholar
• O’Regan, E. (2018). Thousands are told in A&E they have cancer - Independent.ie. Irish Independent. https://www.independent.ie/irish-news/health/thousands-are-told-in-ae-they-have-cancer-37580540.html
   Google Scholar
• Ormerod, R. J. (2014). The mangle of or practice: Towards more informative case studies of ‘technical’ projects. The Journal of the Operational Research Society, 65(8), 1245–1260. https://doi.org/10.1057/jors.2013.78
   Web of Science ®Google Scholar
• Orsi, M. A., Oliva, A. G., & Cellina, M. (2020). Radiology department preparedness for COVID-19: Facing an unexpected outbreak of the disease. Radiology, 295(3), 201214. https://doi.org/10.1148/radiol.2020201214
   PubMed Web of Science ®Google Scholar
• Pearson, M., Monks, T., Gibson, A., Allen, M., Komashie, A., Fordyce, A., Harris-Golesworthy, F., Pitt, M. A., Brailsford, S., & Stein, K. (2013). Involving patients and the public in healthcare operational research—the challenges and opportunities. Operations Research for Health Care, 2(4), 86–89. https://doi.org/10.1016/j.orhc.2013.09.001
   Google Scholar
• Pessôa, L. A. M., Lins, M. P. E., Da Silva, A. C. M., & Fiszman, R. (2015). Integrating soft and hard operational research to improve surgical centre management at a university hospital. European Journal of Operational Research, 245(3), 851–861. https://doi.org/10.1016/j.ejor.2015.04.007
   Web of Science ®Google Scholar
• Pickering, A. (1995). The mangle of practice : Time, agency, and science. University of Chicago Press.
   Google Scholar
• Pidd, M. (2010). Why modelling and model use matter. Source: The Journal of the Operational Research Society, 61(1), 14–24. https://doi.org/10.1057/jors.2009.141
   Web of Science ®Google Scholar
• Pitman, A. G., Jones, D. N., Seymour, J. F., Pitman, A. G., Stark, R. J., & Prince, H. M. (2004). Radiologist workloads in teaching hospital departments: Measuring the workload. American Journal of Hematology, 77(1), 72–76. https://doi.org/10.1111/j.1440-1673.2005.01524.x
   PubMedGoogle Scholar
• Rachuba, S., Knapp, K., Ashton, L., & Pitt, M. (2018). Streamlining pathways for minor injuries in emergency departments through radiographer-led discharge. Operations Research for Health Care, 19, 44–56. https://doi.org/10.1016/j.orhc.2018.03.001
   Web of Science ®Google Scholar
• Rashwan, W. (2017). An Integrated Framework for Staffing and Shift Scheduling in Hospitals (Issue November) [Dublin Institute technology]. https://arrow.dit.ie/busdoc/25/
   Google Scholar
• Reinus, W. R., Enyan, A., Flanagan, P., Pim, B., Sallee, D. S., & Segrist, J. (2000). A proposed scheduling model to improve use of computed tomography facilities. Journal of Medical Systems, 24(2), 61–76. https://doi.org/10.1023/A:1005512729184
   PubMedGoogle Scholar
• Robinson, A. S., & Robinson, S. (2001). Soft with a Hard Centre : Discrete-Event Simulation in Facilitation Published by : Palgrave Macmillan Journals on behalf of the Operational Research Society Linked references are available on JSTOR for this article : Soft with a hard centre : Discrete-eve. The Journal of the Operational Research Society, 52(8), 905–915. https://doi.org/10.1057/palgrave.jors.2601158
   Web of Science ®Google Scholar
• Robinson, S., Worthington, C., Burgess, N., & Radnor, Z. J. (2014). Facilitated modelling with discrete-event simulation: Reality or myth? European Journal of Operational Research, 234(1), 231–240. https://doi.org/10.1016/j.ejor.2012.12.024
   Web of Science ®Google Scholar
• Rodriguez-Ulloa, R., & Paucar-Caceres, A. (2005). Soft System Dynamics Methodology (SSDM): Combining Soft Systems Methodology (SSM) and System Dynamics (SD). Systemic Practice and Action Research, 18(3), 303–334. https://doi.org/10.1007/s11213-005-4816-7
   Web of Science ®Google Scholar
• Ross, S., Lavis, J., Rodriguez, C., Woodside, J., & Denis, J. L. (2003). Partnership experiences: Involving decision-makers in the research process. Journal of Health Services Research and Policy, 8(SUPPL. 2), 26–34. https://doi.org/10.1258/135581903322405144
   PubMedGoogle Scholar
• The Royal College of Radiologists. (2020). Clinical Radiology UK Workforce Census 2019 Report. Clinical Radiology, April. http://www.rcr.ac.uk/publications.aspx?PageID=310&PublicationID=359
   Google Scholar
• Sinclair, S., Norris, J. M., McConnell, S. J., Chochinov, H. M., Hack, T. F., Hagen, N. A., McClement, S., & Bouchal, S. R. (2016). Compassion: A scoping review of the healthcare literature. BMC palliative care, 15(1), 6. https://doi.org/10.1186/s12904-016-0080-0
   PubMedGoogle Scholar
• Snaith, B., Milner, R. C., & Harris, M. A. (2016). Beyond image interpretation: Capturing the impact of radiographer advanced practice through activity diaries. Radiography, 22(4), e233–238. https://doi.org/10.1016/j.radi.2016.07.005
   Web of Science ®Google Scholar
• Sunshine, J. H., & Burkhardt, J. H. (2000). Radiology groups’ workload in relative value units and factors affecting it. Radiology, 214(3), 815–822. https://doi.org/10.1148/radiology.214.3.r00mr50815
   PubMed Web of Science ®Google Scholar
• Tako, A. A., & Kotiadis, K. (2015). PartiSim: A multi-methodology framework to support facilitated simulation modelling in healthcare. European Journal of Operational Research, 244(2), 555–564. https://doi.org/10.1016/j.ejor.2015.01.046
   Web of Science ®Google Scholar
• Taylor, K., & Dangerfield, B. (2005). Modelling the feedback effects of reconfiguring health services. The Journal of the Operational Research Society, 56(6), 659–675. https://doi.org/10.1057/palgrave.jors.2601862
   Web of Science ®Google Scholar
• Tyler, J. M., Murch, B. J., Vasilakis, C., & Wood, R. M. (2022). Improving uptake of simulation in healthcare: User-driven development of an open-source tool for modelling patient flow. Journal of Simulation, 1–18. https://doi.org/10.1080/17477778.2022.2081521
   Google Scholar
• Zanardo, M., Martini, C., Monti, C. B., Cattaneo, F., Ciaralli, C., Cornacchione, P., & Durante, S. (2020). Management of patients with suspected or confirmed COVID-19, in the radiology department. Radiography, 26(3), 264–268. https://doi.org/10.1016/j.radi.2020.04.010
   PubMed Web of Science ®Google Scholar