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• W2334199191 abstract "Hypothesis Over the past decade the number, variety and cost of available simulators have risen dramatically. Decisions associated with simulator selection can be challenging, particularly when multiple stakeholders are involved in the acquisition process. Consensus can be even more elusive when definitions of value diverge, and/or priorities are misaligned across the stakeholders involved. Currently, there is no reliable, standardized mechanism to support technicians, faculty, administrators, and leadership during the simulator evaluation and procurement process. We propose a tool founded on scientific evidence could be used to facilitate the simulator evaluation and purchase process. Methods Using a Delphi method that included 2 rounds of surveys and 2 focus groups, we collected data from members from SSIH (n=88) and ACS AEI (n=69) societies. The survey consisted of 31 factors organized across six domains. Participants rated each on a 4-point rating scale, ranging from 1(Not considered/not important to me when I consider a simulator purchase) to 4 (Critical to me when I consider a simulator purchase). Demographics were also captured. Societies’ rankings were compared using Wilcoxon signed rank test. Rating differences across professional society, institution type, and participants’ self-reported stakeholder role were evaluated using a Rasch model. Inter-item reliabilities were estimated using Cronbach alpha. Results Participant demographics are reviewed in detail. The top 17 factors were identified and ranked, with top two as Technical stability/reliability of simulator and Customer service. Top 17 factors were incorporated into an Excel® spreadsheet. The majority of Round 2 focus group participants 27 (87.1%) agreed that the resulting SVI Worksheet adequately represented all critical factors considered during a simulator purchase. Conclusion The product from this work (SVI Worksheet tool) can be applied aid the simulator purchase process across countries, institutions, and stakeholder. We are hopeful that simulator purchase processes might include the SVI Worksheet with the intention to maintain alignment with educational goals, while still accounting for other factors considered at the institutional level. At the same time, common measures might facilitate future communication across academic medical institutions and simulator industry. More evaluation is required following broad-scaled implementation. References 1. Britt RC, Novosel TJ, Britt LD, Sullivan M (2009). The impact of central line simulation before the ICU experience. Am J Surg Apr;197(4):533-6. Epub 2009 Feb 27. 2. Dayan AB, Ziv A, Berkenstadt H, Munz Y (2008). A simple, low-cost platform for basic laparoscopic skills training. Surg Innov Jun;15(2):136–42. 3. Conroy S (2010). Competence and retention in performance of the lumbar puncture procedure in a task trainer model. Simul Healthc;5: 133–138. 4. Parent RJ, Plerhoples TA, Long EE, etal (2010). Early, intermediate, and late effects of a surgical skills “boot camp” on an objective structured assessment of technical skills: a randomized controlled study. J Am Coll Surg; 210(6):984–9. 5. Lim WS, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax, 58(5):377-82, 2003 May. 6. Gage BF, et al. Validation of Clinical Classifications Schemes for Predicting Stroke, Results From the National Registry of Atrial Fibrillation. JAMA, 285(22):2864-70, June 2001. 7. Dalkey N, Helme O (1963). An experimental application of the Delphi method to the use ofexperts. Management Science 1963; 9(3): 458–467. 8. Brown B (1968). Delphi Process: A Methodology Used for the Elicitation of Opinions of Experts.“ : An earlier paper published by RAND (Document No: P-3925, 1968, 15 pages). 9. Rasch G (1960/1980). Probabilistic models for some intelligence and attainment tests.(Copenhagen, Danish Institute for Educational Research), expanded edition (1980) with foreword and afterword by B.D. Wright. Chicago: The University of Chicago Press. 10. Andrich D (1988). Rasch models for measurement. Beverly Hills: Sage Publications. Disclosures None" @default.
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• W2334199191 date "2014-12-01" @default.
• W2334199191 modified "2023-09-26" @default.
• W2334199191 title "Board #153 - Research Abstract The Creation of a Simulator Value Index Tool by Connected Consensus (Submission #8590)" @default.
• W2334199191 doi "https://doi.org/10.1097/01.sih.0000459322.91351.95" @default.
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