Abstract
Following the step-by-step presentation of radiology department operations presented in this book, this chapter discusses some of the basic tools of operations analysis including queuing theory, process mining, artificial intelligence, and machine learning. It concludes with a discussion of our fundamental beliefs—that efficiency can improve quality, and that operations analysis can enhance but not replace managerial oversight. Data does not drive change. People drive change.
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References
Wikipedia. Little’s Law. [Online]. https://en.wikipedia.org/wiki/Little%27s_law.
Wikipedia. Pollaczek–Khinchine formula. [Online]. https://en.wikipedia.org/wiki/Pollaczek-Khinchine_formula.
Pianykh OS, Rosenthal DI. Can we predict patient wait time? J Am Coll Radiol. 2015;12(10):1058–66.
Flexicon. Disco. [Online]. https://fluxicon.com/disco/.
ProM. ProM. [Online]. http://www.promtools.org/doku.php.
Ludwig M, Van Merode F, Groot W. Principal agent relationships and the efficiency of hospitals. Eur J Health Econ. 2010;11(3):291–304.
Reiner B. New strategies for medical data mining, part 2: the customizable productivity pacer. J Am Coll Radiol. 2011;8(1):33–8.
Acknowledgements
This book would not have come about without the support and interest of many of our colleagues. It would be impossible to name them all here. But we would like to thank the Radiology Department of Massachusetts General Hospital and its Medical Analytics Group for providing us with opportunities to investigate, solve, and implement. We would also like to thank the many leaders and managers of our department for their willingness to try new ways of doing things. We would also like to thank our current and past chairmen, Dr. James A. Brink and Dr. James H. Thrall for their support, insights, and encouragement.
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Rosenthal, D., Pianykh, O. (2021). Ars Longa, Vita Brevis. In: Efficient Radiology. Springer, Cham. https://doi.org/10.1007/978-3-030-53610-7_10
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DOI: https://doi.org/10.1007/978-3-030-53610-7_10
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