PURPOSE: For a number of different treatment types [such as Total Body Irradiation (TBI), etc.] most institutions utilize tables from commissioned databooks to perform the dose calculations. Each time one manually looks up data from a large table and then copies the numbers for a manual calculation, there is potential for errors. While a second check effectively mitigates the potential error from such calculations, information regarding the frequency and nature of such mistakes is important to develop protocols and workflows that avoid related errors. METHODS: Five years' worth of TBI calculations were reviewed. Each calculation was re-performed and evaluated against the original calculation and original second check. Any discrepancies were noted and those discrepancies were checked to see if the number was the result of misreading from the look-up table, a typo, copying/skipping partially redundant steps, or rounding/avoiding interpolation. The number of calculations that contained these various types of discrepancies was tallied and percentages representing the frequency of said discrepancies were derived. RESULTS: All of the discrepancies only resulted in a monitor unit (MU) calculation difference of <1.7%. Typos, looking up wrong values from tables, rounding/avoiding interpolation, and skipping steps occurred in 10.4% ( ± 3.1%), 6.3% ( ± 2.5%), 53.1% ( ± 5.1%), and 4.2% ( ± 2.0%) of MU calculations, respectively. CONCLUSIONS: While all of the discrepancies only resulted in a monitor unit (MU) calculation difference of <1.7%, this review shows how frequently various discrepancies can occur. Typos and rounding/avoiding interpolation are the steps most likely to potentially cause a miscalculation of MU. To avoid direct human interaction on such a large repetitive scale, creating forms that calculate MU automatically from initial measurement data would reduce the incidences that numbers are written/transcribed and eliminate the need to look up data in a table, thus reducing the chance for error.
PURPOSE: For a number of different treatment types [such as Total Body Irradiation (TBI), etc.] most institutions utilize tables from commissioned databooks to perform the dose calculations. Each time one manually looks up data from a large table and then copies the numbers for a manual calculation, there is potential for errors. While a second check effectively mitigates the potential error from such calculations, information regarding the frequency and nature of such mistakes is important to develop protocols and workflows that avoid related errors. METHODS: Five years' worth of TBI calculations were reviewed. Each calculation was re-performed and evaluated against the original calculation and original second check. Any discrepancies were noted and those discrepancies were checked to see if the number was the result of misreading from the look-up table, a typo, copying/skipping partially redundant steps, or rounding/avoiding interpolation. The number of calculations that contained these various types of discrepancies was tallied and percentages representing the frequency of said discrepancies were derived. RESULTS: All of the discrepancies only resulted in a monitor unit (MU) calculation difference of <1.7%. Typos, looking up wrong values from tables, rounding/avoiding interpolation, and skipping steps occurred in 10.4% ( ± 3.1%), 6.3% ( ± 2.5%), 53.1% ( ± 5.1%), and 4.2% ( ± 2.0%) of MU calculations, respectively. CONCLUSIONS: While all of the discrepancies only resulted in a monitor unit (MU) calculation difference of <1.7%, this review shows how frequently various discrepancies can occur. Typos and rounding/avoiding interpolation are the steps most likely to potentially cause a miscalculation of MU. To avoid direct human interaction on such a large repetitive scale, creating forms that calculate MU automatically from initial measurement data would reduce the incidences that numbers are written/transcribed and eliminate the need to look up data in a table, thus reducing the chance for error.
Authors: Julian R Perks; Sinisa Stanic; Robin L Stern; Barbara Henk; Marsha S Nelson; Rick D Harse; Mathew Mathai; James A Purdy; Richard K Valicenti; Allan D Siefkin; Allen M Chen Journal: Int J Radiat Oncol Biol Phys Date: 2011-12-22 Impact factor: 7.038
Authors: M Saiful Huq; Benedick A Fraass; Peter B Dunscombe; John P Gibbons; Geoffrey S Ibbott; Arno J Mundt; Sasa Mutic; Jatinder R Palta; Frank Rath; Bruce R Thomadsen; Jeffrey F Williamson; Ellen D Yorke Journal: Med Phys Date: 2016-07 Impact factor: 4.071
Authors: Eric C Ford; Ray Gaudette; Lee Myers; Bruce Vanderver; Lilly Engineer; Richard Zellars; Danny Y Song; John Wong; Theodore L Deweese Journal: Int J Radiat Oncol Biol Phys Date: 2009-05-04 Impact factor: 7.038
Authors: Raffaele La Russa; Valentina Fazio; Michela Ferrara; Nicola Di Fazio; Rocco Valerio Viola; Gianluca Piras; Giuseppe Ciano; Fausta Micheletta; Paola Frati Journal: Front Public Health Date: 2022-03-24