Abstract
Many facets of an image acquisition workflow leave a digital footprint, making workflow analysis amenable to an informatics-based solution. This paper describes a detailed framework for analyzing workflow and uses acute stroke response timeliness in CT as a practical demonstration. We review methods for accessing the digital footprints resulting from common technologist/device interactions. This overview lays a foundation for obtaining data for workflow analysis. We demonstrate the method by analyzing CT imaging efficiency in the setting of acute stroke. We successfully used digital footprints of CT technologists to analyze their workflow. We presented an overview of other digital footprints including but not limited to contrast administration, patient positioning, billing, reformat creation, and scheduling. A framework for analyzing image acquisition workflow was presented. This framework is transferable to any modality, as the key steps of image acquisition, image reconstruction, image post processing, and image transfer to PACS are common to any imaging modality in diagnostic radiology.
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Boland GW: Enhancing CT productivity: strategies for increasing capacity. American Journal of Roentgenology 191(1):3–10, 2008
Gunn ML, Maki JH, Hall C, Bhargava P, Andre JB, Carnell J, ... Beauchamp NJ: Improving MRI scanner utilization using modality log files. J Am Coll Radiol 14(6):783–786, 2017.
Flug J, Nagy P: The lean concept of waste in radiology. Journal of the American College of Radiology 8(6):443–445, 2011
Hirschorn DS, Hinrichs CR, Gor DM, Shah K, Visvikis G: Impact of a diagnostic workstation on workflow in the emergency department at a level I trauma center. Journal of digital imaging 14:199–201, 2001
Reiner BI, Siegel EL, Hooper FJ, Pomerantz S, Dahlke A, Rallis D: Radiologists’ productivity in the interpretation of CT scans: a comparison of PACS with conventional film. American Journal of Roentgenology 176(4):861–864, 2001
Reiner BI, Siegel EL, Hooper FJ, Glasser D: Effect of film-based versus filmless operation on the productivity of CT technologists. Radiology 207(2):481–485, 1998
Kato H, Kubota G, Kojima K, Hayashi N, Nishihara E, Kura H, Aizawa M: Preliminary time-flow study: comparison of interpretation times between PACS workstations and films. Computerized medical imaging and graphics 19(3):261–265, 1995
Redfern RO, Horii SC, Feingold E, Kundel HL: Radiology workflow and patient volume: effect of picture archiving and communication systems on technologists and radiologists. Journal of Digital Imaging 13:97–100, 2000
Siegel E, Reiner B: Work flow redesign: the key to success when using PACS. American Journal of Roentgenology 178(3):563–566, 2002
Reiner B, Siegel E, Scanlon M: Changes in technologist productivity with implementation of an enterprisewide PACS. Journal of digital imaging 15(1):22–26, 2002
Reiner BI, Siegel EL: Technologists’ productivity when using PACS: comparison of film-based versus filmless radiography. American Journal of Roentgenology 179(1):33–37, 2002
Siegel EL, Reiner BI, Siddiqui KM: Ten filmless years and ten lessons: a 10th-anniversary retrospective from the Baltimore VA Medical Center. Journal of the American College of Radiology 1(11):824–833, 2004
Lepanto L, Paré G, Aubry D, Robillard P, Lesage J: Impact of PACS on dictation turnaround time and productivity. Journal of digital imaging 19(1):92, 2006
Wideman C, Gallet J: Analog to digital workflow improvement: a quantitative study. Journal of Digital Imaging 19(1):29–34, 2006
Humphrey LM, Fitzpatrick K, Atallah N et al.: Time comparison of intensive care units with and without digital viewing systems. J Digit Imaging 6:37–41, 1993
Schemmel A, Lee M, Hanley T, Pooler BD, Kennedy T., Field, A., ... John-Paul JY. Radiology workflow disruptors: a detailed analysis. J Am Coll Radiol 13(10):1210–1214, 2016.
Dhanoa D, Dhesi TS, Burton KR, Nicolaou S, Liang T: The evolving role of the radiologist: the Vancouver workload utilization evaluation study. Journal of the American College of Radiology 10(10):764–769, 2013
John-Paul JY, Kansagra AP, Mongan J: The radiologist's workflow environment: evaluation of disruptors and potential implications. Journal of the American College of Radiology 11(6):589–593, 2014
Gay SB, Sobel AH, Young LQ, Dwyer SJ: Processes involved in reading imaging studies: workflow analysis and implications for workstation development. Journal of digital imaging 10(1):40–45, 1997
Beard D: Designing a radiology workstation: a focus on navigation during the interpretation task. Journal of Digital Imaging 3(3):152–163, 1990
TJC. Specifications Manual for Joint Commission National Quality Measures, Version 2017A. 2017. https://manual.jointcommission.org/releases/TJC2017A/rsrc56/Manual/TableOfContentsTJC/TJC_v2017A.pdf
Saver JL: Time is brain—quantified. Stroke 37(1):263–266, 2007
Reiner B, Siegel E, Carrino JA: Workflow optimization: current trends and future directions. Journal of Digital Imaging 15(3):141–152, 2002
Branstetter, IV BF: Basics of imaging informatics: Part. Radiology 243(3):656–667, 2007
Branstetter, IV BF: Basics of imaging informatics: Part 2. Radiology 244(1):78–84, 2007
Cook TS, Zimmerman SL, Steingall SR, Maidment AD, Kim W, Boonn WW: Informatics in radiology: RADIANCE: an automated, enterprise-wide solution for archiving and reporting CT radiation dose estimates. Radiographics 31(7):1833–1846, 2011
Gress DA, Dickinson RL, Erwin WD, Jordan DW, Kobistek RJ, Stevens DM, ...: Fairobent LA. AAPM medical physics practice guideline 6. a.: Performance characteristics of radiation dose index monitoring systems. J Appl Clin Med Phys. 2017
Grimes J, Leng S, Zhang Y, Vrieze T, McCollough C: Implementation and evaluation of a protocol management system for automated review of CT protocols. Journal of applied clinical medical physics 17(5):1–11, 2016
Langer SG: A flexible database architecture for mining DICOM objects: the DICOM data warehouse. Journal of digital imaging 25(2):206–212, 2012
Langer SG: DICOM data warehouse: Part 2. Journal of digital imaging 29(3):309–313, 2016
US Department of Health and Human Services. Security standards: General rules, 46 CFR section 164.308(a)-(c)
US Department of Health and Human Services. Technical safeguards. 45 CFR section 164–312 (b)
Integrating the Healthcare Enterprise Profile. “Management of Acquisition Protocols (MAP)” Published 2017–07-14 Downloaded on 8/25/2017 from http://ihe.net/Technical_Frameworks/#radiology
Digital Imaging and Communications in Medicine (DICOM). “Supplement 121: CT Procedure Plan and Protocol Storage SOP Class” Downloaded on 8/25/2017 from http://dicom.nema.org/Dicom/News/oct2013/docs_oct2013/sup121_pc.pdf
Szczykutowicz TP, Siegelman J: On the same page—physicist and radiologist perspectives on protocol management and review. Journal of the American College of Radiology 12(8):808–814, 2015
Szczykutowicz TP, Malkus A, Ciano A, Pozniak M: Tracking patterns of nonadherence to prescribed CT protocol parameters. Journal of the American College of Radiology 14(2):224–230, 2017
Szczykutowicz TP, Rubert N, Belden D, Ciano A, Duplissis A, Hermanns A, Monette S, JanssenSaldivar E: A wiki based solution to managing your institutions imaging protocols. J Am Coll Radiol. 2016
Szczykutowicz TP, Rubert N, Belden D, Ciano A, Duplissis A, Hermanns A, Monette S, JanssenSaldivar E: A wiki based CT protocol management system. Radiol Manage. 2015
Boland GW, Houghton MP, Marchione DG, McCormick W: Maximizing outpatient computed tomography productivity using multiple technologists. Journal of the American College of Radiology 5(2):119–125, 2008
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This work was supported by a research grant from GE Healthcare.
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All authors are involved in a collaborative project that supplies CT protocols to GE Healthcare. TPS is also a GE consultant and the founder of protocolshare.org. RB is co-founder and officer of ImageMoverMD, and GW is on the MAB of McKesson and HealthMyne, a stockholder in HealthMyne, and co-founder of WITS(MD). AF receives research support from GE Healthcare. WP is a stockholder in GE Healthcare.
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Szczykutowicz, T.P., Brunnquell, C.L., Avey, G.D. et al. A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging. J Digit Imaging 31, 201–209 (2018). https://doi.org/10.1007/s10278-018-0055-1
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DOI: https://doi.org/10.1007/s10278-018-0055-1