Tracking Patterns of Nonadherence to Prescribed CT Protocol Parameters

Szczykutowicz, Timothy P.; Malkus, Annelise; Ciano, Amanda; Pozniak, Myron A.

doi:10.1016/j.jacr.2016.08.029

Cited by 8 publications

(6 citation statements)

References 27 publications

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“…This represents another digital footprint not previously discussed in the current work. Monitoring technologist use of protocol management systems could identify technologists who need more training or correlated with instances of technologist non-compliance with imaging protocols [35,36]. Protocol management systems are available from some vendors and institution specific solutions exist [37,38].…”

Section: Resultsmentioning

confidence: 99%

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

et al. 2018

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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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Section: Resultsmentioning

confidence: 99%

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

et al. 2018

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“…Our algorithm expedites these processes by decoupling the protocol file to wiki format conversion, as the MS Excel files can be embedded on a wiki system or stored or shared in an online workspace. In addition, our approach may also be deployed to automatically flag protocol deviations, which is a critical yet time‐consuming task during CT protocol review when done manually, through side‐by‐side protocol visualization and comparison 38 …”

Section: Discussionmentioning

confidence: 99%

Protocol parameter extraction and centralization framework for comprehensive and in‐depth CT protocol review and management

LaBella,

Zhang

2024

J Applied Clin Med Phys

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CT protocol management is an arduous task that requires expertise from a variety of radiology professionals, including technologists, radiologists, radiology IT professionals, and medical physicists. Each CT vendor has unique, proprietary protocol file structures, some of which may vary by scanner model, making it difficult to develop a universal framework for distilling technical parameters to a human‐readable file format. An ideal solution for CT protocol management is to minimize the work required for parameter extraction by introducing a data format into the workflow that is universal to all CT scanners.In this paper, we report a framework for CT protocol management that converts raw protocol files to an intermediary format before outputting them in a human‐readable format for a variety of practical clinical applications, including routine protocol review, protocol version tracking, and cross‐protocol comparisons.The framework was developed in Python 3. Technical parameters of interest were determined via collaborative effort between medical physicists and lead technologists. Protocol files were extracted and analyzed from a variety of scanners across our hospital‐wide CT fleet, including various systems from Siemens and GE. Protocols were subcategorized based on relevant technical parameters into regular, dual‐energy, and cardiac CT protocols. Backend code for technical parameter extraction from raw protocol files to a JavaScript Object Notation (JSON) format was performed on a per‐system basis. Conversion from JSON to a readable output format (MS Excel) was performed identically for all scanners using the universal framework developed and presented in this work. Example results for Siemens and GE scanners are shown, including side‐by‐side comparisons for protocols with similar clinical indications.In conclusion, our CT protocol management framework may be deployed on any CT system to improve clinical efficiency in protocol review and upkeep.

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“…Extensive work has been performed at institution 1 to develop optimized, indication-specific CT protocols [27][28][29]37,38], and these protocols are used by all institutions participating in this study. This effort simplifies the at-thescanner workflow for technologists.…”

Section: Discussionmentioning

confidence: 99%

“…All institutions were provided CTPA protocols developed at institution 1 [27,28], albeit compliance with the intended execution of the protocols varied [29]. Small, medium, and large adult CTPA protocols correspond to anteriorposterior plus lateral widths of <60 cm, 60 to 80 cm, and >80 cm, respectively.…”

Section: Ctpa Protocolsmentioning

confidence: 99%

Applying a New CT Quality Metric in Radiology: How CT Pulmonary Angiography Repeat Rates Compare Across Institutions

Rose

Viggiano

Bour

et al. 2021

Journal of the American College of Radiology

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Tracking Patterns of Nonadherence to Prescribed CT Protocol Parameters

Cited by 8 publications

References 27 publications

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

A General Framework for Monitoring Image Acquisition Workflow in the Radiology Environment: Timeliness for Acute Stroke CT Imaging

Protocol parameter extraction and centralization framework for comprehensive and in‐depth CT protocol review and management

Applying a New CT Quality Metric in Radiology: How CT Pulmonary Angiography Repeat Rates Compare Across Institutions

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