Telemedicine-based system for quality management and peer review in radiology

Morozov, S. P.; Guseva, Ekaterina; Ледихова, Н. В.; Vladzymyrskyy, A.V.; Safronov, D. I.

doi:10.1007/s13244-018-0629-y

Cited by 25 publications

(10 citation statements)

References 15 publications

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“…Increased burnout and high risk of occupational death among healthcare workers call for automation of the reading process, which will improve productivity and minimize errors [8]. Preliminary figures indicate the AI algorithms have sufficient accuracy for the diagnostic evaluation of COVID-19 (responsiveness – 90%, specificity – 96%, AUC – 0.96, overall accuracy 76.37-98.26) [6, 9…”

Section: Introductionmentioning

confidence: 99%

MosMedData: Chest CT Scans with COVID-19 Related Findings Dataset

Morozov¹,

Andreychenko²,

Pavlov³

et al. 2020

Preprint

173

123

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This dataset contains anonymised human lung computed tomography (CT) scans with COVID-19 related findings, as well as without such findings. A small subset of studies has been annotated with binary pixel masks depicting regions of interests (ground-glass opacifications and consolidations). CT scans were obtained between 1st of March, 2020 and 25th of April, 2020, and provided by municipal hospitals in Moscow, Russia. Permanent link: https://mosmed.ai/datasets/covid19_1110. This dataset is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License.

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Section: Introductionmentioning

confidence: 99%

MosMedData: Chest CT Scans with COVID-19 Related Findings Dataset

Morozov¹,

Andreychenko²,

Pavlov³

et al. 2020

Preprint

173

123

View full text Add to dashboard Cite

show abstract

“…Differences in measuring disagreement rates arise when attempting to compare the results of the literature; double-reporting, anonymous peer-review, and retrospective versus prospective secondary image interpretation influence the outcome of disagreement studies [ 26 ]. Nevertheless, the current literature supports the idea that peer-review should be part of self-critical radiology and QA [ 23 , 30 , 46 ]. Again, economic concerns play an important role—what is the economic optimum of quality?…”

Section: Discussionmentioning

confidence: 96%

Quality Assurance of a Cross-Border and Sub-Specialized Teleradiology Service

Hetenyi¹,

Goelz

Boehmcker³

et al. 2022

Healthcare

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Background: The current literature discusses aspects of quality assurance (QA) and sub-specialization. However, the challenges of these topics in a teleradiology network have been less explored. In a project report, we aimed to review the development and enforcement of sub-specialized radiology at Telemedicine Clinic (TMC), one of the largest teleradiology providers in Europe, and to describe each step of its QA. Evaluation: The company-specific background was provided by the co-authors—current and former staff members of TMC. Detailed descriptions of the structures of sub-specialization and QA at TMC are provided. Exemplary quantitative evaluation of caseloads and disagreement rates of secondary reviews are illustrated. Description of Sub-specialization and Quality Assurance at TMC: Sub-specialization at TMC is divided into musculoskeletal radiology, neuroradiology, head and neck, a body, and an emergency section operating at local daytime in Europe and Australia. Quality assurance is based on a strict selection process of radiologists, specific reporting guidelines, feedback through the secondary reading of 100% of all radiology reports for new starters, and a minimum of 5% of radiology reports on a continuous basis for all other radiologists, knowledge sharing activities and ongoing training. The level of sub-specialization of each radiologist is monitored continuously on an individual basis in detail. After prospective secondary readings, the mean disagreement rate at TMC indicating at least possibly clinically relevant findings was 4% in 2021. Conclusion: With continuing and current developments in radiology in mind, the essential features of sub-specialization and innovative QA are relevant for further expansion of teleradiology services and for most radiology departments worldwide to respond to the increasing demand for value-based radiology.

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“…Whether initial expectations have been met needs to be considered before roll-out of any technological innovation [ 19 ]. Therefore, our several iterative steps (Phases 2 to 5) are incremental and in line with the PDCA cycle [ 75 ] as well as the established key elements of integrated care [ 76 ]. The idea of conceptualising product development levels and evaluating the maturity of the product accordingly is the focus of the established technology readiness assessment [ 77 ], as well as an essential part of Roger’s Diffusion of Innovations theory [ 78 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluation is Key: Providing Appropriate Evaluation Measures for Participatory and User-Centred Design Processes of Healthcare IT

Harst

Wollschlaeger

Birnstein

et al. 2021

International Journal of Integrated Care

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Introduction:The increasing availability of healthcare IT has the potential to improve the integration of health services. Existing projects developing healthcare IT mostly disregard the potential and importance of incorporating user feedback and proper evaluation measures to gain user feedback throughout the development process. We therefore provide methodological guidance for evaluation in a stepwise user-centred design process.Methods: Based on a literature review we propose adequate methods for data collection in each phase of participatory and user-centred healthcare IT development. In order to provide an orientation within the plethora of development processes used in practice, we consolidate a generic blueprint process from the literature review. The applicability of our methodological guidance is shown in three diverse use cases from the field of integrated care.Results: From 14 literature items, we identified common evaluation methods including, among others, interviews, focus groups, and surveys. These methods can be associated to six typical development phases that could be derived from research: State of the Art Research, Requirement Analysis, Conceptual Prototype, Preliminary Prototype, Full Prototype, Full Application. The use cases demonstrate the value of qualitative methods and mixed methods designs. Discussion: Our methodological guidance has proven applicable for designing healthcare IT solutions from scratch -both for patient and professional settings -and to develop a platform for combining existing component-based solutions. In integrated care settings, where a wide range of stakeholders with multiple needs exist, we thus provide methodological guidance on how to involve users in the development process. Conclusion:Our stepwise methodological guidance helps to design and properly evaluate healthcare IT solutions, which meet the user needs and requirements, for integrated care settings.

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Telemedicine-based system for quality management and peer review in radiology

Cited by 25 publications

References 15 publications

MosMedData: Chest CT Scans with COVID-19 Related Findings Dataset

MosMedData: Chest CT Scans with COVID-19 Related Findings Dataset

Quality Assurance of a Cross-Border and Sub-Specialized Teleradiology Service

Evaluation is Key: Providing Appropriate Evaluation Measures for Participatory and User-Centred Design Processes of Healthcare IT

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