The Role of Radiology in the Diagnostic Process: Information, Communication, and Teamwork

Patient Communication Innovations in Breast Imaging

Effective patient communication is paramount in breast radiology, where standardized reporting and patient-centered care practices have long been established. This communication profoundly affects patient experience, well-being, and adherence to medical advice. Breast radiologists play a pivotal role in conveying diagnostic findings and addressing patient concerns, particularly in the context of cancer diagnoses. Technological advances in radiology reporting, patient access to electronic medical records, and the demand for immediate information access have reshaped radiologists' communication practices. Innovative approaches, including image-rich reports, visual timelines, and video radiology reports, have been used in various institutions to enhance patient comprehension and engagement.

Night and Day, Why Radiologists Need Play

What is play and why does it matter for radiologists? Play can take many forms in the workplace, including organic, managed, task-related, diversionary, and resistive forms of play, and play may also take the form of authentic self-expression and creation. In this review article, we will discuss the benefits of play including improved problem solving, gaining perspective, and stress reduction, and also provide low-tech and high-tech examples of beneficial play for the radiology team in work and personal contexts.

Factors influencing teamwork in healthcare applicable to interventional and diagnostic radiology

Teamwork in healthcare has been analysed extensively in the literature, mainly in acute healthcare settings such as the operating room, emergency room, and intensive care unit, with limited evidence related to diagnostic and interventional radiology. Multiple factors that affect teamwork in different domains have been described, such as communication, hierarchy, and distractions. Teamwork is an important patient safety, job satisfaction and patient outcome determinant, with interprofessional and interdisciplinary healthcare education playing a relevant role in the different domains affecting team performance. The aim of this article is to review the literature to describe domains and specific factors that influence teamwork in diagnostic and interventional radiology practice. This is of particular interest for radiologist involved in quality improvement and/or patient safety initiatives development and implementation. The review will conclude with a summary table highlighting the most important factors that, according to the authors, appear relevant to the radiology practice.

Health Systems Science - A Primer for Radiologists

Health systems science (HSS) is an educational framework designed to promote improved care through enhanced citizenship and the training of systems-fluent individuals trained in the science of health care delivery.  HSS education in residency builds upon foundations established during medical school, emphasizing practical skills development, and fostering a growth mindset among trainees.  The HSS framework organizes elements of system-based practice for radiology trainees, promoting practice-readiness for providing safe, timely, effective, efficient, equitable and patient centered radiological care. This paper serves as a primer for radiologists to understand and apply the HSS framework. Additionally, we highlight radiology-specific curricular elements aligned with the HSS framework, and provide teaching resources both for classroom education and for resident self-study.

The ACR Learning Network: Facilitating Local Performance Improvement Through Shared Learning

PURPOSE

The ACR Learning Network was established to test the viability of the learning network model in radiology. In this report, the authors review the learning network concept, introduce the ACR Learning Network and its components, and report progress to date and plans for the future.

METHODS

Patterned after institutional programs developed by the principal investigator, the ACR Learning Network was composed of four distinct improvement collaboratives. Initial participating sites were solicited through broad program advertisement. Candidate programs were selected on the basis of assessments of local leadership support, experience with quality improvement initiatives, intraorganizational relationships, and access to data and analytic support. Participation began with completing a 27-week formal quality improvement training and project support program, with local teams reporting weekly progress on a common performance measure.

RESULTS

Four improvement collaborative topics were chosen for the initial cohort with the following numbers of participating sites: mammography positioning (6), prostate MR image quality (6), lung cancer screening (6), and follow-up on recommendations for management of incidental findings (4). To date, all sites have remained actively engaged and have progressed in an expected fashion. A detailed report of the results of the improvement phase will be provided in a future publication.

CONCLUSIONS

To date, the ACR Learning Network has successfully achieved planned milestones outlined in the program's plan, with preparation under way for the second and third cohorts. By providing a shared platform for improvement training and knowledge sharing, the authors are optimistic that the network may facilitate widespread performance improvement in radiology on a number of topics for years to come.

The performance of the nursing team in outpatient radiology and diagnostic imaging services

OBJECTIVE

To know the performance of nursing professionals in accredited outpatient radiology and diagnostic imaging services.

METHODS

Exploratory, qualitative study, conducted in January 2019, through interview with 21 coordinators in three outpatient imaging services in the Southeast region of Brazil. A textual corpus was formed and processed by a software and the data was analyzed using Reinert's method.

RESULTS

After the organization of the content, two thematic blocks were elaborated: nursing assignments when assisting imaging exams, with three classes with similar content; and nursing and patient safety in radiology, with two classes with similar content.

CONCLUSION

Nursing had a relevant role in quality management, developing actions to mitigate risks and damages, recording and managing adverse events and acting in educational processes, focusing on the quality of care and of images from the perspective of patient safety.

The effect of a relationship-centered communication program on patient experience and provider wellness

OBJECTIVES

Despite evidence of the central importance of communication to patient experience, health outcomes, and provider wellness, communication training for clinicians is not a standard part of clinical education. The study explores the impact of an 8-hour relationship-centered communication (RCC) training program on patient experience and provider wellness.

METHODS

636 healthcare providers participated in 48 workshops conducted January-August 2018. 481 (76%) agreed to participate in research. Participants completed a pre/post assessment that included a wellness survey, the Professional Fulfillment Index (PFI). We conducted chi-squared analyses comparing wellness data immediately prior to the course to 3 months following course participation. Patient experience, assessed using Press Ganey likelihood to recommend care provider (PG-LTR CP) scores, were examined prior to an individual's course participation and following participation up to September 2019.

RESULTS

104 participants completed the three-month PFI (22% response rate). Participants demonstrated marked improvements in professional wellness after 3 months. In bivariate analyses, PG-LTR CP significantly increased and persisted more than 7 months following program completion.

CONCLUSIONS

The RCC training program, a low-cost communication intervention, led to significant, beneficial changes in provider wellness and patient experience.

PRACTICE IMPLICATIONS

Implementing a RCC course for providers may improve patient experience and provider wellness.

Usefulness of Collaborative Work in the Evaluation of Prostate Cancer from MRI

The aim of this study is to show the usefulness of collaborative work in the evaluation of prostate cancer from T2-weighted MRI using a dedicated software tool. The variability of annotations on images of the prostate gland (central and peripheral zones as well as tumour) by two independent experts was firstly evaluated, and secondly compared with a consensus between these two experts. Using a prostate MRI database, experts drew regions of interest (ROIs) corresponding to healthy prostate (peripheral and central zones) and cancer. One of the experts then drew the ROI with knowledge of the other expert’s ROI. The surface area of each ROI was used to measure the Hausdorff distance and the Dice coefficient was measured from the respective contours. They were evaluated between the different experiments, taking the annotations of the second expert as the reference. The results showed that the significant differences between the two experts disappeared with collaborative work. To conclude, this study shows that collaborative work with a dedicated tool allows consensus between expertise in the evaluation of prostate cancer from T2-weighted MRI.

A atuação da equipe de enfermagem em serviços ambulatoriais de radiologia e diagnóstico por imagem

RESUMO Objetivo: Conhecer a atuação da enfermagem nos serviços ambulatoriais de radiologia e diagnóstico por imagem acreditados. Métodos: Estudo exploratório, qualitativo, realizado em janeiro de 2019, através de entrevistas com 21 profissionais coordenadores em três serviços ambulatoriais de imagem na região Sudeste. Formou- se um corpus textual processado por um software e a análise dos dados ocorreu por meio do método de Reinert. Resultados: Foram produzidos dois blocos temáticos a partir da organização do conteúdo: atribuições da enfermagem na assistência aos exames de imagem, onde três classes emergiram de conteúdo similar e o outro bloco, a enfermagem e segurança do paciente na radiologia formados por duas classes que demonstraram temáticas análogas. Conclusão: A enfermagem teve uma atuação relevante na gestão da qualidade, executando ações para mitigação dos riscos, registrando e gerenciando eventos adversos; atuando em processos educativos, focando na qualidade do atendimento e das imagens na perspectiva da segurança do paciente.

Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI

Background Although artificial intelligence (AI) shows promise across many aspects of radiology, the use of AI to create differential diagnoses for rare and common diseases at brain MRI has not been demonstrated. Purpose To evaluate an AI system for generation of differential diagnoses at brain MRI compared with radiologists. Materials and Methods This retrospective study tested performance of an AI system for probabilistic diagnosis in patients with 19 common and rare diagnoses at brain MRI acquired between January 2008 and January 2018. The AI system combines data-driven and domain-expertise methodologies, including deep learning and Bayesian networks. First, lesions were detected by using deep learning. Then, 18 quantitative imaging features were extracted by using atlas-based coregistration and segmentation. Third, these image features were combined with five clinical features by using Bayesian inference to develop probability-ranked differential diagnoses. Quantitative feature extraction algorithms and conditional probabilities were fine-tuned on a training set of 86 patients (mean age, 49 years ± 16 [standard deviation]; 53 women). Accuracy was compared with radiology residents, general radiologists, neuroradiology fellows, and academic neuroradiologists by using accuracy of top one, top two, and top three differential diagnoses in 92 independent test set patients (mean age, 47 years ± 18; 52 women). Results For accuracy of top three differential diagnoses, the AI system (91% correct) performed similarly to academic neuroradiologists (86% correct; P = .20), and better than radiology residents (56%; P < .001), general radiologists (57%; P < .001), and neuroradiology fellows (77%; P = .003). The performance of the AI system was not affected by disease prevalence (93% accuracy for common vs 85% for rare diseases; P = .26). Radiologists were more accurate at diagnosing common versus rare diagnoses (78% vs 47% across all radiologists; P < .001). Conclusion An artificial intelligence system for brain MRI approached overall top one, top two, and top three differential diagnoses accuracy of neuroradiologists and exceeded that of less-specialized radiologists. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Zaharchuk in this issue.