Radiologist and Radiology Practice Wellbeing: A Report of the 2023 ARRS Wellness Summit

In April 2023, the first American Roentgen Ray Society (ARRS) Wellness Summit was held in Honolulu, Hawaii. The Summit was a communal call to action bringing together professionals from the field of radiology to critically review our current state of wellness and reimagine the role of radiology and radiologists to further wellbeing. The in-person and virtual Summit was available free-of-cost to all meeting registrants and included 12 sessions with 44 invited moderators and panelists. The Summit aimed to move beyond simply rehashing the repeated issues and offering theoretical solutions, and instead focus on intentional practice evolution, identifying implementable strategies so that we as a field can start to walk our wellness talk. Here, we first summarize the thematic discussions from the 2023 ARRS Wellness Summit, and second, share several strategic action items that emerged.

Deep Radiomics Features of Median Nerves for Automated Diagnosis of Carpal Tunnel Syndrome With Ultrasound Images: A Multi-Center Study

OBJECTIVES

Ultrasound is widely used in diagnosing carpal tunnel syndrome (CTS). However, the limitations of ultrasound in CTS detection are the lack of objective measures in the detection of nerve abnormality and the operator-dependent nature of ultrasound imaging. Therefore, in this study, we developed and proposed externally validated artificial intelligence (AI) models based on deep-radiomics features.

METHODS

We have used 416 median nerves from 2 countries (Iran and Colombia) for the development (112 entrapped and 112 normal nerves from Iran) and validation (26 entrapped and 26 normal nerves from Iran, and 70 entrapped and 70 normal nerves from Columbia) of our models. Ultrasound images were fed to the SqueezNet architecture to extract deep-radiomics features. Then a ReliefF method was used to select the clinically significant features. The selected deep-radiomics features were fed to 9 common machine-learning algorithms to choose the best-performing classifier. The 2 best-performing AI models were then externally validated.

RESULTS

Our developed model achieved an area under the receiver operating characteristic (ROC) curve (AUC) of 0.910 (88.46% sensitivity, 88.46% specificity) and 0.908 (84.62% sensitivity, 88.46% specificity) with support vector machine and stochastic gradient descent (SGD), respectively using the internal validation dataset. Furthermore, both models consistently performed well in the external validation dataset, and achieved an AUC of 0.890 (85.71% sensitivity, 82.86% specificity) and 0.890 (84.29% sensitivity and 82.86% specificity), with SVM and SGD models, respectively.

CONCLUSION

Our proposed AI models fed with deep-radiomics features performed consistently with internal and external datasets. This justifies that our proposed system can be employed for clinical use in hospitals and polyclinics.

Value-Based Healthcare and Radiology: How can Value be Measured?

The concept of value-based healthcare (VBH) emerges as a response to traditional models of healthcare system management. More specifically, in radiology, the transition from volume to value has been discussed by its main associations, having as the main concern regarding the role of the specialty in a more integrated healthcare context.

Through a qualitative study, this work aims to analyse and evaluate how this new concept can be implemented in radiology by identifying obstacles and mapping the technical and procedural improvements necessary for its correct implementation in the national context of healthcare provision. Through interviews with different elements of the healthcare sector (from doctors to industry partners and researchers), it was possible to draw a set of metrics for measuring the value of radiology, alongside the implementation of a VBH strategy.

As the main conclusion, the implementation of a strategic agenda for the creation of value in radiology at the national level should be based on the reduction of variability and the identification of best practices in terms of adequacy, quality, safety and efficiency, aiming to satisfy the needs of requesting doctors and patients.

The diagnostic value of susceptibility-weighted imaging for identifying acute intraarticular hemorrhages

PURPOSE

To evaluate the diagnostic performance of susceptibility-weighted imaging (SWI) in identifying acute intraarticular hemorrhages and differentiating blood from other types of joint effusions.

METHODS

Thirty-two patients (21 men, 11 women; mean age 38.7 ± 16.5 SD) clinically suspected of having joint effusion were prospectively included. All the patients underwent both conventional MRI and SWI. Two radiologists independently reviewed the conventional MRI images and scored the likelihood of intraarticular hemorrhage using a 5-level scoring system. Immediately thereafter, SWI images of each patient were also provided for the radiologists, and the scoring was repeated evaluating the conventional MRI and SWI images together. The patients underwent joint aspiration or surgical operation as the reference standard. The area under the curve (AUC) of conventional MRI and conventional MRI + SWI methods were calculated and compared. The weighted kappa analysis was used to evaluate the interobserver agreement.

RESULTS

Traumatic knee injury comprised the majority of study sample. Eighteen out of 32 of the patients were proven to have intraarticular hemorrhage. Using the conventional MRI, reader 1 and 2 achieved AUCs of 0.67 (p = 0.09) and 0.53 (p = 0.76), respectively. Following the addition of SWI, reader 1 and 2 achieved AUCs of 0.96 (p = 0.0001) and 0.95 (p = 0.0001), respectively, and interobserver agreement improved from Κ = 0.61 to Κ = 0.93. Accordingly, difference between the AUCs was 0.28 (p = 0.003) and 0.42 (p = 0.0001) for reader 1 and 2, respectively.

CONCLUSIONS

If confirmed by future studies, SWI enables the reliable and accurate diagnosis of acute intraarticular hemorrhages.

Talking Points: Enhancing Communication Between Radiologists and Patients

Radiologists communicate along multiple pathways, using written, verbal, and non-verbal means. Radiology trainees must gain skills in all forms of communication, with attention to developing effective professional communication in all forms. This manuscript reviews evidence-based strategies for enhancing effective communication between radiologists and patients through direct communication, written means and enhanced reporting. We highlight patient-centered communication efforts, available evidence, and opportunities to engage learners and enhance training and simulation efforts that improve communication with patients at all levels of clinical care.

AI MSK clinical applications: spine imaging

Recent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain in spine imaging, independent from modality or specific application. This review aims to summarize the status quo and future perspective regarding utilization of AI for spine imaging. First, the basics of AI concepts are clarified. Second, the different tasks and use cases for AI applications in spine imaging are discussed and illustrated by examples. Finally, the authors of this review present their personal perception of AI in daily imaging and discuss future chances and challenges that come along with AI-based solutions.

Qualitative and Quantitative Workplace Analysis of Staff Requirement in an Academic Radiology Department

PURPOSE

 The role of today's hospital-based radiologists goes far beyond interpretation-related tasks. This observational study defines these types of activities and quantifies the type of value-adding interactions radiologists experience on a daily basis with referring departments and other health personnel. The purpose of this study is to evaluate the quality and quantity of these value-adding non-image interpretation tasks in the daily routine of hospital-based residents and attending radiologists.

METHODS

 A prospective, observational study was performed in the radiology department of a German university hospital. Two experienced radiologists performed a 30-day observation of the entire medical staff. The observers followed the subject radiologists throughout the workday, recording activities using a time and motion methodology. An evaluation matrix was developed to characterize and quantify image interpretation tasks (IITs), non-image interpretation tasks (NITs), and contingency allowance (CA) for residents and attending radiologists. Here, the example of the MRI unit is used.

RESULTS

 Four main categories of responsibilities for NITs were identified including teaching and education, clinical decision support, management and organization, and patient care. The quantitative analysis for residents showed: IITs 15 h/d (53 %), NITs 9.8 h/d (34 %), CA 2.2 h/d (13 %). For attendings the analysis revealed: IITs 6.7 h/d (40 %), NITs 7.8 h/d (47 %), and CA 1.7 h/d (13 %). This resulted in staff requirements of 2 attendings and 3.4 residents for the MRI unit. On average, 6 TSEs/h occurred in the case of residents and 13 TSEs/h in the case of attendings.

CONCLUSION

 NITs consumed a significant portion of a radiologist's workday. Therefore, the number of examinations performed is not a reliable surrogate for the daily workload of hospital-based radiologists especially in cross-sectional imaging units. Though time-consuming, these non-interpretive tasks are greatly contributing to the fact that modern radiology is assuming a central position in patient management, fulfilling a critical role that surpasses image interpretation-related tasks to include a more integrative and consultative role. These findings will help to further define the changing role of radiologists with respect to other physicians, non-medical personnel, hospital administrators, as well as policy makers.

KEY POINTS

  · Staff requirements are a significant factor in department strategy.. · Targeted analysis can deliver valuable information about workload per activity and the required staff.. · The number of examinations performed is not a reliable surrogate for the daily workload of hospital-based radiologists.. · NITs comprise a significant portion of a radiologist's workday.. · Though time-consuming, non-interpretive tasks contribute to the fact that modern radiology is assuming a central role in patient management..

CITATION FORMAT

· Streit U, Uhlig J, Lotz J et al. Qualitative and Quantitative Workplace Analysis of Staff Requirement in an Academic Radiology Department. Fortschr Röntgenstr 2021; DOI: 10.1055/a-1472-6530.

The Composite Severity Score for Lumbar Spine MRI: a Metric of Cumulative Degenerative Disease Predicts Time Spent on Interpretation and Reporting

Conventional measures of radiologist efficiency, such as the relative value unit, fail to account for variations in the complexity and difficulty of a given study. For lumbar spine MRI (LMRI), an ideal performance metric should account for the global severity of lumbar degenerative disease (LSDD) which may influence reporting time (RT), thereby affecting clinical productivity. This study aims to derive a global LSDD metric and estimate its effect on RT. A 10-year archive of LMRI reports comprising 13,388 exams was reviewed. Objective reporting timestamps were used to calculate RT. A natural language processing (NLP) tool was used to extract radiologist-assigned stenosis severity using a 6-point scale (0 = “normal” to 5 = “severe”) at each lumbar level. The composite severity score (CSS) was calculated as the sum of each of 18 stenosis grades. The predictive values of CSS, sex, age, radiologist identity, and referring service on RT were examined with multiple regression models. The NLP tool accurately classified LSDD in 94.8% of cases in a validation set. The CSS increased with patient age and differed between men and women. In a univariable model, CSS was a significant predictor of mean RT (R² = 0.38, p < 0.001) and independent predictor of mean RT (p < 0.001) controlling for patient sex, patient age, service location, and interpreting radiologist. The predictive strength of CSS was stronger for the low CSS range (CSS = 0–25, R² = 0.83, p < 0.001) compared to higher CSS values (CSS > 25, R² = 0.15, p = 0.05). Individual radiologist study volume was negatively correlated with mean RT (Pearson’s R =  − 0.35, p < 0.001). The composite severity score predicts radiologist reporting efficiency in LMRI, providing a quantitative measure of case complexity which may be useful for workflow planning and performance evaluation.

Comparison of outcomes and cost-effectiveness of trisacryl gelatin microspheres alone versus combined trisacryl gelatin microspheres and gelatin sponge embolization in uterine fibroid embolization

BACKGROUND

Uterine fibroid embolization (UFE) is an effective treatment for uterine leiomyomata. Optimizing the choice of embolic agents is imperative to achieve better patient outcomes with maximum resource utilization.

PURPOSE

To evaluate the efficacy and cost-effectiveness of trisacryl gelatin microspheres (TAGM) versus combined TAGM and gelatin sponge (GS) embolization in the treatment of symptomatic uterine leiomyomata.

MATERIAL AND METHODS

Between July 2007 and December 2010, 106 consecutive patients underwent UFE with TAGM. Between January 2011 and December 2016, 123 consecutive patients underwent UFE with a combination of TAGM/GS. The primary outcomes were successful infarction rate (≥90% infarction) of the dominant leiomyoma and percentage reduction in uterine and dominant leiomyoma volume on MRI at six months. Secondary outcomes included adverse event rates, pain scores, and change in clinical symptoms at six months. The embolic agents utilized per procedure were recorded and a cost-effectiveness analysis was performed.

RESULTS

Baseline characteristics of both groups were similar. Successful infarction was achieved in 93.2% of the TAGM group and 94.6% of the TAGM/GS group (P = 0.52). Reduction in uterine volume (TAGM 40.7%, TAGM/GS 44.4%, P = 0.16) and dominant leiomyoma volume (TAGM 47.6%, TAGM/GS 50.1%, P = 0.29) at six months was similar. No significant difference was observed in symptom improvement at six months (P = 0.8). The mean number of TAGM vials utilized and cost per procedure was 6.3 and $1688.40 for TAGM embolization and 3.6 and $979.50 for TAGM/GS embolization, respectively.

CONCLUSION

Primary and secondary outcomes were comparable when performing UFE with TAGM versus combined TAGM/GS. The combined use of TAGM/GS reduced the mean cost of embolic agents by 42%.

Essential Elements of Natural Language Processing: What the Radiologist Should Know

Natural language is ubiquitous in the workflow of medical imaging. Radiologists create and consume free text in their daily work, some of which can be amenable to enhancements through automatic processing. Recent advancements in deep learning and "artificial intelligence" have had a significant positive impact on natural language processing (NLP). This article discusses the history of how researchers have extracted data and encoded natural language information for analytical processing, starting from NLP's humble origins in hand-curated, linguistic rules. The evolution of medical NLP including vectorization, word embedding, classification, as well as its use in automated speech recognition, are also explored. Finally, the article will discuss the role of machine learning and neural networks in the context of significant, if incremental, improvements in NLP.

Assessing information sources to elucidate diagnostic process errors in radiologic imaging - a human factors framework

Objective

To assess information sources that may elucidate errors related to radiologic diagnostic imaging, quantify the incidence of potential safety events from each source, and quantify the number of steps involved from diagnostic imaging chain and socio-technical factors.

Materials and Methods

This retrospective, Institutional Review Board-approved study was conducted at the ambulatory healthcare facilities associated with a large academic hospital. Five information sources were evaluated: an electronic safety reporting system (ESRS), alert notification for critical result (ANCR) system, picture archive and communication system (PACS)-based quality assurance (QA) tool, imaging peer-review system, and an imaging computerized physician order entry (CPOE) and scheduling system. Data from these sources (January-December 2015 for ESRS, ANCR, QA tool, and the peer-review system; January-October 2016 for the imaging ordering system) were collected to quantify the incidence of potential safety events. Reviewers classified events by the step(s) in the diagnostic process they could elucidate, and their socio-technical factors contributors per the Systems Engineering Initiative for Patient Safety (SEIPS) framework.

Results

Potential safety events ranged from 0.5% to 62.1% of events collected from each source. Each of the information sources contributed to elucidating diagnostic process errors in various steps of the diagnostic imaging chain and contributing socio-technical factors, primarily Person, Tasks, and Tools and Technology.

Discussion

Various information sources can differentially inform understanding diagnostic process errors related to radiologic diagnostic imaging.

Conclusion

Information sources elucidate errors in various steps within the diagnostic imaging workflow and can provide insight into socio-technical factors that impact patient safety in the diagnostic process.

Classifying Safety Events Related to Diagnostic Imaging From a Safety Reporting System Using a Human Factors Framework

Purpose:

To measure diagnostic imaging safety events reported to an electronic safety reporting system (ESRS) and assess steps where they occurred within the diagnostic imaging workflow and contributing socio-technical factors.

Methods:

We evaluated all ESRS safety reports related to diagnostic imaging during calendar 2015 at an academic medical center with 50,000 admissions, 950,000 ambulatory visits, and performing 680,000 diagnostic imaging studies annually. Each report was assigned a 0-4 harm score by the reporter; we classified scores of 2 (minor harm) to 4 (death) as “potential harm”. Two reviewers manually classified reports into steps involved in the diagnostic imaging chain and socio-technical factors per the Systems Engineering Initiative for Patient Safety (SEIPS) framework. Kappa measured inter-reviewer agreement on 10% of reports. The percentage of reports that could cause “potential harm” was compared for each step and socio-technical factor using chi-square analysis.

Results:

Of 11,570 safety reports submitted in 2015, 854 (7%) were related to diagnostic imaging. Although the most common step was Imaging Procedure (54% of reports), potential harm occurred more in Report Communication (Odds Ratio=2.36, p=0.05). Person factors most commonly contributed to safety reports (71%). Potential harm occurred more in safety reports that were related to Task compared to Person factors (OR=5.03, p<0.0001). Kappa was 0.79.

Conclusion:

Safety events were related to diagnostic imaging in 7% of reports and potential harm occurred primarily during Imaging Procedure and Report Communication. Safety events were attributed to multifactorial socio-technical factors. Further work is necessary to decrease safety events related to diagnostic imaging.

Improving diagnosis in health care: perspectives from the American College of Radiology

In September of 2014, the American College of Radiology joined a number of other organizations in sponsoring the 2015 National Academy of Medicine report, Improving Diagnosis In Health Care. Our presentation to the Academy emphasized that although diagnostic errors in imaging are commonly considered to result only from failures in disease detection or misinterpretation of a perceived abnormality, most errors in diagnosis result from failures in information gathering, aggregation, dissemination and ultimately integration of that information into our patients' clinical problems. Diagnostic errors can occur at any point on the continuum of imaging care from when imaging is first considered until results and recommendations are fully understood by our referring physicians and patients. We used the concept of the Imaging Value Chain and the ACR's Imaging 3.0 initiative to illustrate how better information gathering and integration at each step in imaging care can mitigate many of the causes of diagnostic errors. Radiologists are in a unique position to be the aggregators, brokers and disseminators of information critical to making an informed diagnosis, and if radiologists were empowered to use our expertise and informatics tools to manage the entire imaging chain, diagnostic errors would be reduced and patient outcomes improved. Heath care teams should take advantage of radiologists' ability to fully manage information related to medical imaging, and simultaneously, radiologists must be ready to meet these new challenges as health care evolves. The radiology community stands ready work with all stakeholders to design and implement solutions that minimize diagnostic errors.

Building Imaging Institutes of Patient Care Outcomes: Imaging as a Nidus for Innovation in Clinical Care, Research, and Education

Traditionally, radiologists have been responsible for the protocol of imaging studies, imaging acquisition, supervision of imaging technologists, and interpretation and reporting of imaging findings. In this article, we outline how radiology needs to change and adapt to a role of providing value-based, integrated health-care delivery. We believe that the way to best serve our specialty and our patients is to undertake a fundamental paradigm shift in how we practice. We describe the need for imaging institutes centered on disease entities (eg, lung cancer, multiple sclerosis) to not only optimize clinical care and patient outcomes, but also spur the development of a new educational focus, which will increase opportunities for medical trainees and other health professionals. These institutes will also serve as unique environments for testing and implementing new technologies and for generating new ideas for research and health-care delivery. We propose that the imaging institutes focus on how imaging practices-including new innovations-improve patient care outcomes within a specific disease framework. These institutes will allow our specialty to lead patient care, provide the necessary infrastructure for state-of-the art-education of trainees, and stimulate innovative and clinically relevant research.

ESR concept paper on value-based radiology

The European Society of Radiology (ESR) established a Working Group on Value-Based Imaging (VBI WG) in August 2016 in response to developments in European healthcare systems in general, and the trend within radiology to move from volume- to value-based practice in particular. The value-based healthcare (VBH) concept defines "value" as health outcomes achieved for patients relative to the costs of achieving them. Within this framework, value measurements start at the beginning of therapy; the whole diagnostic process is disregarded, and is considered only if it is the cause of errors or complications. Making the case for a new, multidisciplinary organisation of healthcare delivery centred on the patient, this paper establishes the diagnosis of disease as a first outcome in the interrelated activities of the healthcare chain. Metrics are proposed for measuring the quality of radiologists' diagnoses and the various ways in which radiologists provide value to patients, other medical specialists and healthcare systems at large. The ESR strongly believes value-based radiology (VBR) is a necessary complement to existing VBH concepts. The Society is determined to establish a holistic VBR programme to help European radiologists deal with changes in the evolution from volume- to value-based evaluation of radiological activities. Main Messages • Value-based healthcare defines value as patient's outcome over costs. • The VBH framework disregards the diagnosis as an outcome. • VBH considers diagnosis only if wrong or a cause of complications. • A correct diagnosis is the first outcome that matters to patients. • Metrics to measure radiologists' impacts on patient outcomes are key. • The value provided by radiology is multifaceted, going beyond exam volumes.

Preferences of referring physicians regarding the role of radiologists as direct communicators of test results

PURPOSE

Currently, there is a growing need for patient-centered radiology in which radiologists communicate with patients directly. The aim of this study is to investigate the preferences of referring physicians (RPs) regarding direct communication between radiologists and patients.

METHODS

This study was conducted in a single academic hospital using a survey form. The survey items investigated the preferences of RPs regarding: 1. who should be the communicator of test results when a patient with abnormal findings requests information (the options were the radiologist; another health professional with communication skills training (CST); and the RP with CST); and 2. how the communication activity should be conducted if the radiologist is obliged (or chooses) to communicate with the patient directly (the options were that the disclosure should be limited to the findings in the radiology report; the radiologist should emphasize that the RP is the primary physician; and the communication activity should be conducted in accordance with guidelines established by consensus). The respondents were 101 RPs from various fields of specialty; they were asked to rate the items using a 5-point Likert scale. The effects of age, sex, field of specialty (surgical vs. nonsurgical), and total years of experience as a medical specialist on the ratings were statistically compared.

RESULTS

Most RPs preferred that the radiologist transmit the information to the RP without communicating directly with the patient (89.1%). Although 69.3% of the RPs declared that health professionals with CST have priority in communication, 86.1% declared that the RP should be the person who received CST. If the radiologist communicates with patients directly, the RPs favored that 1. the disclosure should be limited to the findings in the radiology report (95%); 2. the communication activity should include an emphasis on the RP as the patient's primary agent (84.1%); and 3. communication should be conducted in accordance with guidelines established by consensus (73.2%). The percentage of strong opinions did not change significantly with regard to age, sex, field of specialty, or total years of experience, except that surgeons expressed strong disagreement with delegating the communication activity to another health professional who received CST (χ² = 9.9; P = 0.042).

CONCLUSION

These findings may serve as a basis to implement institutional and national policies for patient-centered radiology.

Costing in Radiology and Health Care: Rationale, Relativity, Rudiments, and Realities

Costs direct decisions that influence the effectiveness of radiology in the care of patients on a daily basis. Yet many radiologists struggle to harness the power of cost measurement and cost management as a critical path toward establishing their value in patient care. When radiologists cannot articulate their value, they risk losing control over how imaging is delivered and supported. In the United States, recent payment trends directing value-based payments for bundles of care advance the imperative for radiology providers to articulate their value. This begins with the development of an understanding of the providers' own costs, as well as the complex interrelationships and imaging-associated costs of other participants across the imaging value chain. Controlling the costs of imaging necessitates understanding them at a procedural level and quantifying the costs of delivering specific imaging services. Effective product-level costing is dependent on a bottom-up approach, which is supported through recent innovations in time-dependent activity-based costing. Once the costs are understood, they can be managed. Within the high fixed cost and high overhead cost environment of health care provider organizations, stakeholders must understand the implications of misaligned top-down cost management approaches that can both paradoxically shift effort from low-cost workers to much costlier professionals and allocate overhead costs counterproductively. Radiology's engagement across a broad spectrum of care provides an excellent opportunity for radiology providers to take a leading role within the health care organizations to enhance value and margin through principled and effective cost management. Following a discussion of the rationale for measuring costs, this review contextualizes costs from the perspectives of a variety of stakeholders (relativity), discusses core concepts in how costs are classified (rudiments), presents common and improved methods for measuring costs in health care, and discusses how cost management strategies can either improve or hinder high-value health care (realities). ^© RSNA, 2017 Online supplemental material is available for this article.

Affinity Chart Analysis: A Method for Structured Collection, Aggregation, and Response to Customer Needs in Radiology

OBJECTIVE

The objective of this study is to analyze implementation of the voice-of-the-customer method to assess the current state of image postprocessing and reporting delivered by a radiology department and to plan improvements on the basis of referring physicians' preferences.

SUBJECTS AND METHODS

The voice-of-the-customer method consisted of discovery, analysis, and optimization phases. Fifty referring physicians were invited to be interviewed. Interviews addressed the topics of structure, process, outcome, and support. Interviews were dissected into individual statements categorized as fact or feeling. Statements were grouped to find collective voices. Improvements were compiled from affinity charts and were processed by identifying insights.

RESULTS

Ninety-four percent (47/50) of physicians participated, generating 352 statements (81 facts and 271 feelings) that subsequently underwent affinity chart clustering. The resultant affinity charts covered distinct themes: "we need you to know us better," "we need you to consider our workflow," "we need more from your services," "we want to review your data in certain ways," and "we want to do more with you." As a result of the insights gained, the following optimizations were implemented: a software application that improves study requesting, performance tracking, study prioritization, and longitudinal data archiving; six prototype reports containing tabulated data and annotated images; two prototype longitudinal reporting templates assessing aneurysm evolution and treatment-induced changes in organ size over time; and a teaching curriculum for trainees.

CONCLUSION

This study has shown the clinical feasibility to assess the current state of image postprocessing and reporting and to implement improvements of and investments in image postprocessing and reporting infrastructure on the basis of referring physicians' preferences using the voice-of-the-customer method.

Reengineering the radiology enterprise: a summary of the 2014 Intersociety Committee Summer Conference

The current initiative to reform health care from both a quality and a cost perspective has already had a profound impact on the radiology enterprise. We have seen a decrease in the utilization of imaging studies, a reduction in reimbursement, a declining payer mix, shrinking incomes, a proliferation of performance indices, creation of radiology mega-groups, growth of national radiology companies, and increasing turf incursions. Our cheese is clearly on the move, and we must take action to reengineer the radiology enterprise. In keeping with general health care reform, we must be patient-centric, data driven, and outcome based. We must create a radiology enterprise that adheres to the value equation of providing the highest quality health care, for the lowest possible cost, for all citizens.

Mobile devices and their prospective future role in emergency radiology

Mobile devices, wireless networks and software have significantly evolved since the late 1990s and are now available with sufficient computing power, speed and complexity to allow real-time interpretation of radiology studies. Emergency radiology (ER)'s time-sensitive nature would seem to be an excellent match for study interpretation using mobile devices, allowing the radiologist to read studies anywhere, at any time. While suitable for use by the radiologist outside of the hospital, or clinicians and surgeons at the bedside or in the operating room, these devices do have limitations, and regulatory approval for in-hospital diagnostic use is limited. In the ER setting, we suggest that the best use of mobile devices is to be available to consult directly with patients about their imaging findings and to the clinical team during rounds and at handover. This will bring the radiologist to the clinician and patient, helping us to better understand the patient's presentation, educate both the physician and patient and increase the visibility and value of the radiologist as a member of the clinical care team.

The Value of Imaging Part II: Value beyond Image Interpretation

Although image interpretation is an essential part of radiologists' value, there are other ways in which we contribute to patient care. Part II of the value of imaging series reviews current initiatives that demonstrate value beyond the image interpretation. Standardizing processes, reducing the radiation dose of our examinations, clarifying written reports, improving communications with patients and providers, and promoting appropriate imaging through decision support are all ways we can provide safer, more consistent, and higher quality care. As payers and policy makers push to drive value, research that demonstrates the value of these endeavors, or lack thereof, will become increasingly sought after and supported.

Imaging-histologic discordance at percutaneous biopsy of the lung

RATIONALE AND OBJECTIVES

The purpose of this study was to quantify the degree of imaging-histologic discordance in a cohort of patients undergoing computed tomography (CT)-guided lung biopsy for focal lung disease.

MATERIALS AND METHODS

A retrospective review was performed of 186 patients who underwent percutaneous lung biopsy of a parenchymal lesion at our institution between January and December 2009. Diagnostic radiology reports of CT or positron emission tomography-CTs performed before biopsy were used to classify the lesion as malignant or benign by five readers. Pathology reports of the biopsied lesions were classified by three readers. Inter-reader agreement and imaging-histologic concordance were quantified using kappa statistics. Discordant benign cases were then revisited to determine downstream effects.

RESULTS

Inter-reader agreement on report content was substantial or almost perfect with kappas >0.783. Kappas for concordance were as follows: malignant (0.448), primary lung cancer (0.517), metastatic disease to lung (0.449), benign (0.510), and overall agreement (0.381). Of the twelve discordant benign cases that were revisited, four were found to be false negatives, resulting in a delay in diagnosis.

CONCLUSIONS

Our study of imaging-histologic discordance in percutaneous biopsy of lung lesions supports the need for imaging report standardization and improved integration and communication between the fields of radiology and pathology.

The risks of innovation in health care

Innovation in health care creates risks that are unevenly distributed. An evolutionary analogy using species to represent business models helps categorize innovation experiments and their risks. This classification reveals two qualitative categories: early and late diversification experiments. Early diversification has prolific innovations with high risk because they encounter a "decimation" stage, during which most experiments disappear. Participants face high risk. The few decimation survivors can be sustaining or disruptive according to Christensen's criteria. Survivors enter late diversification, during which they again expand, but within a design range limited to variations of the previous surviving designs. Late diversifications carry lower risk. The exception is when disruptive survivors "diversify," which amplifies their disruption. Health care and radiology will experience both early and late diversifications, often simultaneously. Although oversimplifying Christensen's concepts, early diversifications are likely to deliver disruptive innovation, whereas late diversifications tend to produce sustaining innovations. Current health care consolidation is a manifestation of late diversification. Early diversifications will appear outside traditional care models and physical health care sites, as well as with new science such as molecular diagnostics. They warrant attention because decimation survivors will present both disruptive and sustaining opportunities to radiology. Radiology must participate in late diversification by incorporating sustaining innovations to its value chain. Given the likelihood of disruptive survivors, radiology should seriously consider disrupting itself rather than waiting for others to do so. Disruption entails significant modifications of its value chain, hence, its business model, for which lessons may become available from the pharmaceutical industry's current simultaneous experience with early and late diversifications.

Methods and challenges in quantitative imaging biomarker development

Academic radiology is poised to play an important role in the development and implementation of quantitative imaging (QI) tools. This article, drafted by the Association of University Radiologists Radiology Research Alliance Quantitative Imaging Task Force, reviews current issues in QI biomarker research. We discuss motivations for advancing QI, define key terms, present a framework for QI biomarker research, and outline challenges in QI biomarker development. We conclude by describing where QI research and development is currently taking place and discussing the paramount role of academic radiology in this rapidly evolving field.

IT infrastructure in the era of imaging 3.0

Imaging 3.0 is a blueprint for the future of radiology modeled after the description of Web 3.0 as "more connected, more open, and more intelligent." Imaging 3.0 involves radiologists' using their expertise to manage all aspects of imaging care to improve patient safety and outcomes and to deliver high-value care. IT tools are critical elements and drivers of success as radiologists embrace the concepts of Imaging 3.0. Organized radiology, specifically the ACR, is the natural convener and resource for the development of this Imaging 3.0 toolkit. The ACR's new Imaging 3.0 Informatics Committee is actively working to develop the informatics tools radiologists need to improve efficiency, deliver more value, and provide quantitative ways to demonstrate their value in new health care delivery and payment systems. This article takes each step of the process of delivering high-value Imaging 3.0 care and outlines the tools available as well as additional resources available to support practicing radiologists. From the moment when imaging is considered through the delivery of a meaningful and actionable report that is communicated to the referring clinician and, when appropriate, to the patient, Imaging 3.0 IT tools will enable radiologists to position themselves as vital constituents in cost-effective, high-value health care.

The nature of change

There is little doubt that health care is facing change. The conventional view of change, based on evolution, is that it is slow, gradual, and generally an evenly paced system change. Unfortunately, it is much more uneven, being burstlike, unpredictable, and, in fact, steplike. This pattern is called punctuated equilibrium, which is well illustrated by the metaphorical picture of the Devil's Staircase. These features call for a reassessment of how to cope with change. In addition to detecting change, responding to it and preparing for it require some understanding of the role of experimentation because the evolution algorithm is simple: experimentation, selection, and replication. Experimentation in radiology forms a continuum ranging from modifying traits to developing variants of diagnostic, interventional, and even new integrated services. We often describe experiments by relating their motives (ie, adaptation and innovation), but complex systems see only experiments available for selection. Experiments generating new services and business models are the important ones because they create the "subspecies" of radiology, which offers a robust set of options capable of withstanding new health care selection forces. Experimentation and selection are the prerequisites of replication (i.e., survival). It behooves radiology to combine and concatenate diversified, reactive, and innovative experiments to explore adjacent domains to expand its set of options. Just as in Darwinian evolution, major changes on the health care landscape will be at the specialty, ie, species and subspecies levels, rather than at the individual specialty trait level. Radiology needs a strong set of "subspecies" to succeed in selection to enhance evolution and allow replication.

Digitization of medicine: how radiology can take advantage of the digital revolution

In the era of medical cost containment, radiologists must continually maintain their actual and perceived value to patients, payers, and referring providers. Exploitation of current and future digital technologies may be the key to defining and promoting radiology's "brand" and assure our continued relevance in providing predictive, preventive, personalized, and participatory medicine. The Association of University of Radiologists Radiology Research Alliance Digitization of Medicine Task Force was formed to explore the opportunities and challenges of the digitization of medicine that are relevant to radiologists, which include the reporting paradigm, computational biology, and imaging informatics. In addition to discussing these opportunities and challenges, we consider how change occurs in medicine, and how change may be effected in medical imaging community. This review article is a summary of the research of the task force and hopefully can be used as a stimulus for further discussions and development of action plans by radiology leaders.

Academic radiology in the new health care delivery environment

RATIONALE AND OBJECTIVES

Ongoing concerns over the rising cost of health care are driving large-scale changes in the way that health care is practiced and reimbursed in the United States.

MATERIALS AND METHODS

To effectively implement and thrive within this new health care delivery environment, academic medical institutions will need to modify financial and business models and adapt institutional cultures. In this article, we review the expected features of the new health care environment from the perspective of academic radiology departments.

CONCLUSIONS

Our review will include background on accountable care organizations, identify challenges associated with the new managed care model, and outline key strategies-including expanding the use of existing information technology infrastructure, promoting continued medical innovation, balancing academic research with clinical care, and exploring new roles for radiologists in efficient patient management-that will ensure continued success for academic radiology.

The total value equation: a suggested framework for understanding value creation in diagnostic radiology

As a result of macroeconomic forces necessitating fundamental changes in health care delivery systems, value has become a popular term in the medical industry. Much has been written recently about the idea of value as it relates to health care services in general and the practice of radiology in particular. Of course, cost, value, and cost-effectiveness are not new topics of conversation in radiology. Not only is value one of the most frequently used and complex words in management, entire classes in business school are taught around the concept of understanding and maximizing value. But what is value, and when speaking of value creation strategies, what is it exactly that is meant? For the leader of a radiology department, either private or academic, value creation is a core function. This article provides a deeper examination of what value is, what drives value creation, and how practices and departments can evaluate their own value creation efficiencies. An equation, referred to as the Total Value Equation, is presented as a framework to assess value creation activities and strategies.

Measuring radiology's value in time saved

Because radiology has historically not measured its added value to patient care and thus not communicated it in easily understood terms to all stakeholders, the specialty must correct this to prepare for the eventual transition from the current fee-for-service payment schedule to new value-based reimbursement systems. Given the increasing risk for marginalization, radiologists need to engage clinicians and managers to map the processes and associated costs of episodes of patient care to identify areas for providing and improving integrated diagnostic information and to measure the value thereof. In such time-driven, activity-based costing practices, radiologists should highlight how proper investments in the information generated by imaging and how radiologists' associated consultative and coordination of services can save greater resources downstream, especially in the nonrenewable resource of physician time, an increasingly scarce health care resource. Using physician time in the most efficient way will be a key element for decreasing health care costs at the aggregate level. Therefore, expressing radiology's contribution in terms of downstream physician time saved is a metric that can be easily understood by all stakeholders. In a conceptual framework centered on value, the specialty of radiology must focus more on its most important product, actionable information, rather than on imaging technologies themselves. Information, unlike imaging technologies, does not depreciate with time but rather increases in value the more it is used.