Multi-case Study Research Articles

Data-Driven Agile Leadership: The Impact of Business Intelligence Solutions on Transformation Outcomes

This article examines the integration of Business Intelligence (BI) solutions in empowering leadership teams during Agile transformations within organizations. As businesses increasingly adopt Agile methodologies to enhance adaptability and efficiency, leaders face unique challenges in monitoring and steering these complex transformations. Through a multi-case study approach, we investigate how BI tools provide real-time insights into key performance indicators such as sprint velocity and team capacity, significantly enhancing leadership's ability to make informed decisions and identify bottlenecks in the Agile process. Our findings reveal that the implementation of BI solutions fosters a culture of transparency and accountability, enabling leaders to navigate the intricacies of Agile transformation more effectively. The article contributes to the growing body of literature on Agile leadership by highlighting the symbiotic relationship between data-driven decision-making and successful organizational change. We conclude that the strategic use of BI in Agile environments not only improves visibility into transformation progress but also enhances overall organizational performance in response to dynamic market demands.

A multi-case study exploring the effect of interventions on food safety culture maturity

A multi-case study exploring the effect of interventions on food safety culture maturity

Exploration of Strategies and Learning Experience Process of Mompreneurs: Case Studies in the Halal Certification

This study aims to explore the strategies and learning experiences process of mompreneurs. The halal certification process was chosen as the point of this because the process of obtaining halal certification is a process that requires preparation and time. In addition, obtaining halal certification is a legality that is considered to reflect the needs of Muslims. This study uses a multi-case study methodology. Data were obtained through observation and interviews. Meanwhile, data triangulation was carried out by digital tracking. This study reveals that the learning experiences process of mompreneurs is utilizing programs from various government agencies to overcome cost challenges and build a network through which to obtain halal certification. Certification experience increases the mompreneur’s ability in good production processes but does not directly impact sales. Momprenaurs' commitment is built on the motivation to protect the family heritage. In all cases, they did not apply a low-cost strategy, so they prioritized the sales channel for souvenir centers and did not take advantage of the online market because prices could not compete in the online market.

Accessibility engineering in the mhealth industry - A multi-case study

Abstract Medical apps, i.e. apps that fall under the EU Medical Device Regulation (MDR), are increasingly becoming a relevant part of healthcare in European countries. This is particularly evident in the numerous partnerships between app vendors and insurers as well as in the launches of national reimbursement programs. However, when it comes to enabling as many patients as possible to benefit from the medical advantages associated with the use of these apps, funding is only one part of the equation. It is up to the app vendors to develop barrier-free user interfaces so that people - regardless of individual characteristics such as cognitive abilities, physical limitations or language skills - can interact successfully with the app. Little is known about how these companies approach the topic of accessibility, what challenges they face and how big the impact of medical device legislation and other regulations on accessibility is. Against this background, we are undertaking a case study in several companies offering apps on the German market that are certified as medical devices and targeted at patients. Through interviews with employees with various roles (e.g. business, engineering, design) we are aiming at reconstructing the development processes of the apps with a focus on accessibility. We plan to expand the results by interviews with experts, e.g., in the area of MDR conformity assessment. 20 interviews in four companies have revealed that accessibility only plays a minor role during development. As a result, the topic is not systematically addressed, but only a few features are implemented. The app’s compatibility with screen reader or voice control was not explicitly addressed in any of the companies. There was also no deliberate involvement of people with disabilities in user studies. The preliminary results also indicate that the influence of medical device legislation on the implementation of accessibility is negligible. Key messages • User interface accessibility has a very low priority in the mhealth companies we have examined so far. • The current regulations are not sufficient in enforcing the basic implementation of accessibility features requiring more guidance and detailed regulations, given our sample of companies.

Deep learning improves detection of aortic stenosis in b-mode ultrasound: results of a pivotal multicenter validation study using artificial intelligence

Abstract Background Aortic stenosis (AS) is a highly prevalent and morbid condition, with moderate or severe AS present in 9% of patients over 75 years. Despite improved diagnostic and therapeutic methods, AS remains underdiagnosed, particularly in Black patients and underserved communities. Echocardiography (echo) is effective for detecting AS but requires expertise to quantify and interpret valve gradients and valve area. We hypothesized that a deep learning (DL) algorithm could be trained to detect AS severity using B-mode (non-Doppler) echo alone, the modality most likely to be available in point-of-care ultrasound (POCUS) studies. Here, we present the results of a multicenter pivotal trial to test whether artificial intelligence (AI) can help increase the detection of AS from B-mode echoes. Methods A convolutional neural network (CNN) was trained to classify the severity of aortic stenosis from 3 B-mode echo views of the aortic valve (parasternal long- and short-axis and apical 5-chamber). The training dataset had over 500,000 cine loops from 29,527 echoes in 26,981 patients. A fully crossed multireader multicase study was conducted using 220 echoes never seen during algorithm development. 5 level II-trained cardiologists (referred to as POCUS readers as they only reviewed B-mode clips) were presented with these echoes twice at least a month apart, once with and again without AI interpretation of AS severity. Readers identified 2 dichotomous severity levels (either "suggestive of moderate to severe AS" or not), with ground truth established by 3 level III-trained cardiology echo experts. While experts had access to full studies (including Doppler) to adjudicate severity, POCUS readers had no Doppler or measurements of any kind available. Sensitivity and specificity were compared for the 5 POCUS readers when aided by the AI algorithm vs unaided, with similar tests of inter-reader agreement. Results There was a statistically significant improvement in sensitivity (+5.5%, 95% CI [1.5%, 9.5%], p=0.007) with stable specificity (-0.3%, 95% CI [-3.6%, 3.0%], p=NS) when the 5 POCUS readers received the assistance of the AI software. Fig 1 shows 2,500 bootstrapping assessments to better show consistency of these findings. In addition, the POCUS inter-reader agreement (overall percent agreement) improved by approximately 7% (p<0.001), becoming comparable to that of expert readers (Fig 2). Conclusions In a comprehensive multireader pivotal trial, an AI algorithm improved the performance of POCUS cardiologist readers to identify significant AS from limited B-mode echoes as might be obtained in screening or outreach settings. Sensitivity for detection of moderate-severe AS increased significantly by 5.5% with stable specificity. Inter-reader agreement improved to resemble that of expert cardiologists given access to full study information, including Doppler. AI may have a role in assisting detection of significant AS from limited B-mode echoes.Fig 1Fig 2

In development intervention, professionals aim to enhance working practices and interaction

Abstract Background The social services and healthcare professions are experiencing a global labor shortage. Enhancing the appeal and retention requires the development of work and processes through community-level interventions that reduce workload and bolster resources. Further research into such interventions is necessary. This study focuses on a systematic community-based practice development model (Breakthrough Collaboratives) to evaluate the change in alignment with the development intervention’s objectives and the prerequisites for change. The evaluation will utilize the process evaluation model for well-being at work projects and health promotion interventions. Methods This qualitative process evaluation employs a multi-case study approach to depict the changes occurring during the development intervention. It assesses the development processes of fifteen workplaces across Finland. The research material includes recorded group discussions from the initial workshop, where professionals establish goals and development targets for their work. The qualitative data are analyzed using content analysis. The analysis is guided by questions such as: What goals and development objectives do participants set for their work? What workplace-specific characteristics inform these objectives? Results Preliminary findings indicate that the work units’ development objectives concentrate on updating the unit’s common rules, enhancing the induction process for new employees, improving work behavior, and refining meeting practices. Workplace-specific characteristics differ based on the work unit’s sector, the level of trust among professionals, and their willingness to critically evaluate management. Additionally, competence and professionalism emerge as prominent themes in group discussions. Conclusions In a workplace development intervention, professionals aim to enhance common working practices and interaction, with the goal of improving well-being at work. Key messages • Enhancing operational practices and promoting positive interpersonal conduct among colleagues constitutes a pivotal goal in advancing social and health care work units. • The Community based intervention provides workplaces with concrete models to support co-creation and permanent changes in working practices.

Racial group differences and export market access challenges in agricultural value chains and supply networks of SMEs in South Africa

ABSTRACT Although previous studies provide an insightful and categorised nature of internal and external export barriers experienced by agricultural SMEs in general; there is little, if any, strategic insights on the racial nuances in value chain barriers for most agricultural SMEs that target global export markets. This study posits that export barriers are not uniform and differ based on race and the context in which the agricultural SME is based. Hence, we specifically explore the nature of export barriers per race within the agro-value chains in South Africa and juxtapose these with the dynamic market and historical conditions of the South African market environment. In this multi-case study, we focused mainly on the differences between black and white-owned agricultural SMEs riding on their different supply networks’ capabilities to navigate the export barriers they face. The findings serve to develop seminal knowledge to enhance export capabilities and opportunities for minority groups globally and more importantly to highlight the underlying drivers for racial imbalances in agro-supply chains. Although the findings are geographically skewed to South Africa, the market dynamics are relevant across countries with similar demographic characteristics and provide a platform for future research.

The Relationship Between Corporate ESG Disclosure and the Chinese-style Modernization

Against the backdrop of contemporary Chinese-style modernization, the state has placed increasing demands on enterprises to adhere to the principles of Environmental (E), Social (S), and Governance (G). Consequently, enterprises will face more challenges and transformations. This paper employs a multi-case study method, focusing on the sample data of Wahaha Group and Ant Group. Based on Wahaha Group's 2020 Social Responsibility Report and Ant Group's 2022 Sustainable Development Report, the paper analyzes the impact and role of corporate ESG disclosure on Chinese-style modernization from the perspectives of people-oriented, shared prosperity, and green development. The paper argues that Wahaha Group and Ant Group fully embody the new development concept of "coordination, greenness, and sharing" in their disclosure of ESG information, which has a close relationship with "Chinese-style modernization" and holds significant importance in contemporary China.

Assessing the impact of deep-learning assistance on the histopathological diagnosis of serous tubal intraepithelial carcinoma (STIC) in fallopian tubes.

In recent years, it has become clear that artificial intelligence (AI) models can achieve high accuracy in specific pathology-related tasks. An example is our deep-learning model, designed to automatically detect serous tubal intraepithelial carcinoma (STIC), the precursor lesion to high-grade serous ovarian carcinoma, found in the fallopian tube. However, the standalone performance of a model is insufficient to determine its value in the diagnostic setting. To evaluate the impact of the use of this model on pathologists' performance, we set up a fully crossed multireader, multicase study, in which 26 participants, from 11 countries, reviewed 100 digitalized H&E-stained slides of fallopian tubes (30 cases/70 controls) with and without AI assistance, with a washout period between the sessions. We evaluated the effect of the deep-learning model on accuracy, slide review time and (subjectively perceived) diagnostic certainty, using mixed-models analysis. With AI assistance, we found a significant increase in accuracy (p < 0.01) whereby the average sensitivity increased from 82% to 93%. Further, there was a significant 44 s (32%) reduction in slide review time (p < 0.01). The level of certainty that the participants felt versus their own assessment also significantly increased, by 0.24 on a 10-point scale (p < 0.01). In conclusion, we found that, in a diverse group of pathologists and pathology residents, AI support resulted in a significant improvement in the accuracy of STIC diagnosis and was coupled with a substantial reduction in slide review time. This model has the potential to provide meaningful support to pathologists in the diagnosis of STIC, ultimately streamlining and optimizing the overall diagnostic process.

Os desafios de egressos do sistema prisional na inserção em ambientes laborais e o papel da política pública de economia solidária

Prison institutions, in Brazil, should be an effective instrument for the rehabilitation of people previously incarcerated after serving their sentence. However, the prison sphere has not provided effective opportunities to prepare these individuals. The principal objective of this article was to identify the challenges faced by people previously incarcerated for their insertion in the world of work and the contributions that the public policy of Solidarity Economy can provide in this process. It was a multi-case study and the data collection method consisted of semi-structured interviews with individuals who have already been in prison and are part of Solidarity Economy Cooperatives in the city of Araraquara, São Paulo state. As results found by the research with the people previously incarcerated, when trying to re-enter work environments, the following difficulties can be pointed out: prejudice and discrimination, lack of documentation, fine due with justice, low education, insufficient professional qualification to access more valued jobs in the world of work and the absence of programs that generate opportunities, both on the part of public power and society. The results of this research also point out that the Solidarity Economy public policy, which encourages the organization of people previously incarcerated in Solidarity Economy Enterprises, can be one of the alternatives to prevent criminal recidivism.

Information Stratification: An Understanding of Rural Governance in the New Media Era

Current research on media governance emphasizes the technological aspect of information as a tool but lacks sufficient attention to the digital transformation of information subjects. This paper aims to focus on the internal information characteristics of rural governance in the digital age, thus understanding the changes of rural governance subjects in the information society under new media contexts. Based on more than a decade of fieldwork in rural areas of Beijing conducted by the research team, this study employs in-depth interviews and participant observation in a multi-case study, exploring the structural representation of rural governance from an information perspective. The research reveals that in the new media era, rural society, under multiple governance bodies, generates differentiated information stratification, specifically manifesting as instrumental rational information in the formal governance layer, proxy implementation information in the semi-formal governance layer, and livelihood-adaptive information in the informal governance layer. Among these, the authority-driven governance information in the formal layer is the core part of the rural governance system. The subjects and structures of information under multiple governance bodies are interconnected and coexist within the internal field of rural governance, subsequently driving the centralization of formal governance information, the collaboration of semi-formal governance information, and the alienation of informal governance information. This leads to the emergence of orderly information stratification within the multi-layered governance structure. Information stratification deepens the explanatory pathway of multi-layered governance in rural social studies and proposes new perspectives for understanding rural governance issues in the new media era.

Internal quality assurance strategies for enhancing students’ soft skills in Tanzania’s higher education institutions

This paper explored the strategies used by the Internal Quality Assurance (IQA) units of the Higher Education Institutions (HEIs) to enhance soft skills among university students in Tanzania. The qualitative research approach was adopted using a multi-case study design involving a sample of thirty-nine (39) participants obtained through purposive and convenient sampling procedures. The study used interviews, focus group discussion and documentary review methods to collect data for the study. The paper deployed thematic and content analysis procedures in the analysis of data. The findings revealed four quality assurance strategies to enhance university students’ soft skills, including developing and reviewing curricula, prolonged field attachment, student assessment and developing academic personnel. The study concludes that there is more to be done to ensure that HEIs students are competent in soft skills for their future life realities. The study recommends assigning soft skills greater emphasis in HEIs curricula due to their importance in future life of the students. More studies on the studied topic using larger samples and different contexts are also recommended.

Can AI generate diagnostic reports for radiologist approval on CXR images? Amulti-reader and multi-case observer performance study.

Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR) images and writing radiology reports is often difficult and time-consuming. To access the utility of a novel artificial intelligence (AI) system (MOM-ClaSeg) in enhancing the accuracy and efficiency of radiologists in detecting heterogenous lung abnormalities through a multi-reader and multi-case (MRMC) observer performance study. Over 36,000 CXR images were retrospectively collected from 12 hospitals over 4 months and used as the experiment group and the control group. In the control group, a double reading method is used in which two radiologists interpret CXR to generate a final report, while in the experiment group, one radiologist generates the final reports based on AI-generated reports. Compared with double reading, the diagnostic accuracy and sensitivity of single reading with AI increases significantly by 1.49% and 10.95%, respectively (P < 0.001), while the difference in specificity is small (0.22%) and without statistical significance (P = 0.255). Additionally, the average image reading and diagnostic time in the experimental group is reduced by 54.70% (P < 0.001). This MRMC study demonstrates that MOM-ClaSeg can potentially serve as the first reader to generate the initial diagnostic reports, with a radiologist only reviewing and making minor modifications (if needed) to arrive at the final decision. It also shows that single reading with AI can achieve a higher diagnostic accuracy and efficiency than double reading.

Organizational innovations related to Primary Care Access Points (GAP) for unattached patients in Quebec: a multi-case qualitative study

BackgroundBeing attached to a primary care (PC) provider is at the core of a strong primary health care system. Centralized waiting lists (CWL) for unattached patients have been implemented in eight provinces of Canada to support the attachment process. In Quebec, the Ministry of Health mandated the implementation of Primary Care Access Points (GAP) across the province to help unattached patients navigate the health system while awaiting attachment through the CWL. Several local health territories developed complementary innovations to the GAP to respond to local population needs. This paper aims to describe five organizational innovations implemented locally.MethodsThis multi-case qualitative study was conducted in four local health territories in the province of Quebec. Fifty-two semi-structured interviews with healthcare managers, nurses, physicians, other health professionals and administrative staff were conducted between April 2023 and April 2024. An interview guide was developed based on existing frameworks on the implementation of innovations and the evaluation of the GAP. Thematic analysis was conducted using NVivo software. Inductive and deductive approaches were used to develop relevant codes and themes. Logic models were built to describe the organizational innovations.ResultsFive organizational innovations are described. First, a multidisciplinary clinic aimed at responding to patients with mental health issues was implemented. Second, a nurse clinic was implemented to provide temporary care for patients with unstable chronic illnesses. The third innovation is a mobile proximity clinic where unattached GAP patients are first evaluated by a paramedic before receiving care from a nurse. Fourth, a pharmacist trajectory was implemented to increase engagement of community pharmacists to respond to GAP patients. The last innovation is a decentralized GAP offering in-person nursing care to unattached GAP patients.ConclusionsDescriptions of these five innovations are key to inform other territories and provinces on ways to improve access for unattached patients while they are waiting to be attached. The introduction of the GAP and the organizational innovations, suggests a transition where access to PC services does not rely solely on attachment status.

Pre-service teachers’ world history discussions: Distancing global citizenship, justice, and identity

In this qualitative multi-case study, we illustrate how three pre-service teachers from varying programs and social positions framed discussions in world history classrooms, and we discuss the broader narratives about the world their discussions communicated. Using critical theories of global citizenship education (GCE) and the Dynamic Systems Model of Role Identity (DSMRI), three primary data sources inform our analysis: observations of participants’ discussions, decision memos written while reflecting on their discussion facilitation, and semi-structured interviews. The three participants prioritized making discussion content relevant to their students. However, their facilitation practice ultimately contradicted such aims by favoring dominant and distancing global narratives, though this tendency went unacknowledged in interviews and while writing reflective memos. Our DSMRI cross-case analysis reveals how candidates’ role identities manifested in classroom discourse, with ontological and epistemological beliefs reliant on dominant global narratives. Despite varied personal experiences offering potential strengths for critical GCE teaching, participants’ self-perceived limited world history content knowledge appeared to condition their distanced and power-neutral facilitation approaches. By unconsciously relying on dominant narratives, teachers’ discussion facilitation positioned global issues firmly in the past and distant from students’ lived experiences and agency.

From Tiny Cues to Business Transformation: Serendipity and Strategic Project Initiations in a Small Family Business

Insights on strategic project processes are needed in a contemporary society characterized by many disruptions and major transformations. In this paper, we supplement existing theoretical framings on the process of strategic project initiation by exploring the relationship between serendipity, i.e., surprising and valuable discoveries, and strategic project initiations. With a qualitative longitudinal embedded multi-case study approach, we study a family business entrepreneur who successfully transforms her small family business via strategic projects initiated by serendipity triggers. Our research provides four contributions related to the nature of the relationship between serendipity and strategic project initiation: (1) the causality between the two phenomena can go in both directions; (2) strategic project initiation can relate to Archimedean, Columbian, or Galilean serendipity; (3) a time lag between the serendipity trigger and the strategic project initiation may exist; and (4) business stakeholders and family stakeholders may be involved in serendipity triggers and strategic project initiations through different logics.

‘Round outside and square inside’: language teachers’ emotion regulation strategies in crosscultural teaching contexts

ABSTRACT With the expansion of transnational language learning and teaching, chances have increased for language teachers to work in crosscultural teaching contexts and regulate their emotions in the face of crosscultural emotional challenges. This study investigated the emotion regulation strategies employed by language teachers in crosscultural teaching contexts. Through a qualitative multi-case study with six Chinese as a second language (CSL) teachers in China, data collected from semi-structured interviews, class observations, and teacher reflective journals revealed seven emotion regulation strategies of three categories: restraining and pretending of surface acting; reframing, reconcentrating, and repositioning of deep acting; releasing and relieving of genuine expressing. These three categories reflected language teachers’ three experiences to cultural differences: deliberate minimisation, reflective acceptance, and communicative adaptation. The identified emotion regulation strategies also revealed two paradoxes existing in teacher-student interactions in crosscultural language teaching, which can be summarised as the Chinese idiom ‘round outside and square inside’. The study also proposed practical implications for language teachers’ emotion regulation and offered suggestions for institutions concerning teacher emotion in crosscultural teaching contexts.

Enhancing supply chain resilience through the supply network approach

Purpose This study aims to investigate the efficacy of the supply network approach in bolstering supply chain resilience amidst escalating global uncertainty. With enterprises worldwide facing increasing threats that disrupt supply chains, this research explores how firms enhance supply network resilience during crises. Design/methodology/approach Using a multi-case study design, this research thoroughly examines interactions within firms’ supply networks to uncover new insights on supply network approach and how firms enhance supply network resilience against global uncertainty. The selection of cases was methodologically aligned to represent diverse industries and geographical locations to ensure a comprehensive analysis. Findings This study’s findings reveal how firms develop supply network resilience during global crises. The supply network perspective provides a deeper understanding of how firms manage supply chain interactions, interdependencies and strategic positions to survive and thrive during crises. The conceptual framework developed here provides insights that can foster improved coordination and facilitate effective temporary organising. The framework highlights the need for firms to proactively seize opportunities and mitigate risks within their global supply chains during crises to boost overall resilience. Originality/value Offering novel insights into the domain of supply chain networks, this study underscores novel perspectives of the supply network approach when firms develop supply chain resilience during global crises. Highlighting the adaptive responses of firms that integrate these approaches enriches the understanding of strategic manoeuvres firms can use to navigate global uncertainty and secure supply chain continuity.

Strategic digital product management: Nine approaches

Context:The role of product management (PM) is key for building, implementing and managing software-intensive systems. Whereas engineering is concerned with how to build systems, PM is concerned with ’what’ to build and ’why’ we should build the product. The role of PM is recognized as critical for the success of any product. However, few studies explore how the role of PM is changing due to recent trends that come with digitalization and digital transformation. Objectives:Although there is prominent research on PM, few studies explore how this role is changing due to the digital transformation of the software-intensive industry. In this paper, we study how trends such as DevOps and short feedback loops, data and artificial intelligence (AI), as well as the emergence of digital ecosystems, are changing current product management practices. Methods:This study employs a qualitative approach using multi-case study research as the method. For our research, we selected five case companies in the software-intensive systems domain. Through workshop sessions, frequent meetings and interviews, we explore how DevOps and short feedback loops, data and artificial intelligence (AI), and digital ecosystems challenge current PM practices. Results:Our study yielded an in-depth understanding of how digital transformation of the software-intensive systems industry is changing current PM practices. We present empirical results from workshops and from interviews in which case company representatives share their insights on how software, data and AI impact current PM practices. Based on these results, we present a framework organized along two dimensions, i.e. a certainty dimension and an approach dimension. The framework helps structure the approaches product managers can employ to select and prioritize development of new functionality. Contributions:The contribution of this paper is a framework for ’Strategic Digital Product Management’ (SDPM). The framework outlines nine approaches that product managers can employ to maximize the return on investment (RoI) of R&D using new digital technologies.

Enhancing Radiologist Reading Performance by Ordering Screening Mammograms Based on Characteristics That Promote Visual Adaptation.

Background Mammographic background characteristics may stimulate human visual adaptation, allowing radiologists to detect abnormalities more effectively. However, it is unclear whether density, or another image characteristic, drives visual adaptation. Purpose To investigate whether screening performance improves when screening mammography examinations are ordered for batch reading according to mammographic characteristics that may promote visual adaptation. Materials and Methods This retrospective multireader multicase study was performed with mammograms obtained between September 2016 and May 2019. The screening examinations, each consisting of four mammograms, were interpreted by 13 radiologists in three distinct orders: randomly, by increasing volumetric breast density (VBD), and based on a self-supervised learning (SSL) encoding (examinations automatically grouped as "looking similar"). An eye tracker recorded radiologists' eye movements during interpretation. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity of random-ordered readings were compared with those of VBD- and SSL-ordered readings using mixed-model analysis of variance. Reading time, fixation metrics, and perceived density were compared using Wilcoxon signed-rank tests. Results Mammography examinations (75 with breast cancer, 75 without breast cancer) from 150 women (median age, 55 years [IQR, 50-63]) were read. The examinations ordered by increasing VBD versus randomly had an increased AUC (0.93 [95% CI: 0.91, 0.96] vs 0.92 [95% CI: 0.89, 0.95]; P = .009), without evidence of a difference in specificity (89% [871 of 975] vs 86% [837 of 975], P = .04) and sensitivity (both 81% [794 of 975 vs 788 of 975], P = .78), and a reduced reading time (24.3 vs 27.9 seconds, P < .001), fixation count (47 vs 52, P < .001), and fixation time in malignant regions (3.7 vs 4.6 seconds, P < .001). For SSL-ordered readings, there was no evidence of differences in AUC (0.92 [95% CI: 0.89, 0.95]; P = .70), specificity (84% [820 of 975], P = .37), sensitivity (80% [784 of 975], P = .79), fixation count (54, P = .05), or fixation time in malignant regions (4.6 seconds, P > .99) compared with random-ordered readings. Reading times were significantly higher for SSL-ordered readings compared with random-ordered readings (28.4 seconds, P = .02). Conclusion Screening mammography examinations ordered from low to high VBD improved screening performance while reducing reading and fixation times. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Grimm in this issue.