The prioritization of software requirements is necessary for successful software development. A use case is a useful approach to represent and prioritize user-centric requirements. Use-case-based prioritization is used to rank use cases to attain a business value based on identified criteria. The research community has started engaging use case modeling for emerging technologies such as the IoT, mobile development, and big data. A systematic literature review was conducted to understand the approaches reported in the last two decades. For each of the 40 identified approaches, a review is presented with respect to consideration of scenarios, the extent of formality, and the size of requirements. Only 32.5% of the reviewed studies considered scenario-based approaches, and the majority of reported approaches were semiformally developed (53.8%). The reported result opens prospects for the development of new approaches to fill a gap regarding the inclusive of strategic goals and respective business processes that support scenario representation. This study reveals that existing approaches fail to consider necessary criteria such as risks, goals, and some quality-related requirements. The findings reported herein are useful for researchers and practitioners aiming to improve current prioritization practices using the use case approach.

Background: Breast cancer treatment has been described as a dynamic and patient-centered approach that emphasizes adaptability and flexibility throughout the treatment process. Breast cancer is complex, with varying subtypes and stages, making it important to tailor treatment plans to each patient’s unique circumstances. Breast cancer treatment delivery relies on a multidisciplinary team of health care professionals who collaborate to provide personalized care and quick adaptation to changing conditions to optimize outcomes while minimizing side effects and maintaining the patient’s quality of life. However, agility in breast cancer treatment has not been defined according to common agile values and described in language comprehensible to breast cancer professionals. In the rapidly evolving landscape of breast cancer treatment, the incorporation of agile values from software engineering promises to enhance patient care. Objective: Our objective is to propose agile values for breast cancer treatment adopted and adapted from software engineering. We also aim to validate how these values conform to the concept of agility in the breast cancer context through referencing past work. Methods: We applied a structured research methodology to identify and validate 4 agile values for breast cancer treatment. In the elicitation phase, through 2 interviews, we identified 4 agile values and described them in language that resonates with breast cancer treatment professionals. The values were then validated by a domain expert and discussed in the context of supporting work from the literature. Final validation entailed a domain expert conducting a walkthrough of the 4 identified agile values to adjust them as per the reported literature. Results: Four agile values were identified for breast cancer treatment, and among them, we validated 3 that conformed to the concept of agility. The fourth value, documentation and the quality of documentation, is vital for breast cancer treatment planning and management. This does not conform to agility. However, its nonagility is vital for the agility of the other values. None of the identified agile values were validated as partially conforming to the concept of agility. Conclusions: This work makes a novel contribution to knowledge in identifying the first set of agile values in breast cancer treatment through multidisciplinary research. Three of these values were evaluated as conforming to the concept of agility, and although 1 value did not meet the concept of agility, it enhanced the agility of the other values. It is anticipated that these 4 agile values can drive oncology practice, strategies, policies, protocols, and procedures to enhance delivery of care. Moreover, the identified values contribute to identifying quality assurance and control practices to assess the concept of agility in oncology practice and breast cancer treatment and adjust corresponding actions. We conclude that breast cancer treatment agile values are not limited to 4. International Registered Report Identifier (IRRID): RR1-10.2196/53124

Purpose: The current state of the art in process modeling of blood banking and transfusion services is not well grounded; methodological reviews are lacking to bridge the gap between such blood banking and transfusion processes (and their models) and their automation. This research aims to fill this gap with a methodological review. Methods: A systematic mapping study was adopted, driven by five key research questions. Identified research studies were accepted based on fulfilling the following inclusion criteria: 1) research studies should focus on blood banking and transfusion process modeling since the late 1970s; and 2) research studies should focus on process automation in relation to workflow-based systems, with papers classified into categories in line with the analysis undertaken to answer each of the research questions. Results: The search identified 22 papers related to modeling and automation of blood banking and transfusion, published in the period 1979– 2022. The findings revealed that only four process modeling languages were reported to visualize process workflows. The preparation of blood components, serologic testing, blood distribution, apheresis, preparation for emergencies, maintaining blood banking and transfusion safety, and documentation have not been reported to have been modeled in the literature. This review revealed the lack of use of Business Process Modeling Notation (BPMN) as the industry standard process modeling language in the domain. The review also indicated a deficiency in modeling specialized processes in blood banking and transfusion, with the majority of reported processes being described as high level, but lacking elaboration. Automation was reported to improve transfusion safety, and to reduce cost, time cycle, and human errors. Conclusion: The work highlights the non-existence of a developed process architectural framework for blood banking and transfusion processes, which is needed to lay the groundwork for identifying and modeling strategic, managerial, and operational processes to bridge the gap with their enactment in healthcare systems. This paves the way for the development of a data-harvesting platform for blood banking and transfusion services.

Purpose: The complex nature of breast cancer demands flexible and adaptable principles that can account for the diverse characteristics and evolving conditions of each patient. However, there are no common breast cancer treatment agility principles that can influence policies and direct breast cancer professionals and healthcare providers into enhancing the delivery of health outcomes to patients under these conditions along with continuous rapid improvements in breast cancer treatment plan design. The incorporation of agile principles from software engineering offers a promising avenue for enhancing patient care. This research is conducted to identify breast cancer treatment agility principles adopted from the software engineering field and to validate their conformance to agility through work reported from literature in breast cancer treatment context. Material and Methods: The authors applied a structured research methodology that involved interviews for eliciting and validating twelve agility principles from oncologists. Discussion of each principle is reflected using work reported from literature as a form of validation. Finally, a domain expert reviewed the literature-driven validation for each of the twelve identified breast cancer treatment agile principle to finally validate their conformance to agility and provide results. Results: This work resulted twelve validated agility principles for breast cancer treatment and classified whether they are meeting, partially-(hybrid), or not meeting agility. Seven out of the twelve agile principles resulted as meeting agility, where the remaining five principles resulted as partially meeting agility. None of them is recorded as not meeting agility. Conclusion: The work contributes to forming an agile mindset that can empower breast cancer professionals to optimize treatment plans, enhance patient experiences, and continuously improve the quality of care. The twelve identified agile principles are anticipated to contribute to driving more efficient oncology practices, policies, and protocols. It is concluded that the breast cancer treatment agility principles are not limited to twelve.

Introduction: Evidence-based practice is a problem-based solving approach to clinical practice that encourages nurses providing personalized patient care while utilizing the necessary scientific evidence for a better understanding of risks and benefits of diagnostic tests and treatments. Digital transformation of an organization begins with attaining an acceptable digital readiness level. One approach entails specifying and modeling their processes and the respective data models. Objectives: In Jordan, at King Hussein Cancer Center—an international and regional accredited cancer care hospital—their nursing practice requires obtaining a standardized specification of evidence-based practice processes and their respective conceptual data model that is currently not specified for digital readiness. Methods: The design science research methodology was adopted to deliver two increments. The first was concerned with the design, development, and demonstration of eight evidence-based practice processes specified using BPMN. The second was related to the design and development, demonstration, and evaluation of a respective derived data model of the case study. Both increments involved interviews with domain experts for elicitation and validation. Results: Eight evidence-based practice process models were identified and specified using BPMN along with their associated data models, where one representative process model was utilized in this research to demonstrate the effectiveness of process and data modeling towards digital readiness of evidence-based practice in regional cancer center. Conclusions: Both deliverables enabled the evidence-based practice management to attain common understanding to identify inefficiencies, redundancies, and areas for improvement that can be addressed through digital solutions. Evidence -based practice BPMN process models were considered as a road map to follow up a project implementation and a rich visualization to perform data analytics to identify evidence-based practice trends, patterns, and insights that can inform strategic data-driven decisions. Both deliverables were concluded necessary for developing respective information systems in the journey towards digital transformation.