Understanding Provider Perspectives: Catalysts and Challenges of Intelligent Clinical Decision Support Systems

The study aims to understand the providers\u27 perspectives of Intelligent Clinical Decision Support Systems (ICDSS). Providers are the key users of ICDSS. ICDSS uptake is heavily reliant on providers. However, providers have a powerful sense of personal identity due to their prestige, high autonomy, and socially accepted role. Currently, providers are resisting ICDSS. ICDSS resistance is due to poor fit with workflow, lack of relevant output and usefulness, insensitivity to complex patients, autonomy challenges, and an impact on the provider-patient relationship. Recently, researchers have overlooked the providers\u27 contextual perspectives of ICDSS. The study addressed the research gap by understanding the providers\u27 perspectives on their experiences, the ICDSS clinical utility, and the providers\u27 adaptation to the ICDSS. No known research exists explaining a comprehensive understanding of the providers\u27 perspectives of ICDSS. Therefore, this research study empirically investigated the providers\u27 perspectives to lay the foundation for tailoring ICDSS to providers\u27 unique needs and preferences. As a result, provider satisfaction and patient care will improve. The study used Grounded Theory as an overarching methodology for our qualitative case study research. Semi-structured interviews were used to gather the providers\u27 narrative data. The researcher transcribed the interview data and further refined it by comparing the text data to the audio recording data. The researcher analyzed the transcribed data using open coding. Further analysis identified catalysts and challenges for ICDSS. The ICDSS catalysts facilitated medical search, improved task efficiency, leveraged data-driven intelligence, provided transparent and reliable recommendations, improved treatment choices, prevented adverse events, supported their diagnosis process, promoted personalized training, promoted team dialogue, and improved technical literacy. The challenges of the ICDSS included contributing to cognitive overload, data quality issues, inflexibility, dehumanization of the patient-provider interaction, diminishing provider autonomy, increasing workload through compliance requirements, misalignment with their workflow, increasing AI anxiety, challenging to learn, and a resistance to change. The researcher grouped the focused codes into provider experiences, clinical utility, and adaptation. These were the categories of the ICDSS-Diagnostic Perspective Model (ICDSS-DPM). The ICDSS-DPM proposed six propositions that indicated the providers\u27 perspectives of ICDSS

GENERATIVE ADVERSARIAL NETWORKS IN TUMOR-RELATED RESEARCH: A REVIEW AND AGENDA FOR MOVING FORWARD

Recent advances in Generative Adversarial Networks (GANs) have led to many new variants and uses of GANs. The latest advancements have allowed researchers and practitioners to apply this technique to tumor-related problems with limited data. One of the trends in this problem domain is to develop different variants of GANs suited explicitly to particular problems. The variants of GANs are numerous but share a common characteristic of expanding the dataset by creating synthetic data from the original dataset. This paper aims to develop a research agenda through a systematic literature review that investigates practitioners\u27 and researchers\u27 emerging issues and current works on the topic. Emerging implementation trends and limitations of GANs in tumor-related problems are explored

General Adversarial Networks in Tumor-related Research: A Review and Agenda for Moving Forward

Recent advances in Generative Adversarial Networks (GANs) have led to many new variants and uses of GANs. The latest advancements have allowed researchers and practitioners to apply this technique to tumor-related problems with limited data. One of the trends in this problem domain is to develop different variants of GANs suited explicitly to particular problems. The variants of GANs are numerous but share a common characteristic of expanding the dataset by creating synthetic data from the original dataset. This paper aims to develop a research agenda through a systematic literature review that investigates practitioners\u27 and researchers\u27 emerging issues and current works on the topic. Emerging implementation trends and limitations of GANs in tumor-related problems are explored

The Evolving Civil Justice Reform Movement: Procedural Reforms Have Gained Steam, but Critics Still Focus on Arguments of the Past

Symposium issue: Tort Refor

How can Health Technology Project Communications be Improved in a Hospital

Healthcare professionals have had many challenges related to communication. Some of these challenges are related to health information technology, project management, and change management. This research addresses facilitators and barriers that healthcare providers have encountered in projects completed at the survey site. The integration of technology to support interdisciplinary teams transitioning to patient centered care requires enhanced focus on Project Communication as a key component of successful Health Information Technology (HIT) projects. Professional and organizational cultures in health care must transform to promote improved patient care

Ending an Internet Auction: Is eBay\u27s Approach Optimal?

Internet auctions can be ended in different ways. EBay auctions, for example, end at a predetermined time while Amazon auctions do not. The auctions at Amazon are extended by ten minutes if a bid is submitted within the last ten minutes of an auction. EBay’s hard closing rule induces bidding strategies that can produce inefficient results. Nevertheless, a hard close ending rule is more efficient than the automatic extension rule used by Amazon. EBay’s hard closing rule can be modified to resemble a Vickrey second-price auction. The modifications would make auctions on eBay more efficient

A Design Theory for Intelligent Clinical Decision Support

Poor or inadequate design of intelligent clinical decision support systems (ICDSS) can result in low adoption and use of these systems. These are some of the prevalent factors stimulating physician resistance. This resistance facilitates low physician involvement and creates a lack of trust in these systems. This is addressed through the development of a design theory for ICDSS. This is demonstrated through mapping and identifying extant literature in the context of the socio-technical model (STM). The gaps were identified through the relationships of the STM and developed into characteristics that are translated into meta-requirements informing design principles. The primary result of this research includes a design theory for ICDSS development. The developed design theory motivates and enables efficient ICDSS development, physician adoption, and more effective patient care. The design theory will also provide managers and researchers deeper insight into designing ICDSS to further improve physician adoption and use of ICDSS

PEOPLE, PROCESS, AND TECHNOLOGY IN CLINICAL DECISION SUPPORT SYSTEMS: A META-ANALYSIS

Artificial Intelligence (AI) techniques assist clinicians and physicians in making more effective and well-informed decisions for their patients. Clinical decision support systems (CDSS) offer extreme promise for integrating AI into the healthcare industry. To learn and extend the work done by researchers in the past, this research presents a meta-analysis of literature reviews focusing on acceptance, adoption, avoidance, and resistance of CDSS. The investigation spanned various academic databases from January 2016 to April 2021. A conceptual model guided the classification of literature into the dimensions of People, Process, and Technology. The analysis revealed the range and evolution of research relating to CDSS and clarifies trends for practitioners and Information Systems (IS) researchers. The study concludes with recommendations to further advance CDSS acceptance, adoption, avoidance, and resistance by focusing on the People, Process, and Technology dimensions. We found that 1) technology has been identified as the main component in the studies more often than people and process and 2) adoption and acceptance have been constructed as the focus of the theoretical frameworks much more than avoidance and resistance

What are Healthcare Providers\u27 Perceptions of Health Information Technology Project Training?

Technological change in the healthcare environment provides opportunities to improve quality of care, increase patient satisfaction and reduce costs. However, employee training is seen as a major factor that influences the change management processes of healthcare projects. This research focuses on the healthcare providers’ perceptions of Health Information Technology project training. A qualitative survey was used to collect physicians’ and healthcare provider responses. Open coding was used to analyze the data. Our findings reveal that the physicians and healthcare providers are not satisfied with the Health Information Technology project training. From the analysis, we identify five categories that influence user training