Ethics Certification of Health Information Professionals

Telemedicine and Telementoring in Urology: A Glimpse of the Past and a Leap Into the Future

Telemedicine is the process of utilizing telecommunications and digital relay to perform, teach, or share medical knowledge. The digital era eased the incorporation of telemedicine to different areas of medical care, including the surgical care of Urologic patient mainly through telementoring, telesurgery, and telerobotics. Over the years, Telemedicine has played an integral part in a physicians' ability to provide high quality medical care to remote patients, as well as serve as an educational tool for trainee physicians, in the form of telementoring. During the COVID-19 pandemic, telemedicine has played a vital role in combatting the health implications of confinements. Challenges of telemedicine implementation include cost, ethical considerations, security, bandwidth, latency, legal, and licensure difficulties. Nevertheless, the future of telemedicine, specifically telementoring, promises several improvements and innovative advancements that aim to bridge the gap in technological divides of urologic care. In this review, we build on what is already known about telemedicine focusing specifically on aspects related to telementoring, telestration, and telesurgery. Furthermore, we discuss its historical role in healthcare with a special emphasis on current and future use in urology.

Teasing out Artificial Intelligence in Medicine: An Ethical Critique of Artificial Intelligence and Machine Learning in Medicine

The rapid adoption and implementation of artificial intelligence in medicine creates an ontologically distinct situation from prior care models. There are both potential advantages and disadvantages with such technology in advancing the interests of patients, with resultant ontological and epistemic concerns for physicians and patients relating to the instatiation of AI as a dependent, semi- or fully-autonomous agent in the encounter. The concept of libertarian paternalism potentially exercised by AI (and those who control it) has created challenges to conventional assessments of patient and physician autonomy. The unclear legal relationship between AI and its users cannot be settled presently, an progress in AI and its implementation in patient care will necessitate an iterative discourse to preserve humanitarian concerns in future models of care. This paper proposes that physicians should neither uncritically accept nor unreasonably resist developments in AI but must actively engage and contribute to the discourse, since AI will affect their roles and the nature of their work. One's moral imaginative capacity must be engaged in the questions of beneficence, autonomy, and justice of AI and whether its integration in healthcare has the potential to augment or interfere with the ends of medical practice.

Telemedicine Practice: Review of the Current Ethical and Legal Challenges

Background: Telemedicine involves medical practice and information and communications technology. It has been proven to be very effective for remote health care, especially in areas with poor provision of health facilities. However, implementation of these technologies is often hampered by various issues. Among these, ethical and legal concerns are some of the more complex and diverse ones. In this study, an analysis of scientific literature was carried out to identify the ethical and legal challenges of telemedicine. Materials and Methods: English literature, published between 2010 and 2019, was searched on PubMed, Scopus, and Web of Science by using keywords, including "Telemedicine," "Ethics," "Malpractice," "Telemedicine and Ethics," "Telemedicine and Informed consent," and "telemedicine and malpractice." Different types of articles were analyzed, including research articles, review articles, and qualitative studies. The abstracts were evaluated according to the selection criteria, using the Newcastle-Ottawa Scale criteria, and the final analysis led to the inclusion of 22 articles. Discussion: From the aforementioned sample, we analyzed elements that may be indicative of the efficacy of telemedicine in an adequate time frame. Ethical aspects such as informed consent, protection data, confidentiality, physician's malpractice, and liability and telemedicine regulations were considered. Conclusions: Our objective was to highlight the current status and identify what still needs to be implemented in telemedicine with respect to ethical and legal standards. Gaps emerged between current legislation, legislators, service providers, different medical services, and most importantly patient interaction with his/her data and the use of that data.

Designing a model of professional ethics excellence for clinical librarians

Objective:

Developing and promoting professional ethics principles for clinical librarians can help the health care system balance the interests of all stakeholders, including clinical librarians, health care professionals, and patients. Therefore, the goal of this study was to design a model of professional ethics excellence for clinical librarians.

Methods:

The authors conducted a descriptive applied study using literature review and the delphi method. The delphi panel included eleven experts in medical librarianship, library and information sciences, or information sciences and knowledge studies.

Results:

After the delphi rounds, five concepts and forty-six components were identified and confirmed to provide a model of professional ethics excellence for clinical librarians. The highest-rated concept was excellence in communication. The highest-rated component was mastery in developing search strategies in information resources and databases.

Conclusions:

Identifying and applying principles of professional ethics among clinical librarians can enhance the professionalization of clinical librarians and result in better information services for physicians. Furthermore, incorporating these principles into the curriculum for health sciences library and information sciences students or into workshops for active clinical librarians can further formalize the profession and practice of evidence-based medicine.

The ethics of AI in health care: A mapping review

This article presents a mapping review of the literature concerning the ethics of artificial intelligence (AI) in health care. The goal of this review is to summarise current debates and identify open questions for future research. Five literature databases were searched to support the following research question: how can the primary ethical risks presented by AI-health be categorised, and what issues must policymakers, regulators and developers consider in order to be 'ethically mindful? A series of screening stages were carried out-for example, removing articles that focused on digital health in general (e.g. data sharing, data access, data privacy, surveillance/nudging, consent, ownership of health data, evidence of efficacy)-yielding a total of 156 papers that were included in the review. We find that ethical issues can be (a) epistemic, related to misguided, inconclusive or inscrutable evidence; (b) normative, related to unfair outcomes and transformative effectives; or (c) related to traceability. We further find that these ethical issues arise at six levels of abstraction: individual, interpersonal, group, institutional, and societal or sectoral. Finally, we outline a number of considerations for policymakers and regulators, mapping these to existing literature, and categorising each as epistemic, normative or traceability-related and at the relevant level of abstraction. Our goal is to inform policymakers, regulators and developers of what they must consider if they are to enable health and care systems to capitalise on the dual advantage of ethical AI; maximising the opportunities to cut costs, improve care, and improve the efficiency of health and care systems, whilst proactively avoiding the potential harms. We argue that if action is not swiftly taken in this regard, a new 'AI winter' could occur due to chilling effects related to a loss of public trust in the benefits of AI for health care.