Bribing doctors for preferential treatment is rampant in the healthcare system of developing countries like Vietnam. Although bribery raises the out-of-pocket expenditures of patients, it is so common to be deemed an “envelope culture.” Given the little understanding of the underlying mechanism of the culture, this study employed the mindsponge theory for reasoning the mental processes of both patients and doctors for why they embrace the “envelope culture” and used the Bayesian Mindsponge Framework (BMF) analytics to validate our reasoning. (...) Analyzing responses from 1042 Vietnamese patients, we discovered that bribing doctors can help patients reduce the destitution risk induced by treatment. Such effect of doctor bribery remains consistent among patients that have to pay high daily costs (e.g., accommodation and subsistence fees) regardless of their employment status. Nevertheless, for patients with no or unstable jobs, their risks of destitution increase if they have to pay more thank-you money. These findings suggest that doctor bribery is an adaptive strategy for patients in an environment where the healthcare supply cannot meet the actual demand. Moreover, healthcare equity is greatly exacerbated due to the envelope culture, as vulnerable individuals are exposed to a greater threat of poverty. At the same time, those with good economic conditions get preferential treatment by paying a higher amount of thank-you money. Healthcare workers’ ethics must be the top priority for an equitable and proper healthcare system. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics (...) and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. (shrink)

In a rigorous systematic review, Dukhanin and colleagues categorize metrics and evaluative tools of the engagement of patient, public, consumer, and community in decision-making in healthcare institutions and systems. The review itself is ably done and the categorizations lead to a useful understanding of the necessary elements of engagement, and a suite of measures relevant to implementing engagement in systems. Nevertheless, the question remains whether the engagement of patient representatives in institutional or systemic deliberations will lead to (...) improved clinical outcomes or increased engagement of individual patients themselves in care. Attention to the conceptual foundations of patient engagement would help make this systematic review relevant to the clinical care of patients. (shrink)

The objective of this article is to shed light on some challenging questions regarding public health and medical ethics that the Turkish healthcare system has recently been forced to confront. In recent years, terrorists in eastern Turkey have launched increasingly destructive attacks, including numerous attempts to undermine the social order by targeting not only government agencies but also the healthcare system. In this study, 54 terrorist incidents specifically targeting the Turkish healthcare system and healthcare professionals were (...) analyzed and divided into 6 categories according to the type of attack. Each category was evaluated in terms of the relevant ethical issues, with regard to both public health and medical ethics. This study shows that terrorist activity may lead to numerous breaches of public health and clinical ethics rules. Therefore, healthcare policy must involve special precautions to minimize breaches of public health and medical ethics in the face of terrorist attacks. (shrink)

The objective of this article is to shed light on some challenging questions regarding public health and medical ethics that the Turkish healthcare system has recently been forced to confront. In recent years, terrorists in eastern Turkey have launched increasingly destructive attacks, including numerous attempts to undermine the social order by targeting not only government agencies but also the healthcare system. In this study, 54 terrorist incidents specifically targeting the Turkish healthcare system and healthcare professionals were (...) analyzed and divided into 6 categories according to the type of attack. Each category was evaluated in terms of the relevant ethical issues, with regard to both public health and medical ethics. This study shows that terrorist activity may lead to numerous breaches of public health and clinical ethics rules. Therefore, healthcare policy must involve special precautions to minimize breaches of public health and medical ethics in the face of terrorist attacks. (shrink)

It has been argued that ethical frameworks for data science often fail to foster ethical behavior, and they can be difficult to implement due to their vague and ambiguous nature. In order to overcome these limitations of current ethical frameworks, we propose to integrate the analysis of the connections between technical choices and sociocultural factors into the data science process, and show how these connections have consequences for what data subjects can do, accomplish, and be. Using healthcare as an (...) example, attention to sociocultural conversion factors relevant to health can help in navigating technical choices that require broader considerations of the sociotechnical system, such as metric tradeoffs in model validation, resulting in better ethical and technical choices. This approach promotes awareness of the ethical dimension of technical choices by data scientists and others, and that can foster the cultivation of 'ethical skills' as integral to data science. (shrink)

In Bulgaria, integrating technology and innovation is crucial for advancing sustainable healthcare disaster management, enhancing disaster response and recovery, and minimizing long-term environmental and social impacts. The purpose of the study is to assess the impact of modern technological innovations on the effectiveness of disaster management in health care in Bulgaria with a focus on Health Information Systems (HIS), Telemedicine, Telehealth, e-Health, Electronic Health Records, Artificial Intelligence (AI), Public Communication Platforms, and Data Security and Privacy. These innovations, when (...) integrated effectively, can significantly strengthen Bulgaria's preparedness and response capabilities, improving efficiency and reducing the environmental footprint of disaster interventions. Collaboration with technology experts, research institutions, and international organizations is essential for successful implementation. The research aims to assess how these technologies can enhance disaster management efficacy, adopting a methodical approach using Systematic Literature Reviews (SLRs). Systematic Literature Reviews (SLRs) utilize precise criteria for research selection and evaluation to reduce bias, systematically compiling and analyzing data from various studies to offer evidence-based insights. They are crucial for uncovering research gaps, indicating areas needing further exploration. Findings highlight the transformative potential of technology integration in streamlining communication, data management, and operational efficiency. The study underscores the urgent need for an integrated approach and a culture of innovation within the healthcare sector, emphasizing ongoing assessment and adaptation of technology-based strategies. While acknowledging limitations and calling for further research, the study provides valuable insights into Bulgaria's healthcare disaster management strategies and sets the stage for future investigations to refine and expand upon these strategies. It advocates for a strategic framework guiding the efficient integration of technology into disaster management, aiming for resilient and patient-centric healthcare systems. (shrink)

Self-tracking-technologies can serve as a prominent example of how digital technologies put to test established practices, institutions, and structures of medicine and healthcare. While proponents emphasize the potentials, e.g., for individualized healthcare and new research data, opponents stress the risk that these technologies will reinforce gender-related inequalities. -/- While this has been made clear from—often intersectional—feminist perspectives since the introduction of such technologies, we aim to provide a queer-feminist perspective on self-tracking applications in healthcare by analyzing three (...) concrete cases. In this way, we want to show why such a perspective is helpful in assessing self-tracking technologies and how such a perspective might contribute to a queering of healthcare. -/- After a short introduction to self-tracking in healthcare and the corresponding risks of reproducing gender-related inequalities, we introduce queer bioethics as a methodology to examine structural discrimination and marginalization in bioethical research. We apply this framework in the analysis of three exemplary self-tracking applications from the areas of nutrition/fitness, reproductive health, and mental health. In the subsequent discussion of these results against the backdrop of already existing queer-sensitive technologies, we identify an equal access, a subversive design, an inclusive database, and a diversity-sensitive and discriminatory-critical definition of purposes as well as individualized usage possibilities as first possible starting points for a queering of self-tracking applications. Finally, we draw conclusions, how such a critical perspective on self-tracking applications might also contribute to a queering of the healthcare system at a structural level. (shrink)

Trans healthcare and thus trans people have been severely affected by the COVID-19 pandemic. Trans people’s healthcare situations have turned out to be so vulnerable in this crisis because they have been precarious to begin with. There are multiple ways in which trans healthcare has been affected: Surgeries and other procedures have been cancelled or postponed, and mental health services have been paused or moved online. This raises ethical questions around discrimination against trans people in the (...) class='Hi'>healthcare system. This article argues that cancelling trans surgeries and procedures in the COVID-19 crisis is made possible through an understanding of trans healthcare as non-essential. The article explores how trans healthcare in particular has been affected by the pandemic. (shrink)

Chile has achieved great success in terms of growth and development. However, growing inequalities exist in relation to income and health status. The previous Chilean government began to reform the healthcare system with the aim of reducing health inequities. What is meant by “equity” in this context? What is the extent of the equity aimed for? A normative framework is required for public policy-makers to consider ideas about fairness in their decisions about healthcare reform. This paper aims to (...) discuss the main features of the Chilean healthcare reform and their implications for such a normative framework. (shrink)

This article highlights the limitations of the tendency to frame health- and wellbeing-related digital tools (mHealth technologies) as empowering devices, especially as they play an increasingly important role in the National Health Service (NHS) in the UK. It argues that mHealth technologies should instead be framed as digital companions. This shift from empowerment to companionship is advocated by showing the conceptual, ethical, and methodological issues challenging the narrative of empowerment, and by arguing that such challenges, as well as the risk (...) of medical paternalism, can be overcome by focusing on the potential for mHealth tools to mediate the relationship between recipients of clinical advice and givers of clinical advice, in ways that allow for contextual flexibility in the balance between patiency and agency. The article concludes by stressing that reframing the narrative cannot be the only means for avoiding harm caused to the NHS as a healthcare system by the introduction of mHealth tools. Future discussion will be needed on the overarching role of responsible design. (shrink)

In this paper, I aim to demonstrate that the consequences of the current United States health insurance scheme on both physician and patient autonomy is dire. So dire, in fact, that the only moral solution is something other than what we have now. The United States healthcare system faces much criticism at present. But my focus is particular: I am interested in the ways in which insurance interferes with physician and patient autonomy. I will argue in favor of an (...) expansion of the traditional conception of what I call “medical autonomy” or “healthcare autonomy” and the usual role it plays in bioethical discussions. More generally, I show that in morally designing or evaluating any healthcare system, serious attention should be paid to how this system helps foster what I call active autonomy. (shrink)

If we are to develop efficient, reliable and secure means for sharing information across healthcare systems and organizations, then a careful analysis of human actions will be needed. To address this need, the HL7 organization has proposed its Reference Information Model (RIM), which is designed to provide a comprehensive representation of the entire domain of healthcare centered around the phenomenon of human action. Taking the Basic Formal Ontology as our starting point, we examine the RIM from an (...) ontological point of view, describing how it fails to provide a representation of the healthcare domain which would enjoy the sort of clarity, coherence, rigor and completeness that is claimed on its behalf. (shrink)

Within the last decade, epistemic injustice has been a valuable framework for those working on exposing oppressive practices within the healthcare system. As this work has evolved, new terminology has been added to the epistemic injustice literature to bring to light previously obscured epistemic harms in healthcare practices. This paper aims to explore an important concept that has not received the attention it deserves: epistemic isolation. By developing Ian Kidd and Havi Carel’s concept of epistemic isolation, a new (...) range of epistemic harms are brought to the fore, as some of the most marginalised in our society are forced to operate from positions of ignorance. In the words of Kidd and Carel, epistemic isolation occurs in ‘situations where a person or group lacks the knowledge of, or means of access to, particular information; for instance, if they live within a politically repressive society which forbids access to the necessary sources of information in order to protect the government’s hegemony’ (183–184). This paper will demonstrate that such epistemic isolation is uniquely devastating for those with psychiatric illness, exacerbating their already challenging circumstances. (shrink)

Most people are completely oblivious to the danger that their medical data undergoes as soon as it goes out into the burgeoning world of big data. Medical data is financially valuable, and your sensitive data may be shared or sold by doctors, hospitals, clinical laboratories, and pharmacies—without your knowledge or consent. Medical data can also be found in your browsing history, the smartphone applications you use, data from wearables, your shopping list, and more. At best, data about your health might (...) end up in the hands of researchers on whose good will we depend to avoid abuses of power.2 Most likely, it will end up with data brokers who might sell it to a future employer, or an insurance company, or the government. At worst, your medical data may end up in the hands of criminals eager to commit extortion or identity theft. In addition to data harms related to exposure and discrimination, the collection of sensitive data by powerful corporations risks the creation of data monopolies that can dominate and condition access to health care. -/- This chapter aims to explore the challenge that big data brings to medical privacy. Section I offers a brief overview of the role of privacy in medical settings. I define privacy as having one’s personal information and one’s personal sensorial space (what I call autotopos) unaccessed. Section II discusses how the challenge of big data differs from other risks to medical privacy. Section III is about what can be done to minimise those risks. I argue that the most effective way of protecting people from suffering unfair medical consequences is by having a public universal healthcare system in which coverage is not influenced by personal data (e.g., genetic predisposition, exercise habits, eating habits, etc.). (shrink)

Abstract: Artificial Intelligence (AI) is rapidly becoming a cornerstone of modern healthcare, offering unprecedented capabilities in diagnostics, treatment planning, patient care, and healthcare management. This paper explores the transformative impact of AI on the healthcare sector, examining how it enhances patient outcomes, improves the efficiency of medical practices, and introduces new ethical and operational challenges. By analyzing current applications such as AI-driven diagnostic tools, personalized medicine, and hospital management systems, this paper highlights the significant advancements AI (...) has brought to the field. However, the integration of AI also raises concerns related to data privacy, algorithmic bias, and the displacement of healthcare professionals. This study provides a comprehensive overview of these developments, offering insights into the future potential of AI in revolutionizing healthcare while addressing the ethical considerations that must accompany its adoption. The findings suggest that while AI holds the promise of transforming healthcare delivery, careful consideration of its implications is essential to ensure equitable and effective implementation. (shrink)

Semantic interoperability can be defined as the ability of two or more computer systems to exchange information in such a way that the meaning of that information can be automatically interpreted by the receiving system accurately enough to produce useful results to the end users of both systems. Several activities are currently being performed by a variety of stakeholders to achieve semantic interoperability in healthcare. Many of these activities are not beneficial, because they place too great a (...) focus on business aspects and not enough on involvement of the right sorts of researchers, in particular those that are able to see how the data and information relate to the entities of concern on the side of the patient. The lack of a central focus on the patient, and the associated focus on ‘concepts’, have spawned a variety of mutually incompatible terminologies exhibiting non-resolvable overlap. The predominance of the healthcare IT industry in the writing and selection of semantic interoperability standards mitigates against the benefits that standards, when well designed, can bring about. (shrink)

AI systems, like self-driving cars, healthcare robots, or Autonomous Weapon Systems, already play an increasingly important role in our lives and will do so to an even greater extent in the near future. This raises a fundamental philosophical question: who is morally responsible when such systems cause unjustified harm? In the paper, we argue for the admittedly surprising claim that some of these systems can themselves be morally responsible for their conduct in an important and (...) everyday sense of the term—the attributability sense. More specifically, relying on work by Nomy Arpaly and Timothy Schroeder (In Praise of Desire, OUP 2014), we propose that the behavior of these systems can manifest their ‘quality of will’ and thus be regarded as something they can be blameworthy for. We develop this position in detail, justify some of its crucial presuppositions, and defend it against potential objections. (shrink)

The medical use of computing and information and communication technologies (ICTs) has a history of several decades, but the emergence of the internet, and especially the web and social media, created a new situation. As a result, currently the term eHealth is widely used – and the usage of the internet (and mobile) “technologies” in healthcare (among the patients and professionals, too) tends to be usual practice. There are more and more signs of the institutionalization of this new sub-disciplinary (...) field of medicine, such as social organizations, healthcare institutes, scientific journals, regular conferences, etc. In this paper, collecting the most relevant developments we will try to characterize this state of affairs in the field. Moreover, as it is well-known, the use of the internet has an enormous impact on society, social systems and subsystems, and even on the everyday life of people. This extended practice also influences medicine and healthcare as social subsystems, and fundamentally transforms some of their characteristics. In this paper, we try to show several important dimensions of these changes. (shrink)

Traditional medical practices and relationships are changing given the widespread adoption of AI-driven technologies across the various domains of health and healthcare. In many cases, these new technologies are not specific to the field of healthcare. Still, they are existent, ubiquitous, and commercially available systems upskilled to integrate these novel care practices. Given the widespread adoption, coupled with the dramatic changes in practices, new ethical and social issues emerge due to how these systems nudge users into (...) making decisions and changing behaviours. This article discusses how these AI-driven systems pose particular ethical challenges with regards to nudging. To confront these issues, the value sensitive design approach is adopted as a principled methodology that designers can adopt to design these systems to avoid harming and contribute to the social good. The AI for Social Good factors are adopted as the norms constraining maleficence. In contrast, higher-order values specific to AI, such as those from the EU High-Level Expert Group on AI and the United Nations Sustainable Development Goals, are adopted as the values to be promoted as much as possible in design. The use case of Amazon Alexa's Healthcare Skills is used to illustrate this design approach. It provides an exemplar of how designers and engineers can begin to orientate their design programs of these technologies towards the social good. (shrink)

The paper discusses the possibility that the benefits of pharmacogenomics will not be distributed equally and will create orphan populations. I argue that since these inequalities are not substantially different from those produced by ‘traditional’ drugs and are not generated with the intention to discriminate, their production needs not be unethical. Still, the final result is going against deep-seated moral feelings and intuitions, as well as broadly accepted principles of just distribution of health outcomes and healthcare. I thus propose (...) two provisos that would prevent the most offensive outcomes and moderate the scope of the produced inequalities. The first proviso rejects pharmacogenomics innovations that worsen existing group inequalities and aggravate the disadvantage of communities with a history of discrimination. The second proviso requires that there is a strategy in place to even out as much as possible the distribution of benefits in the future and that a system of compensations is in place for pharmacogenomic orphans. Given that only one moral problem generated by pharmacogenomics has been tackled, the list of provisos might be expanded when other issues are considered. (shrink)

Results indicate substantial improvements in efficiency, accuracy, and personalized care, but also highlight the challenges of data privacy, ethical considerations, and system scalability. By providing a structured analysis, this research contributes insights into optimizing generative AI deployments for both banking and healthcare, ensuring a balance between innovation and risk management. The study concludes with recommendations for future research directions, including advanced model training, ethical guidelines, and enhanced privacy measures. These insights aim to inform practitioners on the benefits of generative (...) AI, ensuring sustainable integration into banking and healthcare ecosystems. (shrink)

The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient (...) needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

Lung cancer is a serious and deadly disease that affects the lungs, which are responsible for taking in oxygen and expelling carbon dioxide from the body. The disease can develop in any part of the lungs and is usually caused by smoking or exposure to certain chemicals. The main Objective: of this expert system is to provide an accurate diagnosis of lung cancer and the appropriate treatment options. In this paper, Methods: we present the design and implementation of an expert (...) system that can assist physicians in diagnosing lung cancer and determining the best course of treatment. The system provides an overview of the disease, its causes, symptoms, diagnosis, and treatment, along with relevant medical information. Results: The system was developed using the Clips expert system language and evaluated by medical professionals who found it to be an effective tool for diagnosing and treating lung cancer. Conclusion: The proposed expert system has the potential to improve patient outcomes and reduce healthcare costs associated with the treatment of lung cancer. (shrink)

On 8th August 2019, Secretary of State for Health and Social Care, Matt Hancock, announced the creation of a £250 million NHS AI Lab. This significant investment is justified on the belief that transforming the UK’s National Health Service (NHS) into a more informationally mature and heterogeneous organisation, reliant on data-based and algorithmically-driven interactions, will offer significant benefit to patients, clinicians, and the overall system. These opportunities are realistic and should not be wasted. However, they may be missed (one may (...) recall the troubled Care.data programme) if the ethical challenges posed by this transformation are not carefully considered from the start, and then addressed thoroughly, systematically, and in a socially participatory way. To deal with this serious risk, the NHS AI Lab should create an Ethics Advisory Board and monitor, analyse, and address the normative and overarching ethical issues that arise at the individual, interpersonal, group, institutional and societal levels in AI for healthcare. (shrink)

The study highlights the advantages telemedicine offers, such as increased flexibility, reduced commuting time, and better time management. It also examines the challenges doctors face, including the demands of always being digitally accessible, the learning curve of new technologies, and the difficulty in maintaining boundaries between personal and professional life. Using both quantitative and qualitative data, this research compares the telemedicine adaptation experiences of doctors in public versus private hospitals, considering factors such as hospital infrastructure, support systems, and patient (...) load. (shrink)

A newborn baby is an infant within the first 28 days of birth. Diagnosis and treatment of infant diseases require specialized medical resources and expert knowledge. However, there is a shortage of such professionals globally, particularly in low-income countries. To address this challenge, a knowledge-based system was designed to aid in the diagnosis and treatment of neonatal diseases. The system utilizes both machine learning and health expert knowledge, and a hybrid data mining process model was used to extract knowledge from (...) a clinical dataset. The PART algorithm achieved the highest performance result with 98.06% accuracy under 10-fold cross-validation, and the generated rules were used to develop the knowledge-based system. The system achieved 90.9% accuracy in system performance testing and 89.2% in user acceptance testing, and is intended to serve as an assistant tool for healthcare experts. (shrink)

Brain tumors pose significant challenges in modern healthcare, with accurate and timely diagnosis crucial for determining appropriate treatment strategies. Artificial intelligence has made significant advancements in recent years. Rule-based expert systems (if-then rule-based systems) have emerged as a promising approach for clinical decision-making in brain tumor diagnosis. In this paper, we present "A CLIPS-Based Expert System for Brain Tumor Diagnosis," which leverages a set of 14 if-then rules to diagnose brain tumors with three possible outcomes: 1) Confirm (...) the diagnosis of a brain tumor, 2) Consider the possibility of a brain tumor that has metastasized, and 3) Consider the possibility of a brain tumor. Our expert system offers a user-friendly interface, enabling users to select symptoms and receive a diagnosis based on the provided information. This paper discusses the expert system's development, implementation, and evaluation, highlighting its potential to facilitate brain tumor diagnosis and decision-making in clinical settings. Additionally, we provide a literature review that contextualizes our expert system within the broader landscape of rule-based expert systems for brain tumor diagnosis, examining their effectiveness, limitations, and challenges. (shrink)

Vertigo is a common symptom that can result from various underlying diseases and conditions, ranging from benign to severe. Accurate and timely diagnosis of the cause of vertigo is crucial for appropriate management and treatment. In this research, we propose the development of an expert system for vertigo diseases diagnosis, utilizing artificial intelligence (AI) and the proposed Expert System which was produced to help assist healthcare professionals in diagnosing the cause of vertigo based on a patient's symptoms, medical history, (...) and other relevant clinical information. The proposed expert system presents an overview about vertigo diseases are given, the cause of disease is outlined and the treatment or recommendation of disease whenever possible is given out. CLIPS language was used for designing and implementing the proposed expert system. The potential of the proposed expert system lies in its ability to enhance the accuracy and efficiency of vertigo diagnosis, as well as assist in the proper referral and management of patients. (shrink)

Mouth ulcers, also known as canker sores, are a common oral health issue affecting a significant portion of the population. Early and accurate diagnosis of mouth ulcers is crucial for effective treatment and prevention of complications. This paper presents an expert system developed using CLIPS (C Language Integrated Production System) to diagnose mouth ulcer disease. The expert system utilizes a rule-based approach, incorporating a comprehensive knowledge base consisting of symptoms, risk factors, and medical literature related to mouth ulcers. By employing (...) an inference engine, the system evaluates patient input against the rules and generates a diagnosis based on the matching symptoms and relevant factors. The system also provides detailed explanations and recommendations for each diagnosis, aiding healthcare professionals and patients in understanding the condition and selecting appropriate treatment options. The development and validation of the expert system involved a multi-step process, including knowledge acquisition, rule formulation, and testing against a diverse dataset of mouth ulcer cases. The system's performance was evaluated by comparing its diagnoses with those made by medical professionals, demonstrating a high level of accuracy and consistency. The implementation of an expert system for diagnosing mouth ulcer disease offers several advantages, including the ability to provide timely and accessible healthcare services, reduce misdiagnosis rates, and assist healthcare professionals in decision-making processes. Moreover, it empowers individuals to make informed decisions about their health and seek appropriate medical intervention. This paper contributes to the field of medical expert systems by showcasing the practical application of CLIPS in the diagnosis of mouth ulcer disease. The results demonstrate the potential of expert systems as valuable tools for healthcare professionals and patients alike, enhancing the efficiency and accuracy of diagnosis in oral health care. (shrink)

Abstract: Colon cancer is a prevalent and life-threatening disease, necessitating accurate and timely diagnosis for effective treatment and improved patient outcomes. This research paper presents the development of a knowledge-based system for diagnosing colon cancer using the CLIPS language. Knowledge-based systems offer the potential to assist healthcare professionals in making informed diagnoses by leveraging expert knowledge and reasoning mechanisms. The methodology involves acquiring and structuring medical knowledge specific to colon cancer, followed by the implementation of a knowledge- based (...) system using CLIPS. The system's design integrates relevant medical databases and employs advanced reasoning mechanisms to facilitate accurate diagnosis. Evaluation results demonstrate the system's effectiveness, with high accuracy and sensitivity rates compared to existing methods. The findings highlight the potential of knowledge-based systems in improving clinical practice and patient care. The research contributes to the growing field of medical informatics by demonstrating the feasibility and effectiveness of CLIPS-based knowledge systems for colon cancer diagnosis. Future research can focus on enhancing system performance and expanding its scope to encompass other types of cancer diagnoses. (shrink)

The paper presents the outlines of an ontology of plans and guidelines, which is then used as the basis for a framework for implementing guideline-based systems for the management of workflow in health care organizations. The framework has a number of special features, above all in that it enables us to represent in formal terms assignments of work-items both to individuals and to teams and to tailor guideline to specific contexts of application in health care organizations. It is designed (...) also to enable implementations to do justice to the fact that the processes carried out in health care organizations may deviate in different ways from the norms set forth in corresponding guideline definitions. This means that implementations built in conformity with the framework will be marked by a type of flexibility that might make them more likely to be accepted by healthcare professionals than are standard guideline-based management systems. (shrink)

Warts and verrucas are common skin conditions caused by the human papillomavirus (HPV) infection. They present as raised, rough, or bumpy growths on the hands, feet, or other areas subjected to friction or pressure. Plantar warts exhibit a rough surface with small black dots, while genital warts have a cauliflower-like appearance. Pain or itchiness may accompany these lesions. Factors such as close contact with infected individuals and immune compromise can impact the severity and spread of warts. Diagnosis is primarily based (...) on clinical examination, and referral to a dermatologist may be necessary for uncertain cases. Treatment options range from over-the-counter remedies to professional interventions. Persistent or symptomatic lesions should be evaluated by a healthcare professional. Improved understanding and effective management of warts and verrucas are essential for optimal patient outcomes. (shrink)

The EdTech revolution in India has emerged as a transformative force, particularly during and after the COVID-19 pandemic, when traditional education systems faced unprecedented disruptions. While digital technologies have unlocked new opportunities for teaching and learning, they have also exposed systemic inequities and deepened the existing digital divide. This paper examines how EdTech is reshaping India's education landscape by addressing these challenges, with a focus on both the opportunities it presents and the barriers it creates.

Over the past year, technology companies have made headlines claiming that their artificially intelligent (AI) products can outperform clinicians at diagnosing breast cancer, brain tumours, and diabetic retinopathy. Claims such as these have influenced policy makers, and AI now forms a key component of the national health strategies in England, the United States, and China. While it is positive to see healthcare systems embracing data analytics and machine learning, concerns remain about the efficacy, ethics, and safety of some (...) commercial, AI health solutions. This paper argues that improved regulation and guidance is urgently required to mitigate risks, ensure transparency and best practice, Without this, patients, clinicians, and other stakeholders cannot be assured of an app’s efficacy, and safety. (shrink)

Abstract The values of the healthcare sector are fairly ubiquitous across the globe, focusing on caring and respect, patient health, excellence in care delivery, and multi-stakeholder collaboration. Many individual pharmacists embrace these core values. But their ability to honor these values is significantly determined by the nature of the system they work in. -/- The paper starts with a model of the prevailing pharmacist workforce model in Scotland, in which core roles are predominantly separated into hierarchically disaggregated jobs focused (...) on one professional ‘pillar’: Clinician /Practice Provider; Educator; Leader/Manager; and Researcher. This is the ‘Atomistic’ Model. This skills-segregation yields a workforce of individuals working in isolation rather than collaborating together, and lacking a shared information flow, purpose and identity. Key strategic flaws include suboptimal responsiveness to population and subpopulation needs, inconsistency and inequity of care, an erosion of professional agency, and lower job satisfaction. It is conjectured that this results from a lack of congruence between values, professional ethos, and organizational structure. ‘Atomism’ culminates in a syndrome of widespread professional-level cognitive dissonance. -/- The paper contrasts this with a new emerging workforce vision, The Collaborative Care Model. This new model defines a systems-first-approach, built on the principle that all jobs must include all four professional ‘pillars’. Vertical skills integration, involving education and task sharing, will support sustainability and succession planning. Horizontal skills integration (across practice, leadership and research) is included to improve responsiveness to population need and individual professional agency. The working conditions, supportive ethos, and career structure needed to make the model work are described. Moral theory and workforce theory are used to justify why the model may be more effective for population health, delivering greater job satisfaction for individuals and ultimately helping systematically realize and honor healthcare values. Finally, the paper sketches the first steps needed to implement the model at the national level, starting with the operationalization of new multi-pillar professional curricula across the career spectrum. Potential pitfalls and challenges are also discussed. -/- Co-Authors: 1. Paul Forsyth (PF) Lead Pharmacist Clinical Cardiology, Pharmacy, NHS Greater Glasgow & Clyde. Contribution: Conceptualization; Model Curation; Model Theory; Model Visualization; Writing - original draft (lead author), Writing - review & editing (lead author) 2. Andrew Radley (AR), Consultant in Public Health Pharmacy, NHS Tayside. Contribution: Conceptualization; Model curation; Model Theory; Writing - review & editing 3. Gordon Rushworth (GR), MPharm MSc FFRPS FRPharmS (Consultant). Programme Director, Highland Pharmacy Education & Research Centre, NHS Highland, Inverness. Contribution: Model curation; Writing - review & editing 4. Fiona Marra (FM) National Lead Clinician Scottish Infection and Immunology Network (SPAIIN) / Advanced Pharmacist HCV / HIV, NHS Greater Glasgow & Clyde. Contribution: Model curation; Writing - review & editing 5. Susan Roberts (SR) Associate Postgraduate Pharmacy Dean, NHS Education for Scotland. Contribution: Model curation; Writing - review & editing 6. Roisin O’Hare (RO) Lead Teacher Practitioner Pharmacist, Northern Ireland University Network, Southern Health and Social Care Trust. Contribution: Model curation; Writing - review & editing 7. Catherine Duggan (CD) Chief Executive Officer, International Pharmaceutical Federation (FIP). Contribution: Model curation; Writing - review & editing 8. Barry Maguire (BM) Senior Lecturer, School of Philosophy, Psychology and Life Sciences, The University of Edinburgh. Contribution: Conceptualization; Model Curation; Model Theory; Model Visualization; Supervision; Writing - original draft (senior academic supervisor), Writing - review & editing (senior academic supervisor) -/- . (shrink)

In this paper, we consider the role of conversations in contributing to healthcare quality improvement. More specifically, we suggest that conversations can be important in responding to what we call ’normative complexity’. As well as reflecting on the value of conversations, the aim is to introduce the dimension of normative complexity as something that requires theoretical and practical attention alongside the more recognised challenges of complex systems, which we label, for short, as ’explanatory complexity’. In brief, normative complexity (...) relates to the inherent difficulty of deciding what kinds of changes are ’improvements’ or, more broadly, what is valuable in healthcare. We suggest that explanatory and normative complexity intersect and that anyone interested in healthcare improvement needs to be sensitive to both. After briefly introducing the idea of normative complexity, we consider some contrasting examples of conversations, reflecting on how they do and might contribute to healthcare quality. We discuss both conversations that are deliberately organised and facilitated (’orchestrated conversations’) and more informally occurring and routine conversations. In the first half of the paper, we draw on some examples of orchestrated and routine conversations to open up these issues. In the second half of the paper, we bring some more theoretical lenses to bear on both conversations and normative complexity, summarise what we take to be the value of conversations and draw together some of the implications of our discussion. In summary, we argue that conversations can play a crucial role in negotiating the normative complexity of healthcare quality improvement because of their capacity to hold together a plurality of perspectives, to contribute and respond to emergence and to help underpin institutional conditions for empathy and imagination. (shrink)

This paper explores the implications of extended and distributed cognition theory for our notions of personal identity. On an extended and distributed approach to cognition, external information is under certain conditions constitutive of memory. On a narrative approach to personal identity, autobiographical memory is constitutive of our diachronic self. In this paper, I bring these two approaches together and argue that external information can be constitutive of one’s autobiographical memory and thus also of one’s diachronic self. To develop this claim, (...) I draw on recent empirical work in human-computer interaction, looking at lifelogging technologies in both healthcare and everyday contexts. I argue that personal identity can neither be reduced to psychological structures instantiated by the brain nor by biological structures instantiated by the organism, but should be seen as an environmentally-distributed and relational construct. In other words, the complex web of cognitive relations we develop and maintain with other people and technological artifacts partly determines our self. This view has conceptual, methodological, and normative implications: we should broaden our concepts of the self as to include social and artifactual structures, focus on external memory systems in the (empirical) study of personal identity, and not interfere with people’s distributed minds and selves. (shrink)

The proposed system combines predictive analytics and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization (...) tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

Diagnosing flatulence involves a thorough assessment of an individual's symptoms, medical history, and, if necessary, the use of diagnostic tests. Healthcare providers gather information about the patient's medical background and conduct a physical examination to identify any signs of gastrointestinal issues. Dietary habits are evaluated, and potential triggers are identified through an elimination diet. Diagnostic tests such as breath tests, stool analysis, or imaging studies may be performed to further investigate the underlying causes of excessive flatulence. Accurate diagnosis is (...) crucial for effective management and treatment of flatulence, enabling individuals to gain control over their symptoms and address any underlying conditions. (shrink)

Artificial intelligence systems have been widely applied to various contexts, including high-stake decision processes in healthcare, banking, and judicial systems. Some developed AI models fail to offer a fair output for specific minority groups, sparking comprehensive discussions about AI fairness. We argue that the development of AI systems is marked by a central paradox: the less participation one stakeholder has within the AI system’s life cycle, the more influence they have over the way the system will (...) function. This means that the impact on the fairness of the system is in the hands of those who are less impacted by it. However, most of the existing works ignore how different aspects of AI fairness are dynamically and adaptively affected by different stages of AI system development. To this end, we present a use case to discuss fairness in the development of corporate wellness programs using smart wearables and AI algorithms to analyze data. The four key stakeholders throughout this type of AI system development process are presented. These stakeholders are called service designer, algorithm designer, system deployer, and end-user. We identify three core aspects of AI fairness, namely, contextual fairness, model fairness, and device fairness. We propose a relative contribution of the four stakeholders to the three aspects of fairness. Furthermore, we propose the boundaries and interactions between the four roles, from which we make our conclusion about the possible unfairness in such an AI developing process. (shrink)

Perioperative staff are frequently exposed to surgical smoke or plume created by using heat-generating devices like diathermy and lasers. This is a concern due to mounting evidence that this exposure can be harmful with no safe level of exposure yet identified. First, I briefly summarise the problem posed by surgical smoke exposure and highlight that many healthcare organisations are not sufficiently satisfying their legal and ethical responsibilities to protect their staff from potential harm. Second, I explore the ethical case (...) for compulsory smoke evacuation systems using the principlist framework and its four ethical principles – autonomy, beneficence, nonmaleficence, and justice. I then consider some objections and argue that surgical smoke evacuation systems – when indicated – should be made compulsory. (shrink)

Background: The concept of digital twins has great potential for transforming the existing health care system by making it more personalized. As a convergence of health care, artificial intelligence, and information and communication technologies, personalized health care services that are developed under the concept of digital twins raise a myriad of ethical issues. Although some of the ethical issues are known to researchers working on digital health and personalized medicine, currently, there is no comprehensive review that maps the major ethical (...) risks of digital twins for personalized health care services. Objective: This study aims to fill the research gap by identifying the major ethical risks of digital twins for personalized health care services. We first propose a working definition for digital twins for personalized health care services to facilitate future discussions on the ethical issues related to these emerging digital health services. We then develop a process-oriented ethical map to identify the major ethical risks in each of the different data processing phases. Methods: We resorted to the literature on eHealth, personalized medicine, precision medicine, and information engineering to identify potential issues and developed a process-oriented ethical map to structure the inquiry in a more systematic way. The ethical map allows us to see how each of the major ethical concerns emerges during the process of transforming raw data into valuable information. Developers of a digital twin for personalized health care service may use this map to identify ethical risks during the development stage in a more systematic way and can proactively address them. Results: This paper provides a working definition of digital twins for personalized health care services by identifying 3 features that distinguish the new application from other eHealth services. On the basis of the working definition, this paper further layouts 10 major operational problems and the corresponding ethical risks. Conclusions: It is challenging to address all the major ethical risks that a digital twin for a personalized health care service might encounter proactively without a conceptual map at hand. The process-oriented ethical map we propose here can assist the developers of digital twins for personalized health care services in analyzing ethical risks in a more systematic manner. (shrink)

Main challenges, priorities and trends of the national health care are analyzed in the paper. The general concept of managerial capital was defined; its main sources were analyzed. Objective processes of developing a professional management system have been viewed. Within the framework of the forming organization’s management capital the following tasks of healthcare facilities’ management were determined. In the paper it is argues, that the process of managerial capital formation is ongoing in the frameworks of managerial staff’s professionalization. Thus, (...) the main directions and variants of professionalization of managerial staff in healthcare field are proposed. But nevertheless, it is important to emphasize, that professionalization of managerial staff in Ukrainian health care is very complicated process, due to the lack of special training basis for its realization and, especially, understanding of government its necessity. The problem of forming and developing managers of healthcare facilities has been emphasized in the paper. Requirements for modern healthcare professionals have been identified. (shrink)

Objectives: Machine learning (ML) has the potential to facilitate “continual learning” in medicine, in which an ML system continues to evolve in response to exposure to new data over time, even after being deployed in a clinical setting. In this article, we provide a tutorial on the range of ethical issues raised by the use of such “adaptive” ML systems in medicine that have, thus far, been neglected in the literature. -/- Target audience: The target audiences for this tutorial (...) are the developers of ML AI systems, healthcare regulators, the broader medical informatics community, and practicing clinicians. -/- Scope: Discussions of adaptive ML systems to date have overlooked the distinction between 2 sorts of variance that such systems may exhibit—diachronic evolution (change over time) and synchronic variation (difference between cotemporaneous instantiations of the algorithm at different sites)—and underestimated the significance of the latter. We highlight the challenges that diachronic evolution and synchronic variation present for the quality of patient care, informed consent, and equity, and discuss the complex ethical trade-offs involved in the design of such systems. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics (...) and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

The continuous growth of healthcare data has made it essential to develop efficient systems that not only alert healthcare providers but also visualize patient data in a comprehensible way. This study introduces a Health Alert System integrated with Report Visualization powered by Data Analytics to improve patient monitoring and alerting mechanisms. By leveraging real-time data from wearable sensors and hospital records, the system generates health alerts based on deviations from normal parameters. The proposed system combines predictive analytics (...) and historical data to flag potential emergencies before they occur. The visual analytics platform provides comprehensive reports to healthcare providers, enabling them to monitor trends, identify risk factors, and make informed decisions. This approach significantly enhances patient care by minimizing delays in response and improving overall health outcomes. The system's architecture, based on big data frameworks, supports scalable and efficient data processing. The study demonstrates how the integration of predictive models and data visualization tools can revolutionize health alert systems, making them more responsive and adaptive to individual patient needs. Future enhancements will focus on incorporating machine learning models for more personalized predictions and extending the system's capabilities to remote patient care. (shrink)

This thesis under the title “Public Health Policy in Resource Allocation: the Role of Ubuntu Ethics in Redressing Resource Disparity between Public and Private Healthcare in South Africa” explores health care disparities pertaining to resource allocation between public and private sector. It is of relevance and importance in South Africa where 54% of the population live on less than US$3 per day. Although the government has instituted certain changes aimed at transforming the public health care system, the resource allocation (...) gap between the two persists and remains wide. The research gives special attention to the role that Ubuntu ethics can play in redressing the resource allocation disparities between public and private health care sectors in South Africa, pointing out the existing gap in financing, as well as human resource between public and private health care sectors, which leads to poor health outcomes in public sector. Therefore, the problem is the prevalent inequality of resource allocation between private and public health care sectors. The analysis of policy gaps, as well as evaluating the cause of disparities in the health system is the goal of this research. The study endeavours to redress the disparities within the context of Ubuntu ethical principles and proposes a change in public policy so as to enhance healthcare for the benefit of the people. The study is philosophical and ethical, so the methodology used is discursive in nature, majorly focusing on critically reviewing existing literature, that is, the philosophical resources on Ubuntu ethics and justice theories as well as a range of government resources inclusive of public health policy documents. Social determinants of health and their impact in a South African context are discussed with the implication that health is not merely freedom from disease and or incapacity, but rather being well mentally, physically and socially. The attainment of a healthy status goes beyond ability to access healthcare services, and incorporates social determinants including but not limited to conditions in which people have been born into, stay, establish career and grow old in. It also includes the arrangements put in place to deal with illness and determine health. Issues of revenue, literacy, communal safety networks, vocation and conditions under-which vocation is undertaken, lack of work and vocation insecurity, early stages of human development, gender, cultural group, dietary insecurity, housing communal exclusion and disability all come into the picture as factors that determine health. But there is also discussion of the socio-economic status as contributors to health inequity wherein alcohol abuse, sugar intake, and smoking are identified as behavioural factors that complicate public health. One outstanding feature of this research is that it establishes a link between Ubuntu and public health policy. The researcher establishes that Ubuntu ethics is appropriate for not only discussing public morality, but also for formulating public policy that is morally tenable for South Africa, especially for the public health sector. This thesis calls for an application of Ubuntu in a proper context in order to enhance societal well-being for the benefit of many, if not all. The research proposes the fundamental principle of Ubuntu ethics in which the good of the community is as important as the good of every member of the community. Since Ubuntu ethics does not merely seek to fulfil what benefits the majority, as would be the case in a utilitarian society, the researcher advocates for the building of consensus on the common good, which should be understood to imply not just what is good for everyone in the community, but also what is good for the continued well-being of the community as a single unit. In this regard, the research finds it important that deliberate effort be made to integrate Ubuntu ethics into policies, citing the example of the National Health Insurance (NHI). The good health of all the members of a community is an assurance of the well-being and continuity of the whole national community. The research concludes that public health policy should integrate Ubuntu ethical values such as community, sharing, care, solidarity, identity, harmony, respect, and dignity into policy documents and legislation. (shrink)

Disaster response is a highly collaborative and critical process that requires the involvement of multiple emergency responders (ERs), ideally working together under a unified command, to enable a rapid and effective operational response. Following the 9/11 and 11/13 terrorist attacks and the devastation of hurricanes Katrina and Rita, it is apparent that inadequate communication and a lack of interoperability among the ERs engaged on-site can adversely affect disaster response efforts. Within this context, we present a scenario-based terrorism case study to (...) highlight the challenges of operational disaster command and response. In this article, which is based on the French emergency response doctrine, we outline a semantics-based common operational command system that is designed to guarantee an efficient information flow among ERs. Our focus is on offering to all ERs, a real-time operational picture of the situation in order to enable multilevel coordination among firefighters, police, healthcare units, public authorities, and other stakeholders. Our approach consolidates information to promote timely sharing of data among ERs. The proposed system is based on an ontology that has been developed to represent the different types of knowledge on the part of ERs, providing a shared vocabulary that covers a variety of interoperability concerns. (shrink)

The article examines the participation and assistance of the Orthodox Church in solving problems that allowed to give a scientific justification for the cooperation of health care and Orthodox religious institutions, to determine their role in the historical context and structure of modern healthcare in Russia. The article presents an algorithm for organizing sisters of mercy, their system of upbringing. Particular attention is given to the possibility of teaching the course "Foundations of Orthodox Culture" in secular educational institutions. -/- (...) Research materials can serve as a basis for the formation of morally sound positions of medical workers and the population on the main problems of medical activity. -/- Based on the study, the authors published a series of articles in which the experience of the work of the Orthodox Church in the charitable sphere has been summarized. This experience can be used to create new charitable institutions, including those who provided medical assistance. -/- In preparing the article, the authors used concrete historical, civilizational, formational and social methods of research that allowed us to uncover facts, phenomena and processes in the interconnection and unity of the past, present and future. (shrink)