The development of artificial intelligence (AI) has revolutionised the medical system, empowering healthcare professionals to analyse complex nonlinear big data and identify hidden patterns, facilitating well-informed decisions. Over the last decade, there has been a notable trend of research in AI, machine learning (ML), and their associated algorithms in health and medical systems. These approaches have transformed the healthcare system, enhancing efficiency, accuracy, personalised treatment, and decision-making. Recognising the importance and growing trend of research in the topic area, this paper presents a bibliometric analysis of AI in health and medical systems. The paper utilises the Web of Science (WoS) Core Collection database, considering documents published in the topic area for the last four decades. A total of 64,063 papers were identified from 1983 to 2022. The paper evaluates the bibliometric data from various perspectives, such as annual papers published, annual citations, highly cited papers, and most productive institutions, and countries. The paper visualises the relationship among various scientific actors by presenting bibliographic coupling and co-occurrences of the author\'s keywords. The analysis indicates that the field began its significant growth in the late 1970s and early 1980s, with significant growth since 2019. The most influential institutions are in the USA and China. The study also reveals that the scientific community\'s top keywords include \'ML\', \'Deep Learning\', and \'Artificial Intelligence\'.

The application of artificial intelligence to improve the access of cancer patients to high-quality medical care is one of the goals of modern medicine. Pathology constitutes the foundation of modern oncologic treatment, and its role has expanded far beyond diagnosis into predicting treatment response and overall survival. However, the funding of pathology is often an afterthought in resource-scarce medical systems. The increased digitalization of pathology has paved the way towards the potential use of artificial intelligence tools for improving pathologist efficiency and extracting more information from tissues. In this review, we provide an overview of the main research directions intersecting with artificial intelligence and pathology in relation to oncology, such as tumor classification, the prediction of molecular alterations, and biomarker quantification. We then discuss examples of tools that have matured into clinical products and gained regulatory approval for clinical use. Finally, we highlight the main hurdles that stand in the way of the digitalization of pathology and the application of artificial intelligence in pathology while also discussing possible solutions.

Healthcare delivery systems are widely accepted as socio-technical systems. Unlike other socio-technical systems, healthcare systems leave very little decision-making to technical automation and control. Instead, the healthcare delivery system relies on human healthcare resources for decision-making. Human decision-making is imperative to the clinical delivery of care to patients and to the operational processes that support care delivery, quality improvement, and other organizational management activities. For these clinical and operational activities, human resources make healthcare decisions using healthcare data typically housed in electronic medical records (EMRs). Unfortunately, EMR systems were first designed with the functional capability to store data, and, second to a lesser degree, to retrieve data. The literature recognizes the need to improve the retrieval of information from EMR systems. More specifically, there remains the need to directly view a patient\'s holistic health and healthcare trajectory. At this time, decision-makers are left to mentally build this holistic picture in their mind by sequentially clicking through many sections of the EMR. Therefore, in this paper, we develop a visualization tool to organize and present an individual\'s health and healthcare trajectory by describing a patient record holistically from a system architecture perspective. This approach is based on a previously developed system model for healthcare delivery and individual health outcomes.

Perceptions of errors associated with healthcare information technology (HIT) often depend on the context and position of the viewer. HIT vendors posit very different causes of errors than clinicians, implementation teams, or IT staff. Even within the same hospital, members of departments and services often implicate other departments. Organizations may attribute errors to external care partners that refer patients, such as nursing homes or outside clinics. Also, the various clinical roles within an organization (e.g., physicians, nurses, pharmacists) can conceptualize errors and their root causes differently. Overarching all these perceptual factors, the definitions, mechanisms, and incidence of HIT-related errors are remarkably conflictual. There is neither a universal standard for defining or counting these errors. This paper attempts to enumerate and clarify the issues related to differential perceptions of medical errors associated with HIT. It then suggests solutions.

BACKGROUND: At a time when welfare contracts are in crisis, it is timely to discuss different forms of disruptive innovation and responses of medical finance and economic systems, especially adjusting with new instruments for recovery and innovative solutions for health reforms.
OBJECTIVE: The objective of this paper is to propose some ways to develop a framework for policy changes affecting life science sectors and healthcare. It aims to analyze the types of relationships between health or medical systems and the economic systems.
METHODS: Medical systems used to be generally closed systems, but the new forms of delivery, especially with increase of telehealth and Mobile health (Mhealth) solutions (boosted by the COVID-19 pandemic, such as online consultations), have open traditional boundaries and generate more interactions with economic systems. It also led to new institutional arrangements at federal, national, or local levels, with different power games according to the history of institutions and cultural differences between countries.
RESULTS: Which system dynamics prevail will also depend on the political systems in place, for instance very innovative open innovation systems dominated by private players such as the USA empower individuals and favor intuitive and entrepreneurial states. On the other hand, systems historically dominated by socialized insurance or former communist countries, have investigated \"attunements\" or adaptation mechanisms in system intelligence. However, systemic changes are not only implemented by traditional rulers (government agencies, federal reserve banks) but also face the emergence of systemic platforms dominated by Big Tech players. The new agendas expressed for instance in the United Nation (UN) framework and the set of Sustainable Development Goals (SDGs) for climate change and sustainable growth, also require global adjustment of supply and demand, in a context where the traditional drug/vaccine split is challenged by the new technologies (e.g., mRNA technologies). Investment for drug research led to the development of COVID-19 vaccines, but also potential cancer vaccines. Finally, welfare economics is increasingly criticized among economist circles; it requires new design for global value assessment framework, facing growing inequalities and inter-generational challenges in aging populations.
CONCLUSIONS: This paper contributes to new models of developments and different frameworks for multiple stakeholders with major technological changes.

Health care is ever more important with the aging population and with the increased awareness of the importance of the medical systems due to the corona crisis that showed the capacity of the health care infrastructure, especially in terms of numbers of health care personnel such as doctors, was not sufficient. Assuming that the number of doctors per patient is one of the determinants of patient satisfaction, optimal investments in new doctors, specialist doctors and foreign doctors are analyzed. Optimal Control Theory is employed to determine the optimal investment strategy for new doctors (new graduates), specialists and foreign doctors to maximize the net (of costs) patient satisfaction over a fixed time horizon. It is found that a nation with an insufficient number of total doctors and specialist doctors at the beginning of the planning horizon should increase the investment in new doctors as a quadratic function of time, increase the local specialist doctors linearly, while employing foreign doctors as to equate their cost to the marginal satisfaction of patients.

Primary Health Care (PHC), based on the Alma Ata declaration, calls for the movement of responsibility, resources, and control away from medical systems and curative measures toward health promotion. However, PHC implementation in practice appears to be heavily influenced by medical systems with its own attendant effects on the attainment of PHC goals. This study therefore examines the extent and effects of medical systems influence on PHC implementation in Ghana. The study uses the thematic framework approach to qualitative data analysis to analyze data collected from PHC managers through interviews. Ethical clearance for the study was obtained from the Noguchi Memorial Institute for Medical Research. Findings suggest that PHC in practice is tied to the apron-strings of medical systems. While this has catalyzed successes in disease control programs and other medicine-based interventions, it has swayed PHC from its intended shift toward health promotion. Community ownership, participation, and empowerment in PHC is therefore lost in the maze of medical systems which reserves power over PHC decision making and implementation to medical professionals while focusing attention on treatment and curative services. Ultimately, PHC has gradually metamorphosed into mini-clinics instead of the revolutionary community-driven promotive services espoused by Alma Ata with concomitant effects on the attainment of Universal Health Coverage. Further, findings show how gradually, the primary in PHC is being used as a descriptor of the first or basic level of hospital-based care instead of a first point of addressing existing health problems using preventive, promotive, and other community driven approaches. Without a reorientation of health systems, significant efforts and resources are channeled toward empowering health workers instead of local communities with significant effects on the long term sustainability of health efforts and the attainment of UHC. The study recommends further studies toward practical means of reducing the influence of medical systems.

The emergency department has been a major focus for the implementation of Australia\'s national electronic health record, known as My Health Record. However, the association between use of My Health Record in the emergency department setting and patient care is largely unknown. The aim of this study was to explore the perspectives of emergency department clinicians regarding My Health Record use frequency, the benefits of My Health Record use (with a focus on patient care) and the barriers to use.
All 393 nursing, pharmacy, physician and allied health staff employed within the emergency department at a tertiary metropolitan public hospital in Melbourne were invited to participate in a web-based survey, between 1 May 2021 and 1 December 2021, during the height of the Delta and Omicron Covid-19 outbreaks in Victoria, Australia.
Overall, the survey response rate was 18% (70/393). Approximately half of the sample indicated My Health Record use in the emergency department (n = 39, 56%, confidence interval [CI] 43-68%). The results showed that users typically only engaged with My Health Record less than once per shift (n = 15, 39%, CI 23-55%). Just over half (n = 19/39, 54%, CI 32-65%) of all participants who use My Health Record agreed they could remember a time when My Health Record had been critical to the care of a patient. Overall, clinicians indicated the biggest barrier preventing their use of My Health Record is that they forget to utilise the system.
The results suggest that My Health Record has not been adopted as routine practice in the emergency department, by the majority of participants. Close to half of self-identified users of My Health Record do not associate use as being critical to patient care. Instead, My Health Record may only be used in scenarios that clinicians perceive will yield the greatest benefit-which clinicians in this paper suggest is patients with chronic and complex conditions. Further research that explores the predictors to use and consumers most likely to benefit from use is recommended-and strategies to socialise this knowledge and educate clinicians is desperately required.

The novel SARS-CoV-2 (COVID-19) disrupted many facets of the healthcare industry throughout the pandemic and has likely permanently altered modern healthcare delivery. It has been shown that existing healthcare infrastructure influenced national responses to COVID-19, but the current implications and resultant sequelae of the pandemic on the organizational framework of healthcare remains largely unknown. This paper aims to review how aspects of contemporary medical systems - the physical environment of care delivery, global healthcare supply chains, workforce structures, information and communication systems, scientific collaboration, as well as policy frameworks - evolved in the initial response to the COVID-19 pandemic.

This study explores patient and context related factors associated with use of Australia\'s national personally controlled Health Information Exchange (HIE), My Health Record, by emergency department (ED) clinicians.
A retrospective analysis explored secondary routinely-collected data including all patients who presented (between August 2019-2021) to the ED at a not-for-profit hospital in Melbourne. Presentation data were linked to the HIE access log-data, and human resources data. The primary outcome indicated HIE access by an ED pharmacist, doctor or nurse, within 3 days of the patient presenting to the ED, or not. Nine variables were explored with logistic regression, representing patient (gender, age, diagnosis) and other factors (presentation time, arrival method, referral, acuity/triage, length of stay, admitted into hospital).
HIE is accessed in 17.43% of patient presentations to the ED, led by pharmacists (15.60%). Overall, as demonstrated in themultivariable analysis, increased HIE access was associated with increasing age, with the biggest effect for 75-84-year old\'s (odd\'s ratio 26.15; 95% confidence interval 15.37-44.50), when compared to < 4 years of age. HIE access was also significantly and positively associated with patients who were later admitted into hospital from theED (4.96; 4.61-5.34).
The results suggest users of HIE in the ED employ the system to meet their needs, but not for all patients. To maximise value derived from HIE use, clinicians should target system access for patients where the benefit of accessing the record outweighs the cost - this research suggests that is for patients who are older in age and are likely to be admitted, potentially linked to greater condition complexity. If the use of a HIE is to improve the provision of care in the ED, the key stakeholders governing patient information within the HIE need to focus on improving clinician recording behaviours for older people and those suffering from complex medical conditions. Doctors and nurses lag behind with respect to the use of the HIE by pharmacists. Therefore, a focus on encouraging HIE engagement across these clinician groups is drastically required.