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Background/Objective: Asthma is a common chronic medical condition among children and the most common diagnosis associated with interfacility transports for pediatric patients. As many as 40% of pediatric transfers may be unnecessary, resulting in potential delays in care and unnecessary costs. Our objective was to identify the patient-related factors associated with potentially unnecessary transfers for pediatric patients with asthma.Methods: We used patient care data from the California Department of Health Care Access and Information patient discharge and emergency department (ED) datasets to capture ED visits where a pediatric patient (age 2–17 years) presented with asthma and was transferred to another ED or acute care hospital. The outcome of interest was a potentially unnecessary transfer, defined as a visit where length of stay after transfer was

Background: People with end-of-life chronic obstructive pulmonary disease (COPD) experience debilitating physical limitations, with a high mortality rate. Our research has shown health system design and delivery leads to inequitable outcomes. Enabling people with end-of-life COPD, their support people, and health professionals to partner in setting the agenda for resource allocation may inform health service improvement. Design: Qualitative methodology utilising focus groups including patients, family, friends, informal support people, health care workers and professionals. Methods: The analysis, utilising critical theory and Actor-Network theory, positioned people with severe COPD, their support people and health professionals as experts in end-of-life care. Analyses triangulated these perspectives, and were reviewed by the research investigators and an expert reference group. Results: Participants (n=74) in seven focus groups reported their experiences of inequity within the healthcare system. Equity was an overarching phenomenon identified by participants, with three specific themes being described: policy design, system design, and service design. Conclusion: Experiences of patients, their support people and health professionals as experts in end-of-life COPD care can inform health systems and health service design to address current inequities in funding and delivery of care for end-of-life COPD. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims Design Methods Results Conclusion Implications for the Profession Impact Reporting Method Patient or Public Contribution To explore and describe the meaning of nurses working in care for older adults give to the nursing professional identity.A qualitative approach was taken.Semi‐structured interviews were conducted with 50 bachelor and vocational‐educated nurses working in care for older adults. Interviews were conducted between December 2019 and May 2020. Data were analysed and interpreted through inductive content analysis.Five themes embody the meaning of the nursing professional identity of nurses who work in care for older adults. The five themes are: born to care: a lifelong motivation to nursing; nursing through the noise: dedication in a demanding profession; the silent backbone: caught in the crossfire of interdisciplinary teams; learning under pressure: the demand for expanded nursing expertise and against the current: the barriers to advocacy in nursing.The professional nursing identity of nurses working in care for older adults is multi‐faceted. A personal dedication to patient care, where patients ‘human’ aspect is heavily valued, commits nurses to their profession and underscores their dedication to upholding the quality standard in nursing practice.The older adults' nursing identity highlights that nursing deserves acknowledgement as a professional occupation. Nurses should speak to the public about their professional roles to improve the public view of older adult nursing.A clear understanding of the older adult nursing professional identity clarifies specific roles, experiences and expectations. This can help attract and retain nurses whose views of older adult nursing align with the nursing professional identity. This could help resolve nurse turnover and reduce shortages in older adult care.We adhered to Consolidated Criteria For Reporting Qualitative Research guidelines.No patient or public contribution. [ABSTRACT FROM AUTHOR]

Objective: To evaluate the effects of Medicaid Accountable Care Organizations (ACOs) on children's access to and utilization of health services. Study Setting and Design: This study employs difference‐in‐differences models comparing ACO and non‐ACO states from 2018 through 2021. Access measures are indicators for preventive and sick care sources, unmet healthcare needs, and having a personal doctor or nurse. Utilization measures are preventive and dental care, mental healthcare, specialist visits, emergency department visits, and hospital admissions. Data Sources and Analytic Sample: Secondary, de‐identified data come from the 2016–2021 National Survey of Children's Health. The sample includes children with public insurance and ranges between 21,452 and 37,177 depending on the outcome. Principal Findings: Medicaid ACO implementation was associated with an increase in children's likelihood of having a personal doctor or nurse by about 4 percentage‐points concentrated among states that implemented ACOs in 2018. Medicaid ACOs were also associated with an increase in specialist care use and decline in emergency visits by about 5 percentage‐points (the latter being concentrated among states that implemented ACOs in 2020). There were no discernable or robust associations with other pediatric outcomes. Conclusions: There is mixed evidence on the associations of Medicaid ACOs with pediatric access and utilization outcomes. Examining effects over longer periods post‐ACO implementation is important. [ABSTRACT FROM AUTHOR]

Background Method Results Conclusion Policy changes in Australia mean that psychedelic‐assisted therapy (PAT) is now available to consumers outside of clinical trials. Yet, the regulatory frameworks guiding the practice of PAT are underdeveloped, and the evidence base for guiding clinical practice is diverse and emerging, resulting in anticipated challenges in translation to community practice. Mental health clinicians who have experience delivering PAT in clinical trials are likely to be at the forefront of community practice and training, and influential in discussions about implementation. Yet little is known of their perspectives, preferences, and practices associated with the implementation of PAT.Interviews with 11 clinicians working on clinical trials of PAT were thematically analysed.Four themes were identified, describing the therapeutic frames that interviewees used to understand PAT and shaped their views on its interface with the mental health system: (1) therapeutic eclecticism, (2) enhanced reflexivity for PAT providers, (3) legitimisation of extra‐medical perspectives in mental health, and (4) what might be lost in translation?We argue that clinicians' perspectives on PAT are reflective of existing tensions between a medical model of mental health care and other psychosocial, relational models. Therapists' ideals for the delivery of PAT can be conceptualised as a sort of ‘enhanced care’ approach, but workforce development and economic constraints are likely to challenge the accessible and impactful translation of this vision. [ABSTRACT FROM AUTHOR]

Improving health and social equity for persons living with a rare disease (PLWRD) is increasingly recognized as a global policy priority. However, there is currently no international alignment on how to define and describe rare diseases. A global reference is needed to establish a mutual understanding to inform a wide range of stakeholders for actions. A multi-stakeholder, global panel of rare disease experts, came together and developed an Operational Description of Rare Diseases. This reference describes which diseases are considered rare, how many persons are affected and why the rare disease population demands specific attention. The operational description of rare diseases is framed in two parts: a core definition of rare diseases, complemented by a descriptive framework of rare diseases. The core definition includes parameters that permit the identification of which diseases are considered rare, and how many persons are affected. The descriptive framework elaborates on the impact and burden of rare diseases on patients, their caregivers and families, healthcare systems, and society overall. The Operational Description of Rare Diseases establishes a common point of reference for decision-makers across the world who strive to understand and address the unmet needs of persons living with a rare disease. Adoption of this reference is essential to improving the visibility of rare conditions in health systems across the world. Greater recognition of the burden of rare diseases will motivate new actions and policies to address the unmet needs of the rare disease community. [ABSTRACT FROM AUTHOR]

We study how welfare states regimes influence the effect of episodes of fiscal consolidations on the four main components of the welfare state: social investment, pensions, healthcare and labour market insurance. Welfare state regimes are associated with distinct social policy legacies that feedback into political competition by shaping the size and influence of different coalitions of constituents. Using data from 1980 to 2014 in 16 OECD countries, we find that labour market insurance is more vulnerable to consolidations in Liberal regimes, while social investments are more resistant to consolidations in Nordic regimes. In the Continental regime, which overlaps with Social Health Insurance systems, healthcare is more resistant to consolidations. Finally, pensions are more resistant to consolidations in the Southern regime. These findings contribute to the study of the comparative political economy of welfare state retrenchment. [ABSTRACT FROM AUTHOR]

There is a paucity of literature on children and young people's participation in decision-making within healthcare organisations in New Zealand. This integrative review examined child self-reported peer-reviewed manuscripts and published guidelines, policy, reviews, expert opinion and legislation to explore how New Zealand children and young people participate in discussions and decision-making processes within healthcare settings and what are barriers and benefits to such participation. Four child self-reported peer-reviewed manuscripts and twelve expert opinion documents were retrieved from four electronic databases including academic, government and institutional websites. Inductive content thematic analysis generated one theme (a discourse in children and young people's participation within healthcare settings), four sub-themes, 11 categories, 93 codes and 202 findings. It is evident within this review that there is a discourse between what expert opinion are stating is required to promote children and young people's participation in discussions and decision-making processes within healthcare settings and what is occurring in practice. Despite literature reporting on how children and young people's participation and voice were essential for healthcare provision, there was sparse literature published on children and young people's participation in discussions and decision-making processes in healthcare delivery in New Zealand. [ABSTRACT FROM AUTHOR]

AbstractObjectiveMethodsResultsConclusions\nHIGHLIGHTSSafety planning for suicide prevention is an important quality metric for Zero Suicide implementation. We describe the development, validation, and application of electronic health record (EHR) programs to measure uptake of safety planning practices across six integrated healthcare systems as part of a Zero Suicide evaluation study.Safety planning was documented in narrative notes and structured EHR templates using the Stanley Brown Safety Planning Intervention (SBSPI) in response to a high-risk cutoff score on the Columbia Suicide Severity Rating Scale (CSSRS). Natural Language Processing (NLP) metrics were developed and validated using chart review to characterize practices documented in narrative notes. We applied NLP to measure frequency of documentation in the narrative text and standard programming methods to examine structured SBSPI templates from 2010–2022.Chart reviews found three safety planning practices documented in narrative notes that were delivered to at least half of patients at risk: professional contacts, lethal means counseling for firearms, and lethal means counseling for medication access/storage. NLP methods were developed to identify these practices in clinical text with high levels of accuracy (Sensitivity, Specificity, & PPV ≥ 82%). Among visits with a high-risk CSSRS, 40% (Range 2–73% by health system) had an SBSPI template within 1 year of implementation.This is one of the first reports describing development of measures that leverage electronic health records to track use of suicide prevention safety plans. There are opportunities to use the methods developed here in future evaluations of safety planning.Measuring safety planning delivery in real-world systems to understand quality of suicide prevention care is challenging.Natural Language Processing (NLP) methods effectively identified some safety planning practices in electronic health records (EHR) from all notes ensuring a comprehensive measurement, but NLP will require updates/testing for local documentation practices.Structured safety planning templates in the EHR using the Stanley Brown Safety Planning Intervention improve ease and accuracy of measurement but may be less comprehensive than NLP for capturing all instances of safety planning documentation.Measuring safety planning delivery in real-world systems to understand quality of suicide prevention care is challenging.Natural Language Processing (NLP) methods effectively identified some safety planning practices in electronic health records (EHR) from all notes ensuring a comprehensive measurement, but NLP will require updates/testing for local documentation practices.Structured safety planning templates in the EHR using the Stanley Brown Safety Planning Intervention improve ease and accuracy of measurement but may be less comprehensive than NLP for capturing all instances of safety planning documentation. [ABSTRACT FROM AUTHOR]

Background: Unhealthy alcohol use is widespread in South Africa and has been linked to tuberculosis (TB) disease and poor treatment outcomes. This study used qualitative methods to explore the relationship between TB and alcohol use during TB treatment. Methods: Focus group discussions (FGDs) were conducted with 34 participants who had previous or current drug-susceptible TB and self-reported current alcohol use. Eight interviews were conducted with healthcare workers who provide TB services in Worcester, South Africa. Results: In this rural setting, heavy episodic drinking is normalized and perceived to be related to TB transmission and decreased adherence to TB medication. Both healthcare workers and FGD participants recommended the introduction of universal screening, brief interventions, and referral to specialized care for unhealthy alcohol use. However, participants also discussed barriers to the provision of these services, such as limited awareness of the link between alcohol and TB. Healthcare workers also specified resource constraints, while FGD participants or patients mentioned widespread stigma towards people with alcohol concerns. Both FGD participants and health providers would benefit from education on the relationship between TB and unhealthy alcohol use and had specific recommendations about interventions for alcohol use reduction. Healthcare workers also suggested that community health worker-delivered interventions could support access to and engagement in both TB and alcohol-related services. Conclusion: Findings support strengthening accessible, specialized services for the identification and provision of interventions and psychosocial services for unhealthy alcohol use among those with TB. [ABSTRACT FROM AUTHOR]

Introduction: Intracranial hemorrhages present across a spectrum of clinical phenotypes, with many patients transferred across hospitals to access higher levels of neurocritical care. We sought to characterize patient dispositions following intracranial hemorrhage and examine disparities associated with interhospital transfers. Methods: Using the Healthcare Cost and Utilization Project database, we mapped and identified factors influencing the likelihood of patient transfers and receipt of specialist interventional procedures following intracranial hemorrhage. Results: Of 11,660 patients with intracranial hemorrhage, 59.4% had non-traumatic and 87.5% single compartment bleeds. After presentation, about a quarter of patients were transferred to another facility either directly from the ED (23.0%) or after inpatient admission (1.8%). On unadjusted analysis, patients who were white, in the upper income quartiles, with private insurance, or resided in suburban areas were more frequently transferred. After adjusting for patient and hospital-level variables, younger and non-white patients had higher odds of transfer. Hospital capabilities, residence location, insurance status, and prior therapeutic relationship remained as transfer predictors. Transferred patients had a similar hospital length of stay compared to admitted patients, with 43.1% having no recorded surgical or specialist interventional procedure after transfer. Discussion: Our analysis reveals opportunities for improvement in risk stratification guiding transfers, as well as structural challenges likely impacting transfer decisions. [ABSTRACT FROM AUTHOR]

Abstract Improving health and social equity for persons living with a rare disease (PLWRD) is increasingly recognized as a global policy priority. However, there is currently no international alignment on how to define and describe rare diseases. A global reference is needed to establish a mutual understanding to inform a wide range of stakeholders for actions. A multi-stakeholder, global panel of rare disease experts, came together and developed an Operational Description of Rare Diseases. This reference describes which diseases are considered rare, how many persons are affected and why the rare disease population demands specific attention. The operational description of rare diseases is framed in two parts: a core definition of rare diseases, complemented by a descriptive framework of rare diseases. The core definition includes parameters that permit the identification of which diseases are considered rare, and how many persons are affected. The descriptive framework elaborates on the impact and burden of rare diseases on patients, their caregivers and families, healthcare systems, and society overall. The Operational Description of Rare Diseases establishes a common point of reference for decision-makers across the world who strive to understand and address the unmet needs of persons living with a rare disease. Adoption of this reference is essential to improving the visibility of rare conditions in health systems across the world. Greater recognition of the burden of rare diseases will motivate new actions and policies to address the unmet needs of the rare disease community.

Abstract Background Unhealthy alcohol use is widespread in South Africa and has been linked to tuberculosis (TB) disease and poor treatment outcomes. This study used qualitative methods to explore the relationship between TB and alcohol use during TB treatment. Methods Focus group discussions (FGDs) were conducted with 34 participants who had previous or current drug-susceptible TB and self-reported current alcohol use. Eight interviews were conducted with healthcare workers who provide TB services in Worcester, South Africa. Results In this rural setting, heavy episodic drinking is normalized and perceived to be related to TB transmission and decreased adherence to TB medication. Both healthcare workers and FGD participants recommended the introduction of universal screening, brief interventions, and referral to specialized care for unhealthy alcohol use. However, participants also discussed barriers to the provision of these services, such as limited awareness of the link between alcohol and TB. Healthcare workers also specified resource constraints, while FGD participants or patients mentioned widespread stigma towards people with alcohol concerns. Both FGD participants and health providers would benefit from education on the relationship between TB and unhealthy alcohol use and had specific recommendations about interventions for alcohol use reduction. Healthcare workers also suggested that community health worker-delivered interventions could support access to and engagement in both TB and alcohol-related services. Conclusion Findings support strengthening accessible, specialized services for the identification and provision of interventions and psychosocial services for unhealthy alcohol use among those with TB.

The application of healthcare systems has led to an explosive growth in personal electronic health records (EHRs). These EHRs are generated from different healthcare institutions and stored in cloud data centers, respectively. However, data owners lose the authority to control and track their private and sensitive EHRs. In fact, data owners cannot establish rules for EHRs exchanging and sharing, nor can they verify the integrity of EHRs stored in semi-trusted clouds. Hence, an individual-centric access control framework is required to realize data access control. In this study, we construct a data access control framework, which integrates decentralized smart contracts and role-based access control (RBAC) to provide fine-grained data access control services. The key ideas of this schme includes: (1) a fine-grained access control framework for EHRs is proposed to achieve trusted access control; (2) a personalized policies definition mechanism is adopted to achieve patient-centric data access control; (3) a integrity checking mechanism for the shared EHRs is implemented to ensure the availability of medical records. Finally, we analyze the security properties of this scheme and develop a prototype system to evaluate its performance. Both theoretical analysis and experiment results demonstrate that this scheme can provide fine-grained access control and efficient integrity checking services for EHRs. [ABSTRACT FROM AUTHOR]

Advancements in uncertain reasoning systems within healthcare are crucial for navigating the complexities of patient data, requiring innovative methodologies that integrate AI interpretation capabilities and robust handling of inherent ambiguity. Healthcare systems face the challenge of handling uncertainty inherent in patient data, necessitating sophisticated decision-making tools like Uncertain Reasoning Systems (URS) for effective ambiguity navigation. Recognizing the complexity of healthcare scenarios, advancements in AI interpretation within URS are crucial beyond traditional methods. Conventional techniques like statistical approaches and rule-based systems often prove inadequate due to their rigid frameworks and limited ability to manage inherent ambiguity. This paper proposes an innovative methodology that integrates Min-Max normalization and robust missing data handling techniques with Hybrid Fuzzy Rule-Based Systems and Neural Networks, supplemented by Game Theory for model refinement. Through the integration of Game Theory, it can dynamically adjust its strategies to healthcare data uncertainties, thereby enhancing its resilience and efficacy. Implemented using Python tools, the proposed system achieves an exceptional 99.4 % accuracy, surpassing baseline methods such as FNN (88.1 %) and Naïve Bayes (90 %), highlighting its superior performance in healthcare decision-making. These findings represent significant strides in AI interpretation and decision-making within Uncertain Reasoning Systems, underscoring the practical relevance of the proposed approach.

Abstract Introduction This study examines the association between healthcare indicators and hospitalization rates in three high-income European countries, namely Estonia, Latvia, and Lithuania, from 2015 to 2020. Method We used a sex-stratified generalized additive model (GAM) to investigate the impact of select healthcare indicators on hospitalization rates, adjusted by general economic status—i.e., gross domestic product (GDP) per capita. Results Our findings indicate a consistent decline in hospitalization rates over time for all three countries. The proportion of health expenditure spent on hospitals, the number of physicians and nurses, and hospital beds were not statistically significantly associated with hospitalization rates. However, changes in the number of employed medical doctors per 10,000 population were statistically significantly associated with changes of hospitalization rates in the same direction, with the effect being stronger for males. Additionally, higher GDP per capita was associated with increased hospitalization rates for both males and females in all three countries and in all models. Conclusions The relationship between healthcare spending and declining hospitalization rates was not statistically significant, suggesting that the healthcare systems may be shifting towards primary care, outpatient care, and on prevention efforts.

Abstract Dengue causes approximately 10.000 deaths and 100 million symptomatic infections annually worldwide, making it a significant public health concern. To address this, artificial intelligence tools like machine learning can play a crucial role in developing more effective strategies for control, diagnosis, and treatment. This study identifies relevant variables for the screening of dengue cases through machine learning models and evaluates the accuracy of the models. Data from reported dengue cases in the states of Rio de Janeiro and Minas Gerais for the years 2016 and 2019 were obtained through the National Notifiable Diseases Surveillance System (SINAN). The mutual information technique was used to assess which variables were most related to laboratory-confirmed dengue cases. Next, a random selection of 10,000 confirmed cases and 10,000 discarded cases was performed, and the dataset was divided into training (70%) and testing (30%). Machine learning models were then tested to classify the cases. It was found that the logistic regression model with 10 variables (gender, age, fever, myalgia, headache, vomiting, nausea, back pain, rash, retro-orbital pain) and the Decision Tree and Multilayer Perceptron (MLP) models achieved the best results in decision metrics, with an accuracy of 98%. Therefore, a tree-based model would be suitable for building an application and implementing it on smartphones. This resource would be available to healthcare professionals such as doctors and nurses.

By integrating energy-efficient AIoT-based biosensor networks, healthcare systems can now predict COVID-19 outbreaks with unprecedented accuracy and speed, revolutionizing early detection and intervention strategies. Therefore, this paper explores the rapid growth of electronic technology in today’s environment, driven by the proliferation of advanced devices capable of monitoring and controlling various healthcare systems. However, these devices’ limited resources necessitate optimizing their utilization. To tackle this concern, we propose an enhanced Artificial Intelligence of Things (AIoT) system that utilizes the networking capabilities of IoT biosensors to forecast potential COVID-19 outbreaks. The system aims to efficiently collect data from deployed sensor nodes, enabling accurate predictions of possible disease outbreaks. By collecting and pre-processing diverse parameters from IoT nodes, such as body temperature (measured non-invasively using the open-source thermal camera TermoDeep), population density, age (captured via smartwatches), and blood glucose (collected via the CGM system), we enable the AI system to make accurate predictions. The model’s efficacy was evaluated through performance metrics like the confusion matrix, F1 score, precision, and recall, demonstrating the optimal potential of the IoT-based wireless sensor network for predicting COVID-19 outbreaks in healthcare systems.

Orjola Shahaj,1 Anne Meiwald,1 Krishnan Puri Sudhir,1 Rupert Gara-Adams,1 Peter Wark,2 Alexis Cazaux,3 Abelardo Elizondo Rios,4 Sergey N Avdeev,5 Elisabeth J Adams1 1Aquarius Population Health, London, UK; 2Respiratory and Sleep Medicine, John Hunter Hospital, New Castle, Australia; 3Pulmonary and Respiratory Medicine, Universidad Nacional de Cordoba, Cordoba, Argentina; 4Intensive Pneumology, Autonomous University of Nuevo Leon, Monterrey, Nuevo Leon, Mexico; 5Respiratory Medicine, Sechenov First Moscow State Medical University, Moscow, RussiaCorrespondence: Elisabeth J Adams, Aquarius Population Health, Unit 29 Tileyard Studios, London, N7 9AH, UK, Tel +44 207 993 2930, Email elisabeth.adams@aquariusph.comPurpose: Chronic obstructive pulmonary disease (COPD) poses a significant global health burden despite being largely preventable and treatable. Despite the availability of guidelines, COPD care remains suboptimal in many settings, including high-income countries (HICs) and upper-middle-income countries (UMICs), with varied approaches to diagnosis and management. This study aimed to identify common and unique barriers to COPD care across six countries (Australia, Spain, Taiwan, Argentina, Mexico, and Russia) to inform global policy initiatives for improved care.Methods: COPD care pathways were mapped for each country and supplemented with epidemiological, health-economic, and clinical data from a targeted literature review. Semi-structured interviews with 17 respiratory care clinicians were used to further validate the pathways and identify key barriers. Thematic content analysis was used to generate the themes.Results: Six themes were common in most HICs and UMICs: “Challenges in COPD diagnosis”, “Strengthening the role of primary care”, “Fragmented healthcare systems and coordination challenges”, “Inadequate management of COPD exacerbations”, “Limited access to specialized care” and, “Impact of underfinanced and overloaded healthcare systems”. One theme, “Insurance coverage and reimbursement challenges”, was more relevant for UMICs. HICs and UMICs differ in patient and healthcare provider awareness, primary care involvement, spirometry access, and availability of specialized care. Both face issues with healthcare fragmentation, guideline adherence, and COPD exacerbation management. In addition, UMICs also grapple with resource limitations and healthcare infrastructure challenges.Conclusion: Many challenges to COPD care are the same in both HICs and UMICs, underscoring the pervasive nature of these issues. While country-specific issues require customized solutions, there are untapped possibilities for implementing global respiratory strategies that support countries to manage COPD effectively. In addition to healthcare system-level initiatives, there is a crucial need for political prioritization of COPD to allocate the essential resources it requires.Keywords: COPD, barriers, qualitative research, healthcare systems, global policy

Abstract Background The national e-prescription system in Greece is one of the most important achievements in the e-health sector. Healthcare professionals’ feedback is essential to ensure the introduced system tends to their needs and reduces their everyday workload. The number of surveys collecting the users’ views is limited, while the existing studies include only a small number of participants. Methods In this study, healthcare professionals’ perceptions on e-prescription are explored. For this, a questionnaire was distributed online, containing closed- and open-ended questions aiming to address strengths and identify drawbacks in e-prescription. Answers were collected from primary health care physicians, specialized medical doctors and pharmacists. Results In total, 430 answers were collected (129 from primary health care physicians, 164 responses from specialized medical doctors and 137 pharmacists). Analysis of the collected answers reveals that the views of the three groups of healthcare professionals mostly converge. The positive impact e-prescribing systems have on the overall prescribing procedure in preventing errors and providing automation is commented. Among gaps identified and proposed improvements, health care professionals note the need for access to information on adverse drug reactions, side effects, drug-to-drug interactions and allergies. Flexible interaction with Therapeutic Prescription Protocols is desired to ameliorate monitoring and decision-making, while drug dosing features, and simplified procedures for copying, repeating, canceling a prescription, are perceived as useful to incorporate. Conclusions Collecting healthcare professionals’ feedback is important, as their views can be transcribed to system requirements, to further promote e-prescribing and improve the provided health care services by facilitating decision making through safer and more efficient e-prescription. Introduction of the identified improvements can simplify the everyday workflow of healthcare professionals. To the best of our knowledge, a survey with more than 400 answered questionnaires on the use of e-prescription systems by healthcare professionals has never been conducted in Greece before.

Abstract Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challenge. In this paper, we present a novel methodology for categorizing AIoMT devices through the application of decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying a system on standard IoT devices and labeled IoMT devices for training purposes and attribute extraction. Through this process, we extract and map the interconnected attributes from a global federated cum aggression server. The aim of this terminology is to extract interdependent devices via federated learning, ensuring data privacy and adherence to operational policies. Consequently, a global training dataset repository is coordinated to establish a centralized indexing and synchronization knowledge repository. The categorization process employs generic labels for devices transmitting medical data through regular communication channels. We evaluate our proposed methodology across a variety of IoT, IoMT, and AIoMT devices, demonstrating effective classification and labeling. Our technique yields a reliable categorization index for facilitating efficient access and optimization of medical devices within global servers.

Abstract Regulatory marketing authorisation is not enough to ensure patient access to new medicinal products. Health Technology Assessment bodies may require data on effectiveness, relative effectiveness, and cost-effectiveness. Healthcare systems may require data on clinical utility, savings, and budget impact. Furthermore, the exact requirements of these bodies vary country by country and sometimes even region to region, resulting in a patchwork of different data requirements to achieve effective, reimbursed patient access to new therapies. In addition, clinicians require data to make informed clinical management decisions. This requirement is of key importance in rare diseases where there is often limited data and clinical experience at the time of regulatory approval. This paper describes an innovative initiative that is called Project SATURN: Systematic Accumulation of Treatment practices and Utilization, Real world evidence, and Natural history data for the rare disease Osteogenesis Imperfecta. The objective of this project is to generate a common core dataset by utilising existing data sources to meet the needs of the various stakeholders and avoiding fragmentation through multiple approaches (e.g., a series of individual national requests/approaches, and unconnected with the regulators’ potential requirements). It is expected that such an approach will reduce the time for patient access to life-changing medications. Whilst Project SATURN applies to Osteogenesis Imperfecta, it is anticipated that the principles could also be applied to other rare diseases and reduce the time for patient access to new medications.

Advancements in uncertain reasoning systems within healthcare are crucial for navigating the complexities of patient data, requiring innovative methodologies that integrate AI interpretation capabilities and robust handling of inherent ambiguity. Healthcare systems face the challenge of handling uncertainty inherent in patient data, necessitating sophisticated decision-making tools like Uncertain Reasoning Systems (URS) for effective ambiguity navigation. Recognizing the complexity of healthcare scenarios, advancements in AI interpretation within URS are crucial beyond traditional methods. Conventional techniques like statistical approaches and rule-based systems often prove inadequate due to their rigid frameworks and limited ability to manage inherent ambiguity. This paper proposes an innovative methodology that integrates Min-Max normalization and robust missing data handling techniques with Hybrid Fuzzy Rule-Based Systems and Neural Networks, supplemented by Game Theory for model refinement. Through the integration of Game Theory, it can dynamically adjust its strategies to healthcare data uncertainties, thereby enhancing its resilience and efficacy. Implemented using Python tools, the proposed system achieves an exceptional 99.4 % accuracy, surpassing baseline methods such as FNN (88.1 %) and Naïve Bayes (90 %), highlighting its superior performance in healthcare decision-making. These findings represent significant strides in AI interpretation and decision-making within Uncertain Reasoning Systems, underscoring the practical relevance of the proposed approach. [ABSTRACT FROM AUTHOR]

Transition from antepartum to postpartum care is important, but often fragmented, and attendance at postpartum visits can be poor. Access to care is especially important for individuals diagnosed antepartum with conditions associated with longer-term implications, including gestational diabetes (GDM) and hypertensive disorders in pregnancy (HDP). Strategies to link and strengthen this transition are essential to support people to attend recommended appointments and testing. This narrative review evaluates what is known about postpartum transition of care after higher-risk antepartum conditions, discusses barriers and facilitators to uptake of recommended testing, and outlines strategies trialled to increase both postpartum attendance and testing. Barriers to attendance frequently overlap with general barriers to accessing healthcare. Specific postpartum challenges include difficulties with transport, coordinating breastfeeding and childcare access. Systemic challenges include inadequate communication to women around implications of health conditions diagnosed in pregnancy, and the importance of postpartum follow up. Uptake of recommended testing after a diagnosis of GDM and HDP is variable but generally suboptimal. Strategies which demonstrate promise include the use of patient navigators, focused education and specialised clinics. Reminder systems have had variable impact. Telehealth and technology are under-utilised in this field but offer promising options particularly with the expansion of virtual healthcare into routine maternity care. Strategies to improve both attendance rates and uptake of testing must be designed to address disparities in healthcare access and tailored to the needs of the community. This review provides a starting point to develop such strategies from the community level to the population level. [ABSTRACT FROM AUTHOR]

The smart healthcare system advancements have introduced the Internet of Things, enabling technologies to improve the quality of medical services. The main idea of these healthcare systems is to provide data security, interaction between entities, efficient data transfer, and sustainability. However, privacy concerning patient information is a fundamental problem in smart healthcare systems. Many authentications and critical management protocols exist in the literature for healthcare systems, but ensuring security still needs to be improved. Even if security is achieved, it still requires fast communication and computations. In this paper, we have introduced a new secure privacy-enhanced fast authentication key management scheme that effectively applies to lightweight resource-constrained devices in healthcare systems to overcome the issue. The proposed framework is applicable for quick authentication, efficient key management between the entities, and minimising computation and communication overheads. We verified our proposed framework with formal and informal verification using BAN logic, Scyther simulation, and the Drozer tool. The simulation and tool verification shows that the proposed system is free from well-known attacks, reducing communication and computation costs compared to the existing healthcare systems. [ABSTRACT FROM AUTHOR]

This paper uses a drama-based method to illustrate the responses of healthcare and legal systems to women experiencing coercive control. This approach involved writing a play using the first-person narrative voice of a victim-survivor. We presented the play at the Stop Domestic Violence Conference (Gold Coast, Australia) in 2021. The central character, 'Kate', provided an embodied performance that enabled the conference participants to see, feel and understand experiences of coercive control from a personal perspective. We followed the trajectory of coercive control from the beginning of an intimate relationship to the time of separation. We showed how the process of coercive control escalates from love bombing, reproductive coercion, isolation, and technology-facilitated abuse until a point of police intervention. As Kate told her story, the conference audience witnessed the barriers and challenges faced by survivors of coercive control, and the emotional, financial, and psychological impacts that are intensified in geographically remote environments. They watched Kate navigate health and other systems meant to help women experiencing domestic and family violence, but that ultimately failed to deliver. Finally, the drama-based approach allowed us to present a feminist embodiment of coercive control and an innovative method for communicating inter-disciplinary research findings on domestic abuse. [ABSTRACT FROM AUTHOR]

Introduction: Hematology/oncology pharmacists work in various roles in healthcare systems and represent a highly skilled and valuable resource. There remains a significant challenge in the recruitment and retention of these well‐trained pharmacists. We sought to identify key factors and propose solutions to impact the ability to recruit, promote, and retain pharmacists. Methods: An initial survey in 2021 assessed the status of the oncology pharmacist workforce with regard to job satisfaction and attrition risk. Based on the top 5 factors identified in the Initial Survey, a Follow‐Up Survey was conducted in 2022 to further understand top dissatisfiers in the workplace. To address these factors, an in‐person collaborative workshop was conducted in 2023 with a focus on creating action plans around the practice model, professional development, well‐being, and metrics. Results: A total of 392 individuals participated in the Follow‐Up Survey. Most were 31–40 years of age (56%), female (70%), Caucasian (78%), and from academic medical centers (68%). Of the 367 individuals who responded to factors contributing to dissatisfaction at work, 51 of the respondents selected all five factors. The most common factor was the practice model (77%), followed by burnout/well‐being (74%), leadership (62%), professional development (56%), and metrics (32%). At the workshop, teams worked collaboratively to review detailed data, evaluate root causes, define a goal future state, and build recommendations for incremental steps to pursue progress in each of these areas. Discussion: Utilizing key information learned from both the Initial and Follow‐Up Survey, the Oncology Pharmacy Workforce Collaborative demonstrated that the key themes are interconnected and institutional support is essential in modernizing practice models, revamping professional development, creating better measures of direct and indirect patient care activities, and ensuring effective support for well‐being. [ABSTRACT FROM AUTHOR]

This study presents the results from rapid review of how model‐based systems engineering (MBSE) is utilized in healthcare systems (HSs). We conduct a review of the last twelve years and find that MBSE adoption in HSs is accelerating, with use of various MBSE languages and tools, as well as their integration with other simulation and modeling techniques. We find that similar to engineered systems, the most common MBSE language is systems modeling language (SysML), followed by unified modeling language (UML) and others. Additionally, we observe that MBSE methods are frequently used in conjunction with other analytical techniques, such as simulation and co‐simulations, to analyze and enhance various HS operations, or to assist with making tradeoffs between HS attributes such as quality and cost. Moreover, we provide a non‐exhaustive classification of current research based on two dimensions: healthcare applications and MBSE use cases. Notably, MBSE is being implemented generally with patient‐centric objectives in various HS domains, including IoT‐enabled smart healthcare, clinical medicine, medical device development, healthcare process enhancement, and healthcare facilities management. While the primary MBSE use case involves modeling different aspects of healthcare operations, there is a significant number of studies that pursue requirements engineering, systems analysis, integration, verification and validation, as well as risk analysis and management. Furthermore, we identify two promising research gaps. First, there is a need for the integration of MBSE with state‐of‐the‐art data‐driven analytical methodologies such as hybrid simulation and artificial intelligence techniques. Second, HSs could greatly benefit from representing the cognitive functions and processes of human decision‐makers in the loop, such as healthcare providers (e.g., doctors and nurses), who are instrumental in sustaining the HS performance and functionality. We contend that MBSE and other SE methods and techniques could improve HSs design, operations, and management; while fostering resilience and long‐term sustainability. [ABSTRACT FROM AUTHOR]

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Aim: Advanced therapy medicinal products (ATMPs) are medicines for human use that are based on genes, tissues or cells. They offer groundbreaking new opportunities for the treatment of disease and injury. However, ATMP adoption requires adjustments to current clinical practices and frameworks. This study investigates the readiness of the Irish healthcare system to adopt licensed ATMPs. Materials & methods: Scoping review, guided by the preferred reporting items for systematic reviews and meta-analyses – scoping review extension. A systematic search of English articles from 2013 to 2023 (published and grey literature) will be conducted. Results: Findings will be presented via narrative summary, graphical and tabular formats. Discussion: Review findings will be discussed in the context of recommendations that will inform national policy and strategy on the adoption of ATMPs in Ireland. Plain Language Summary This study examines whether Ireland's healthcare system is ready to use new kinds of medicines called advanced therapy medicinal products (ATMPs). These medicines are made from genes, tissues or cells and can be effective in treating certain diseases. However, delivering these medicines might mean changing current practices in clinics and hospitals. A scoping review will examine publications from 2013 to 2023 that focus on this topic. Results will be reported via narrative summary, graphs and tables. A discussion of the findings will be completed to inform recommendations for preparing the Irish healthcare system to deliver ATMPs. Ethics and dissemination: Ethical approval is not required for this scoping review. Findings will be disseminated through publication, stakeholder meetings and public engagement. Article highlights Advanced therapy medicinal products (ATMPs) are medicines for human use that are based on genes, tissues or cells. The Irish healthcare system's readiness for adopting ATMPs is unclear and, to the best of the authors' knowledge, has not been explored previously. A scoping review was chosen as the best way to investigate this topic. This scoping review protocol aims to detail the aims of this scoping review and how it will be structured. The scoping review detailed in this scoping review protocol aims to assess the readiness of the Irish Healthcare system to adopt licensed ATMPs and identify necessary changes required to strategically position the Irish healthcare system for future ATMP adoption. This scoping review will be in accordance with the Joanna Briggs Institute PRISMA-Scr approach. Both published and grey literature in English from 2013 to 2023 will be considered. The population, concept, context (PCC) framework will dictate eligibility for inclusion to the review. A previously published framework on ATMP adoption will be used to specify the concept of 'institutional readiness'. We anticipate that the results of this review will help identify gaps in current research relating to the adoption of ATMPs within the Irish healthcare system. We anticipate that these results will also inform future national policy relating to the adoption of ATMPs within the Irish healthcare system. Results will be summarized descriptively using a narrative approach and using summary tables. The findings of the research will be submitted to relevant peer-reviewed journals for publication. [ABSTRACT FROM AUTHOR]

Aim: To explore factors that influence the impact of nurse practitioners' clinical autonomy with a self‐determining perspective. Background: Worldwide, there is a significant demand for healthcare professionals such as the nurse practitioner in meeting some healthcare needs across patients' lifespans. Factors influencing nurse practitioners clinical autonomy can impact the full utilisation of the role in practice. Introduction: Limited evidence exists that describes or researches nurse practitioner clinical autonomy. Instead, there is a focus in the literature on strategic debates, role confusion and nurse practitioners reporting the straddling between nursing, allied heath professionals and medicine in the provision of healthcare services. Design: A cross‐sectional study design was used in a purposive sample in a national sample of nurse practitioners in Ireland across a full range of healthcare settings. Additionally, the survey included open comments sections to capture qualitative comments by the nurse practitioners themselves. Methods: Self‐determination theory is rooted in an organismic dialectical stance. This study used a convenience sample of n = 148 from a total sample of n = 448 (33%) of the population. The Dempster Practice Behavioural Scale and an initially validated advanced nursing practice clinical autonomy scale were used. Open comments were analysed by thematic analysis. STROBE Standards guidelines for cross‐sectional studies were followed, and COREQ guidelines were followed for writing qualitative research. Results: The study findings demonstrated that the more clinical experience the nurse practitioner had, the higher their levels of clinical autonomy. The previous length of nursing experience did not impact nurse practitioner clinical autonomy levels. However, average experience of nurse practitioner' in this study was 3–10 years. No significant differences existed between the reported gender, nurse practitioners' clinical autonomy and decision‐making. 1:40 female and 1:9 male nurse practitioners undertook a doctorate or PhD‐level education. No advanced nurse practitioner identified as non‐binary. Gender and organisational culture considerations can influence nurse practitioners clinical autonomy. Implications for nursing and health policy: This study highlights intrinsic motivators that support nurse practitioners in providing innovative healthcare: competence, relatedness and clinical autonomy. Countries credentialing, regulations professional standards and healthcare policy positively influence nurse practitioner clinical autonomy. Nurse practitioners' clinical autonomy is championed when health policy and organisational stakeholders intrinsically collaborate. A disconnect between health policy organisational culture extrinsically influences lower levels of nurse practitioners' clinical autonomy. Conclusion: The findings underline the positive impact of nurse practitioner clinical autonomy. A recommendation of this study is to continue to measure impact of clinical autonomy and develop nurse practitioners' self‐determination strategies around the role and integrity of their levels of intrinsic clinical autonomy. [ABSTRACT FROM AUTHOR]

By integrating energy-efficient AIoT-based biosensor networks, healthcare systems can now predict COVID-19 outbreaks with unprecedented accuracy and speed, revolutionizing early detection and intervention strategies. Therefore, this paper explores the rapid growth of electronic technology in today's environment, driven by the proliferation of advanced devices capable of monitoring and controlling various healthcare systems. However, these devices' limited resources necessitate optimizing their utilization. To tackle this concern, we propose an enhanced Artificial Intelligence of Things (AIoT) system that utilizes the networking capabilities of IoT biosensors to forecast potential COVID-19 outbreaks. The system aims to efficiently collect data from deployed sensor nodes, enabling accurate predictions of possible disease outbreaks. By collecting and pre-processing diverse parameters from IoT nodes, such as body temperature (measured non-invasively using the open-source thermal camera TermoDeep), population density, age (captured via smartwatches), and blood glucose (collected via the CGM system), we enable the AI system to make accurate predictions. The model's efficacy was evaluated through performance metrics like the confusion matrix, F1 score, precision, and recall, demonstrating the optimal potential of the IoT-based wireless sensor network for predicting COVID-19 outbreaks in healthcare systems. [ABSTRACT FROM AUTHOR]

Background Over the last two decades, inherited cardiac conditions (ICC) centres have emerged with the aim of improving outcomes for patients and their families, through early diagnosis, genetic testing, risk assessment and specialist treatment. Sources of data A literature search was performed using PubMed (https://pubmed.ncbi.nlm.nih.gov/). Commissioned ICC service reviews from NHS England, NHS Improvement and PHG Foundation were evaluated. Areas of agreement ICC patient management requires a multi-disciplinary approach. ICC services are predominantly based within tertiary centres. Despite expansion, provision of care remains inadequate to meet rising demands. Access to services is inconsistent, partly due to geographic variation and lack of standardized pathways. Areas of controversy The optimal ICC care model remains undecided, although there is growing interest in 'hub-and-spoke' networks, which could aid secondary and tertiary service integration and repatriation of care. Growing points Genetic mainstreaming is a priority for the Genomic Medicine Service Alliance. The benefits of telehealth and virtual clinics have been validated by their use during the COVID-19 pandemic. Other innovations to improve resource efficiency, such as clinical scientist–led and nurse-led clinics, show promise. Areas timely for developing research An update for the NHS ICC service specifications is planned that appears well timed given the rapid evolution of the ICC landscape in the decade since last review. This has the potential to address needs including national audit, standardized pathways and ICC networks to improve governance and equity of care. Delegation of commissioning for specialist services to integrated care systems may also provide opportunity for increased regional direction. [ABSTRACT FROM AUTHOR]

Puerto Rico (PR) is facing an unprecedented healthcare crisis due to accelerating migration of physicians to the mainland United States (US), leaving residents with diminishing healthcare and excessively long provider wait times. While scholars and journalists have identified economic factors driving physician migration, our study analyzes the effects of spatial stigma within the broader context of coloniality as unexamined dimensions of physician loss. Drawing on 50 semi‐structured interviews with physicians throughout PR and the US, we identified how stigmatizing meanings are attached to PR, its people, and its biomedical system, often incorporating colonial notions of the island's presumed backwardness, lagging medical technology, and lack of cutting‐edge career opportunities. We conclude that in addition to economically motivated policies, efforts to curb physician migration should also address globally circulating ideas about PR, acknowledge their roots in coloniality, and valorize local responses to the crisis that are in danger of being lost to history. [ABSTRACT FROM AUTHOR]

Background: Neonatal jaundice is a common condition that can lead to brain damage and disabilities when severe cases go undetected. Low- and middle-income countries often lack accurate methods for detecting neonatal jaundice and rely on visual assessment, resulting in a higher incidence of adverse consequences. Picterus Jaundice Pro (Picterus JP), an easy-to-use and affordable smartphone-based screening device for the condition, has demonstrated higher accuracy than visual assessment in Norwegian, Philippine and Mexican newborns. This study aimed to identify the barriers and facilitators to implementing Picterus JP in public health services in low-income settings in Mexico by exploring the current process of neonatal jaundice detection and stakeholders' perspectives in that context. Methods: Qualitative data collection techniques, including one focus group, 15 semi-structured interviews and four observations, were employed in urban and rural health facilities in Oaxaca, Mexico. The participants included medical doctors, nurses and health administrators. The data were analysed by thematic analysis guided by the Consolidated Framework for Implementation Research. Results: The analysis yielded four main themes: (I) the current state of neonatal care and NNJ detection, (II) the needs and desires for enhancing NNJ detection, (III) the barriers and facilitators to implementing Picterus JP in the health system and (IV) HCWs' expectations of Picterus JP. The findings identify deficiencies in the current neonatal jaundice detection process and the participants' desire for a more accurate method. Picterus JP was perceived as easy to use, useful and compatible with the work routine, but barriers to adoption were identified, including internet deficiencies and costs. Conclusions: The introduction of Picterus JP as a supporting tool to screen for neonatal jaundice is promising but contextual barriers in the setting must be addressed for successful implementation. There is also an opportunity to optimise visual assessment to improve detection of neonatal jaundice. [ABSTRACT FROM AUTHOR]

As we learn to co-exist with COVID-19, this Research Topic highlights significant research contributions that examine the interaction of COVID-19 and the social determinants of health. To emphasize the impactful research in this area, this Research Topic features scholarly contributions in the fields of Epidemiology, specifically Aging and Life-course Epidemiology, and Public Health, specifically Public Health Policy. This theme is intentionally broad in scope, and our editorial provides an overview of the key findings of the papers published in the Research Topic on COVID-19 pandemic and the social determinants of health. The types of articles received in response to this Research Topic are summarized below. [ABSTRACT FROM AUTHOR]

Categorizing Artificial Intelligence of Medical Things (AIoMT) devices within the realm of standard Internet of Things (IoT) and Internet of Medical Things (IoMT) devices, particularly at the server and computational layers, poses a formidable challenge. In this paper, we present a novel methodology for categorizing AIoMT devices through the application of decentralized processing, referred to as "Federated Learning" (FL). Our approach involves deploying a system on standard IoT devices and labeled IoMT devices for training purposes and attribute extraction. Through this process, we extract and map the interconnected attributes from a global federated cum aggression server. The aim of this terminology is to extract interdependent devices via federated learning, ensuring data privacy and adherence to operational policies. Consequently, a global training dataset repository is coordinated to establish a centralized indexing and synchronization knowledge repository. The categorization process employs generic labels for devices transmitting medical data through regular communication channels. We evaluate our proposed methodology across a variety of IoT, IoMT, and AIoMT devices, demonstrating effective classification and labeling. Our technique yields a reliable categorization index for facilitating efficient access and optimization of medical devices within global servers. [ABSTRACT FROM AUTHOR]

Background: The national e-prescription system in Greece is one of the most important achievements in the e-health sector. Healthcare professionals' feedback is essential to ensure the introduced system tends to their needs and reduces their everyday workload. The number of surveys collecting the users' views is limited, while the existing studies include only a small number of participants. Methods: In this study, healthcare professionals' perceptions on e-prescription are explored. For this, a questionnaire was distributed online, containing closed- and open-ended questions aiming to address strengths and identify drawbacks in e-prescription. Answers were collected from primary health care physicians, specialized medical doctors and pharmacists. Results: In total, 430 answers were collected (129 from primary health care physicians, 164 responses from specialized medical doctors and 137 pharmacists). Analysis of the collected answers reveals that the views of the three groups of healthcare professionals mostly converge. The positive impact e-prescribing systems have on the overall prescribing procedure in preventing errors and providing automation is commented. Among gaps identified and proposed improvements, health care professionals note the need for access to information on adverse drug reactions, side effects, drug-to-drug interactions and allergies. Flexible interaction with Therapeutic Prescription Protocols is desired to ameliorate monitoring and decision-making, while drug dosing features, and simplified procedures for copying, repeating, canceling a prescription, are perceived as useful to incorporate. Conclusions: Collecting healthcare professionals' feedback is important, as their views can be transcribed to system requirements, to further promote e-prescribing and improve the provided health care services by facilitating decision making through safer and more efficient e-prescription. Introduction of the identified improvements can simplify the everyday workflow of healthcare professionals. To the best of our knowledge, a survey with more than 400 answered questionnaires on the use of e-prescription systems by healthcare professionals has never been conducted in Greece before. [ABSTRACT FROM AUTHOR]

Regulatory marketing authorisation is not enough to ensure patient access to new medicinal products. Health Technology Assessment bodies may require data on effectiveness, relative effectiveness, and cost-effectiveness. Healthcare systems may require data on clinical utility, savings, and budget impact. Furthermore, the exact requirements of these bodies vary country by country and sometimes even region to region, resulting in a patchwork of different data requirements to achieve effective, reimbursed patient access to new therapies. In addition, clinicians require data to make informed clinical management decisions. This requirement is of key importance in rare diseases where there is often limited data and clinical experience at the time of regulatory approval. This paper describes an innovative initiative that is called Project SATURN: Systematic Accumulation of Treatment practices and Utilization, Real world evidence, and Natural history data for the rare disease Osteogenesis Imperfecta. The objective of this project is to generate a common core dataset by utilising existing data sources to meet the needs of the various stakeholders and avoiding fragmentation through multiple approaches (e.g., a series of individual national requests/approaches, and unconnected with the regulators' potential requirements). It is expected that such an approach will reduce the time for patient access to life-changing medications. Whilst Project SATURN applies to Osteogenesis Imperfecta, it is anticipated that the principles could also be applied to other rare diseases and reduce the time for patient access to new medications. [ABSTRACT FROM AUTHOR]

In the present scenario, Information technology has emerged rapidly in various sectors. But, it has various barriers in securing the information during the process, storage, transmission, and retrieval. Past few decades, it has entered the doors of the medical field. Recently, the confidential information of the health care system oscillates with security and privacy. It is significant to secure the patients' data, which is engendered by several healthcare systems. For researchers, those data are of great value; in addition, could help in understanding phenomena and conquering particular challenges. Since this information refers to the patient's personal data, it must be treated as confidential. An adverse effect might be caused by the unauthorized disclosure of patients' personal information. Hence, by employing Hospital id Patient id Central or State Govt. id – ROT Digit Folding Shift Left OR – BLAKE (HPCSG- ROTDF-SLORB) and Diffie Hellman Secret Key – Double Elliptic Curve Cryptography (DHSK-DECC), an efficient Cipher Hashing-based user authentication and Secure Data Transfer along with Block Chain-based (BC) User Verification are proposed for surpassing those issues. For generating strong credentials for authentication, the HPCSG-ROTDF is wielded. For converting the cipher text into hash code, SLOR-BLAKE is deployed. By employing DHSK-DECC, the data is encrypted and decrypted for enhancing data security. Regarding several metrics, the performances of the proposed system were analyzed. As per the outcomes, the proposed system exhibited enhanced performance when analogized to the prevailing methodologies. [ABSTRACT FROM AUTHOR]

Digital scans are extensively used in e-healthcare systems, necessitating increased authenticity and integrity of medical records due to security concerns during data transmission. This study presents a hybrid and robust watermarking solution for medical color scans, leveraging the RPCA-DCT-RSVD approach, which combines Robust Principal Component Analysis (RPCA), Discrete Cosine Transform (DCT), and Randomised Singular Value Decomposition (RSVD). The system incorporates invisible dual watermarking with a high embedding capacity and enhances security through Arnold Cat Map (ACM) and Joint Permutation and Diffusion (JPD). Various medical scans from different modalities were tested, and the system achieved an average peak signal-to-noise ratio (PSNR) of 51.90 dB, structural similarity index (SSIM) of 0.9991, normalized correlation (NC) of 1, and bit error rate (BER) of 0, with an embedding capacity of 5120 bits. Comparative analysis with existing methodologies demonstrates superior robustness, embedding capacity, and security performance. This proposed system offers an effective solution for ensuring the authenticity and integrity of medical records in e-healthcare systems. [ABSTRACT FROM AUTHOR]

Achieving blockbuster status requires more than clinical trial success. Crucial barriers often include real-world factors like patient acceptance, prescriber behavior and timely and full reimbursement. Implementation science can be used to identify such barriers, develop strategies to overcome them, as well as test their effect. Used correctly and at the right time, implementation science can amplify product value and lead to a triple win for patients, healthcare systems and pharma. Three easy steps that focus on context, strategies and outcomes, can be followed by pharma to bring implementation thinking and research into their processes. A ‘what if’ case study is shared to give an indication of how this might work and the impact it might have.

Climate change is a public health crisis predominantly due to fossil fuel combustion, that challenges planetary and human health. Considerable evidence exists to demonstrate the impact climate change has on cardiovascular disease primarily through air pollution, and non-optimal temperature. Conversely, healthcare systems themselves contribute substantially to climate change. Many clinicians personally report a sense of responsibility to reduce the detrimental impact of parts of our healthcare system on the environment. Roadmaps exist to guide decarbonization and reduce pollution in the healthcare sector. The first step in minimizing the climate impact of the provision of cardiovascular care is to determine the carbon footprint of highly resource dependent sectors such as critical care cardiology as well as the cardiac catheterization and electrophysiology laboratories. This should be followed by sustainable changes to address healthcare waste and energy use. Engagement from healthcare leadership, governmental organizations and major cardiac societies will be necessary to impact meaningful change.

Climate resilient development (CRD) is a future-focused solutions framework encapsulating climate adaptation and mitigation activities. It aims to prevent and prepare for the worst impacts of climate change whilst supporting sustainable development. When considering sustainability in healthcare systems, CRD goes beyond the current narrow focus on adaptation and mitigation to a more productive and integrated focus on how healthcare systems must equitably develop and transform to preserve the interconnected health of human and natural systems.The field of governance has received insufficient attention as a key determinant of CRD in healthcare systems, despite being a crucial enabling condition. It is through governance that climate resilient development policies are created, supported, implemented, and monitored. In this perspective we share a review that found no papers concerning how governance can enable CRD of healthcare systems followed by a broadened search which revealed a growing focus on elements of CRD (climate adaptation and mitigation) and barriers to climate adaptation and mitigation in healthcare systems.To respond to this gap, this perspective suggests there is value in jointly considering healthcare systems, climate resilient development and governance. We argue that transdisciplinary research combining these topics could provide practical and novel guidance for stakeholders involved in the pursuit of CRD of healthcare systems and could strengthen policy responses and actions.

Healthcare organizations must urgently prioritize interoperability to enhance the quality of care they provide. However, achieving this collaboration comes with numerous challenges, including differing approaches, data formats, and standards, as well as concerns about privacy, security, technical complexity, and legal and regulatory issues. To tackle these challenges, we determined a set of interoperability solutions. We also developed a comprehensive, component-based, data-driven framework for healthcare systems. Our study's approach involved three main steps: first, conducting a literature review to gather interoperability requirements and solutions from online databases and grey literature; second, carrying out a qualitative study to develop a framework based on the review results and focus group discussions; and third, using the Delphi method to validate the framework with experts. We extracted information from 36 articles during the screening and assessment process. Based on the proposed framework, we organized the identified themes into various categories, including architecture, architecture components, standards, platforms, policies, data sources, consumers, applications, level of interoperability, healthcare facilities, and considerations. Experts believe that establishing a comprehensive architecture for launching interoperability between health information systems can greatly facilitate this process. All framework components (totaling 197) received unanimous approval. The landscape of healthcare delivery is shifting from a focus on diseases to a patient-centered, data-driven approach. There is a growing demand for personalized healthcare systems, which necessitates increased interoperability among all healthcare stakeholders, particularly when dealing with diverse types of data. Our framework is designed to facilitate the implementation of various types of interoperability in healthcare systems.