Health Care Model Research Articles

A benchmarking and evidence-informed gap analysis of the hemodialysis care provision in Iran

BackgroundPatients with end stage renal disease (ESRD) are increasing worldwide. This is especially paramount in low and middle income countries in which ESRD patients are struggling to access specialist services e.g. hemodialysis (HD). Benchmarking analysis of the offered healthcare packages in several countries and comparison of the utilized alternative healthcare models for ESRD patients may be auspicious for institutional capacity-building in the existing healthcare facilities. Main aim of this study was to perform a benchmarking and evidence-informed gap analysis of the ESRD care provision in Iran and recognize the gaps that cause diversification in care quality for ESRD patients that hinder efforts for care quality improvement in the Iranian National Healthcare System.MethodsDimensions of the Australian Anglicare Southern Queensland Clinical and Care Governance Framework (ASQCGF) were utilized as corner stones of a comprehensive clinical care plan that is essential in responding to HD patients’ needs in Iran. An extensive literature search was performed at the next stage to recognize the gold standard core elements. The ascertained components were assigned to the five separate dimensions of the ASQCGF and a preliminary draft (comprehensive package of care for HD patients) was prepared. A checklist was developed at a later stage which was sent to a panel of expert consisting professional healthcare providers in nephrology and hemodialysis wards for their opinions. A gap analysis was conducted to evaluate current care processes of the Iranian HD patients align with the elements of the gold standard framework.ResultsThe identified deficits were classified in five areas in accord with the elements of ASQCGF as follow: A) supply of resources, medical devices and equipment support B) recruitment and endorsement of clinics and general work force C) infection prevention and controlling procedures D) care effectiveness monitoring and quality improvement E) provision of safe environment for both HD patients and hospitals’ staff.ConclusionsThe study findings revealed considerable gaps in providing quality HD services to the Iranian HD patients that herald their therapeutic unmet needs and the shift that is needed to narrow down the widening organizational failure which fuels the current disenchantment among the both healthcare providers and HD patients.

An innovative model of behavioral healthcare for older adults with serious mental illness, substance use disorders, and dementia.

Older adults with serious mental illness (SMI) experience higher rates of medical comorbidities, mortality, hospital readmissions, and total healthcare spending when compared with Medicare beneficiaries without SMI. Although telehealth provides an opportunity to overcome barriers to behavioral healthcare access, older adults face unique challenges when accessing and utilizing telehealth services. We present Author Health's care model, which integrates virtual-first behavioral health care with an interdisciplinary approach to health-related social needs (HRSN) screening and intervention in older adults. We launched an innovative behavioral healthcare delivery model in collaboration with primary care for Medicare Advantage recipients with SMI, substance use disorders (SUD), and dementia. All patients completed an intake with an MD/NP and were offered screening for HRSN at entry using the Accountable Health Communities HRSN tool. Primary diagnosis was assigned and categorized into SMI/SUD/dementia and non-SMI. Logistic regression was used to quantify the odds of food, housing, and transportation insecurity explained by SMI/SUD/dementia versus non-SMI behavioral health conditions. A total of 2301 patients completed an intake from January 2023 to March 2024. Moderate/severe depression (40%) was the most common primary target condition at intake, followed by dementia/Alzheimer's disease (12%) and bipolar disorder (5%). The rates of housing insecurity, food insecurity, and transportation insecurity were 27%, 30%, and 21%, respectively. Within our sample of Medicare Advantage participants in Florida, patients with SMI/SUD/dementia were 1.42 times (p < 0.05) and 1.58 times (p < 0.01) more likely to report housing insecurity and food insecurity, respectively, when compared with those with mild/moderate behavioral health conditions. Author Health provides a blueprint for behavioral health services that remove barriers and provide tenacious, consistent, and whole-person virtual-first behavioral health care tailored to the unique needs of older adults. Our sample of Medicare Advantage participants in Florida suggests SMI/SUD/dementia may be a predictor for HRSN independent of socioeconomic status and race/ethnicity.

A novel recommender framework with chatbot to stratify heart attack risk

Cardiovascular diseases are a major cause of mortality and morbidity. Fast detection of life-threatening emergency events and an earlier start of the therapy would save many lives and reduce successive disabilities. Understanding the specific risk factors associated with heart attack and the degree of association is crucial in the clinical diagnosis. Considering the potential benefits of intelligent models in healthcare, many researchers have developed a variety of machine learning (ML)-based models to identify patients at risk of a heart attack. However, the common problem of previous works that used ML concepts was the lack of transparency in black-box models, which makes it difficult to understand how the model made the prediction. In this study, an automated smart recommender system (Explainable Artificial Intelligence) for heart attack prediction and risk stratification was developed. For the purpose, the CatBoost classifier was applied as the initial step. Then, the SHAP (SHapley Additive exPlanation) explainable algorithm was employed to determine reasons behind high or low risk classification. The recommender system can provide insights into the reasoning behind the predictions, including group-based and patient-specific explanations. In the final step, we integrated a Large Language Model (LLM) called BioMistral for chatting functionally to talk to users based on the model output as a digital doctor for consultation. Our smart recommender system achieved high accuracy in predicting a patient risk level with an average AUC of 0.88 and can explain the results transparently. Moreover, a Django-based online application that uses patient data to update medical information about an individual’s heart attack risk was created. The LLM chatbot component would answer user questions about heart attacks and serve as a virtual companion on the route to heart health, our system also can locate nearby hospitals by applying Google Maps API and alert the users. The recommender system could improve patient management and lower heart attack risk while timely therapy aids in avoiding subsequent disabilities.

Research on Sports Injury Rehabilitation Detection Based on IoT Models for Digital Health Care.

Physical therapists specializing in sports rehabilitation detection help injured athletes recover from their wounds and avoid further harm. Sports rehabilitators treat not just commonplace sports injuries but also work-related musculoskeletal injuries, discomfort, and disorders. Sensor-equipped Internet of Things (IoT) monitors the real-time location of medical equipment such as scooters, cardioverters, nebulizer treatments, oxygenation pumps, or other monitor gear. Analysis of medicine deployment across sites is possible in real time. Health care delivery based on digital technology to improve access, affordability, and sustainability of medical treatment is known as digital health care. The challenging characteristics of such sports injury rehabilitation for digital health care are playing position, game strategies, and cybersecurity. Hence, in this research, health care IoT-enabled body area networks (HIoT-BAN) have been designed to improve sports injury rehabilitation detection for digital health care. The health care sector may benefit significantly from IoT adoption since it allows for enhanced patient safety; health care investment management includes controlling the hospital's pharmaceutical stock and monitoring the heat and humidity levels. Digital health describes a group of programmers made to aid health care delivery, whether by assisting with clinical decision-making or streamlining back-end operations in health care institutions. A HIoT-BAN effectively predicts the rise in sports injury rehabilitation detection with faster digital health care based on IoT. The research concludes that the HIoT-BAN effectively indicates sports injury rehabilitation detection for digital health care. The experimental analysis of HIoT-BAN outperforms the IoT method in terms of performance, accuracy, prediction ratio, and mean square error rate.

Politics of the French empire in the east Adriatic coast (1809–1814)

The article processes the period of the French Empire’s rule on the east Adriatic coast between 1809 and 1814. Based on the relevant literature and historical sources, the article points to events that followed Campo Formio's peace in 1797 until the destruction of French rule in 1814. Special focus is placed on the activities of the new rulers, based on the ideas of the French revolutions, which sought to transform the area of east Adriatic and integrate it into the state system of the French empire, with the goal of creating a united political, administrative, militaristic, economic and cultural-educational area. In that context, in the article, the main question being examined is the formation of the Illyrian provinces, which were intended to be a separate province of the French empire, which was supposed to unite different national and religious communities that spoke the same language. With a comprehensive analysis of political and social changes, an attempt is made to point to a pioneer attempt to transform a patriarchal and traditional community, through the implementation of modern models of public administration, healthcare, and education.

“When in Rome…”: structural determinants impacting healthcare access, health outcomes, and well-being of South Asian older adults in Ontario using a multilingual qualitative approach

With the increase in international migration, the need for an equitable healthcare system in Canada is increasing. The current biomedical model of healthcare is constructed largely in the Eurocentric tradition of medicine, which often disregards the diverse health perspectives of Canada’s racialized immigrant older adults. As a result, current healthcare approaches (adopted in the US and Canada) fall short in addressing the health needs of a considerable segment of the population, impeding their ability to access healthcare services. This study aimed to identify and understand the structural and systemic factors that influence healthcare experiences and well-being among South Asian older adults in Ontario, addressing a significant gap in empirical and theoretical knowledge in the Canadian context. We conducted in-depth individual and dyadic interviews (n = 28) utilizing a descriptive multilingual cross-cultural qualitative approach. Through this research, participants expressed that their understanding of well-being does not align with that of their healthcare providers, resulting in unmet health needs. Our study uses an intersectional lens to demonstrate participants’ perceptions of virtual access to care and systemic factors, such as mandatory assimilation and whiteness as a taken-for-granted norm impacting the health and well-being of South Asian older adults. The findings of this research can offer valuable insights to healthcare providers and policymakers in developing culturally competent practices, guidelines, and training policies that effectively address the healthcare needs of the South Asian population in Canada.

Designing recovery-oriented care: a qualitative study to inform service design at Kyrie Therapeutic Farm in Ireland.

Recovery-oriented approaches are gaining increased attention in the mental health sector, including from the World Health Organization and the United Nations, for their potential to support people in recovering and building meaningful lives through strengths-based, person-centered principles. Kyrie Therapeutic Farm (KTF) is a new initiative in Ireland that seeks to develop recovery-oriented model of adult mental health care. The aim of this study was to explore the barriers and facilitators of recovery-oriented models of practice in a small number of therapeutic farm settings across the world in order to inform service design at KTF whilst also addressing a gap in research on this topic. Three semi-structured focus-group interviews were conducted online via MS Teams with ten staff members in different roles and years of experience from three existing therapeutic community farms. reflexive thematic analysis was employed for data analysis. Four themes emerged that illustrate how therapeutic farm communities operate in general and specifically in relation to recovery: 1. common humanity, 2. freedom and responsibility, 3. interdependence and community living, and 4. learning organisations. This study demonstrates the viability of recovery-oriented practices in community therapeutic farms, including KTF, thereby contributing to the broader trend toward more person-centered mental health services. The values inherent in the recovery-oriented approach - such as community, empowerment, and close, equitable, non-hierarchical relationships - act as facilitators. However, embedding these values in practice can generate tensions for staff which warrant attention. Implications for the integration into service design of KTF and further research are offered.

From structures to systems: towards a model of ethical healthcare

ABSTRACT “Hurt people hurt people” is a phrase which summarises the cyclical nature of painful experiences and harmful actions. Arguably, this cycle of hurt and harm applies to the UK’s National Health Service (NHS), where employees are reporting record low levels of physical and mental wellbeing, while experiencing a climate of hostility, bullying and harassment, and pressures to meet targets. Such working environments carry several risks, not only for the employees themselves but also in terms of clinical outcomes for patients. As a result, a range of systemic and targeted infrastructure interventions have been trialled in several NHS hospitals (managed in the UK by independent Trusts), seeking to promote a culture of compassion, and improve the psychological safety of workers. However, the effectiveness of such measures in achieving ethical working environments and preventing unethical behaviours, has been questioned. We join the ongoing debate by proposing the need to go beyond ethical infrastructures and instead consider ethical environments in their systemic complexity. We conclude, by putting forward a model of a complex and ethical health system, which incorporates workplace networks, policy frameworks, and accounts for regional demographics.

Factors associated with transition readiness among adolescents and young adults with spina bifida in South Korea.

This study aimed to examine the factors associated with transition readiness based on the healthcare transition model among adolescents and young adults (AYAs) with spina bifida (SB) in the individual (self-management and self-efficacy), family or social support (family function and social support), healthcare system, and environmental (transition environment) domains. Using face-to-face and online surveys, we conducted a cross-sectional study on AYAs with SB in South Korea. The participants were aged 13-25 years. Data were analyzed using descriptive statistics, t test, one-way analysis of variance, Pearson's correlation coefficients, and multiple regression analysis. A total of 110 AYAs with SB participated in this study. Their mean age was 19.85 (SD = 3.65) years. The mean score of transition readiness was 3.89 (SD = 0.70) out of 5. Transition readiness was statistically significantly associated with general (age), clinical (mobility), and individual (self-management) characteristics and family or social support (social support) and the healthcare system. These results suggest that it is necessary to develop tailored transition care programs that consider factors associated with transition readiness for AYAs with SB. The findings of this study increase our understanding of the transition readiness of AYAs with SB, which can help in the development of effective transition strategies.

QMedShield: a novel quantum chaos-based image encryption scheme for secure medical image storage in the cloud

In the age of digital technology, medical images play an important role in the healthcare industry, which aids surgeons in making precise decisions and reducing the diagnosis time. However, the storage of large amounts of these images in third-party cloud services raises privacy and security concerns. There are a lot of classical security mechanisms to protect them. Although, the advent of quantum computing entails the development of quantum-based encryption models for healthcare. There is a significant demand for resource-efficient, quantum-secure image encryption mechanisms that leverage existing classical infrastructure. Hence, in this paper, a novel quantum chaos-based encryption scheme for medical images has been introduced. The model utilizes bit-plane scrambling, a 3D quantum logistic map, quantum operations in the diffusion phase, a hybrid chaotic map, and DNA encoding in the confusion phase to transform the plain medical image into a cipher medical image. The proposed scheme has been evaluated using multiple statistical analyses and validated against more attacks such as differential attacks, known and chosen plaintext attacks with three different medical datasets, and theoretically, as well. Hence, the introduced encryption model has proved to be more attack-resistant and robust than other existing image encryption schemes, ensuring the secure storage of medical images in cloud environments.

A Qualitative Analysis of Trialogues Between People with Lived Experience, Their Relatives, and Mental Health Professionals.

Trialogue meetings, aligned with the Recovery model in mental healthcare, foster the development of a shared language and mutual understanding among persons with lived experience, their relatives, and professionals. This study analysed the first mental health trialogue experience in Barcelona, involving six meetings with thirteen voluntary participants over three months. Using qualitative methods for data collection and reflexive thematic analysis, three main themes emerged: Recovery process, Interaction with mental health services, and Trialogue dynamics. Benefits included open dialogues in a safe space, learning from diverse perspectives, and sharing expertise. The meetings created an environment of empathy and respect while promoting open communication. This approach holds substantial potential for transforming mental healthcare systems, suggesting trialogues can be an effective tool for enhancing communication within community-based mental health initiatives. The findings provide a comprehensive picture of the trialogue process, highlighting its potential to foster mutual understanding among participants.

The State of Medical Care for Adults With Intellectual and/or Developmental Disabilities.

For more than 2 decades, medical care for adults with intellectual and/or developmental disabilities (IDDs) has been difficult to access and has not substantially changed the persistently poor health status that is common in this population cohort. While there has been some progress in the development of models of care that are designed with and for adults with IDD, it has been slow and sporadic, with little data or analyses of efficacy or effectiveness. Very few medical schools and other health science professional education in the United States include curricular content on adults with IDD, resulting in health care practitioners being under or altogether unprepared to provide care to them. Public and private health care policy and financing are not responsive to the medical care needs and experiences of adults with IDD. More recently, the impact of the COVID-19 pandemic on adults with IDD was disproportionally more severe, with significantly higher rates of morbidity and mortality than on adults without IDD, having nothing to do with the presence of an IDD itself. This commentary reviews persistent barriers to accessible, responsive medical care for adults with IDD and reviews a number of health care models that have been developed since the turn of the 21st century. It also offers a brief review of Medicaid Managed Care as a potential policy and financing solution to long-standing financing and related obstacles to optimal medical care.

HOW FAMILY DNA CAN CAUSE LUNG CANCER USING MACHINE LEARNING

Lung cancer continues to be one of the leading causes of cancer-related mortality globally. While environmental factors, particularly smoking, are recognized as primary contributors, growing research shows that genetic predisposition, especially family-linked inheritance, plays a significant role in lung cancer susceptibility. Recent advancements in genomics and machine learning (ML) are providing new avenues for understanding these inherited risks. This review provides an in-depth analysis of how familial DNA influences lung cancer development, highlighting how machine learning models can be used to identify genetic markers associated with increased risk. By reviewing current findings and methodologies, we aim to bridge the gap between genetic susceptibility and the application of ML models in predictive healthcare.

Transforming community-based primary health care delivery through comprehensive performance measurement and reporting: examining the influence of context

BackgroundCommunity-based primary health care represents various community-based health care (CBPHC) models that incorporate health promotion and community development to deliver first-contact health services. Learning health systems (LHSs) are essential for improving CBPHC in which feedback from relevant stakeholders is used to continuously improve health systems with the goal of achieving population health and health equity. Performance reporting is one way to present data to clinicians and decision makers to facilitate a process of reflection, participation, and collaboration among partners to improve CBPHC.MethodsOur objective was to obtain feedback on a regional CBPHC performance portrait through key informant interviews. We used purposive convenience sampling to recruit participants who were clinicians in primary care and/or decision-makers in primary care at a regional level. The performance portrait summarized results of survey questions asked of patients, providers, and primary care organizations. The portrait was organized by the 10 pillars of the Patient’s Medical Home (PMH) model. Interview questions specifically asked about portrait content, formatting, interpretability, utility, and dissemination strategies. Content analysis was used to analyze interview data.ResultsWe completed 19 interviews with key informants from the Canadian provinces of Nova Scotia (n = 8), Ontario (n = 6) and British Columbia (n = 5). We coded transcripts into four content areas: (1) Usability as influenced by content and interpretability, (2) Formatting, (3) Utility, and (4) Dissemination. Using data and reporting back to clinicians and decision-makers about how their practices and jurisdictions are performing in primary care in meaningful ways is important. Our results suggest having available methodology notes, including the analysis used to develop any scoring, sampling and sample sizes, and interpretation of the statistics is necessary.ConclusionsThis research was the first to create a comprehensive performance portrait using data driven by factors that are important to primary care partners. We obtained important feedback on the portrait in the context of usability, formatting, utility, and dissemination. This data needs to be used to provide feedback in continuous cycles to evaluate and improve CBPHC models as part of a LHS.

Integration of large language models in Nigeria's healthcare: doctors early perspectives, operational barriers, and privacy concerns

The advent of large language models (LLMs) like ChatGPT has the potential to revolutionize healthcare, offering opportunities for improved patient engagement, clinical decision support, and administrative efficiency. This pioneering study aimed to capture the early perspectives of Nigerian medical professionals on LLMs, particularly ChatGPT, immediately following its 2022 introduction by OpenAI. It explores initial responses, anticipated barriers, and data privacy concerns during this transformative period. A nationwide cross-sectional survey was conducted between February and March 2023, involving 406 medical doctors across Nigeria's six geopolitical zones. Among those aware of ChatGPT, 66.9% were willing to use it. Most (41.4%) were "not very confident" using LLMs for patient care. The majority (54.0%) rated LLMs "somewhat important" for healthcare integration, and 76.6% believed they could improve outcomes. No explored factors significantly influenced willingness to use LLMs. Primary perceived benefits included improved patient information access (65.2%), clinical decision-making efficiency (57.7%), and patient-provider communication (46.4%). Major concerns were misinterpretation (80.1%), technology dependence (66.3%), liability (65.5%), lack of human interaction (60.7%), and privacy/security (51.3%). These findings highlight both optimism and apprehension towards LLMs, recognizing potential benefits and concerns about misinterpretation, overreliance, legal implications, and privacy, thus underscoring the need for educational programs, ethical frameworks, and robust data protection.

Tradeoffs When Building and Running Cohort and Patient-Level Markov Simulation Models

The choice of health care modeling approaches is driven by trade-offs between various modeling techniques. This study evaluates cohort (CH) versus patient-level (PL) Markov modeling techniques within a cost-effectiveness analysis framework to understand the practical decisions analysts face. Both the CH and PL models were constructed using identical datasets and similar assumptions. Each model included eight health states to capture disease severity and symptom types and allowed switching from first-line to second-line treatment. We assessed model outcomes and performance using various quantitative and qualitative techniques. The CH and PL models yielded very similar base case results; only minor differences in functionality and outcome consistency were detected. The CH model offered greater stability and easier parameter testing, while the PL model provided superior flexibility for structural adjustments and detailed patient pathway and subgroup analysis. However, the PL model required substantially more computational time for sensitivity analyses and more technical skills to understand and interpret patient pathways and model results. CH modeling faced more challenges when extensive structural changes were initiated. Choosing between CH and PL modeling techniques involves the careful assessment of trade-offs between the need for a flexible and informed model and the optimization of human and computational resources.

Implementing Best Practices for Nurses in Detecting and Reporting Adverse Drug Reactions in a Tertiary Hospital in Tabriz, Iran: A Mixed-Method Study.

According to the World Health Organization (WHO), an Adverse Drug Reaction (ADR) is defined as "a response to a drug which is noxious and unintended, and which occurs at doses normally used in humans for the prophylaxis, diagnosis, or therapy of disease, or for the modification of physiological function." The aim of this research was to evaluate the current practice and implement the best practices for detecting and reporting ADR in a tertiary hospital in Tabriz, Iran. We used a mixed-methods sequential explanatory design in the current study. The research was conceptually informed by the Joanna Briggs Institute model of Evidence-Based Healthcare (JBI EBHC). A three-phase implementation process, outlined by this model, was used in this study. The first and third phases comprised the quantitaive phase of the study, in which we evaluated the current practice and conducted a final evaluation to measure changes in compliance with the best practice. The qualitative phase, the second phase of the JBI EBHC model,was conducted to identify barriers and develop implementation strategies. There were seven evidence-based audit criteria for evaluating the practice, with a sample size of 23 nurses for the quantitative phase and 10 participants for the qualitative phase. The quantitative findings revealed an improvement in compliance rates for all criteria following the follow-up audit. From the qualitative analysis, four themes of barriers were identified: time and workload, lack of a proper reporting system for ADR, lack of belief and readiness for change among nurses, and lack of awareness about the importance of documenting ADR. The results of this implementation study demonstrated enhanced ADR reporting. It can be inferred that implementing educational strategies, such as holding conferences, informal meetings, workshops, and educational pamphlets, can facilitate the implementation of evidence into practice. Findings will help nurses across sectors of primary, secondary, and tertiary care use the implemented strategies to improve the quality of care and reduce ADR.

Retention in primary care among unstably housed residents of a low-income, inner-city neighborhood with a high prevalence of substance use and related disorders

IntroductionAccess to and engagement with primary healthcare can be difficult for marginalized low-income populations residing in inner cities in high-income countries. We designed a study to examine retention in primary care among clients of a novel interdisciplinary primary care clinic in the Downtown Eastside of Vancouver, Canada who did not previously have access to care.MethodsBeginning in June 2021, clients of the Hope to Health clinic were offered enrolment in a cohort study which involved a baseline and follow-up surveys every six months, and linking their data to information from the clinic’s electronic medical records. We used Chi-square or Fisher’s Exact test and Wilcoxon rank sum test to compare clients who were lost to follow-up (LTFU) or deceased, with clients who were retained in care at the end of follow-up, Cox proportional hazards modeling was used to examine independent associations with mortality or LTFU.ResultsAmong 425 participants enrolled, the median age was 50 years (IQR 40–59), 286 (67.3%) participants were men and 128 (25.4%) were unstably housed at enrollment. Among 338 participants with at least six months of follow-up after enrolment, 262 participants (67.5%) were retained in care, 20 (5.2%) had moved, 57 (14.7%) were classified as LTFU, and 28 (7.2%) had died with a median of 19.9 months of follow-up time. The risk of death or LTFU was independently associated diagnosed with alcohol use disorder (AUD) (adjusted hazard ratio [AHR] = 2.23 vs. not; 1.38–3.60), frequency of medical doctor visits (AHR = 0.69 per visit per 3 months; 0.60–0.79) and social work visits (AHR = 0.73 per visit per 3 months; 0.59–0.90. Stimulant use disorder or asthma were not significantly associated with retention in care.ConclusionWe found that a primary healthcare model of care was successful in retaining over two-thirds of clients in primary healthcare after more than 18 months of follow-up. Additional supports for those diagnosed with alcohol use disorder are needed to retain them in care.

Digital Transformation in Healthcare: A Case Study of the University of Ghana Medical Centre with a Particular Focus on SECTRA PACS

The University of Ghana Medical Centre LTD (UGMC) is a state-of-the-art facility that provides world-class quaternary health care, training, and research in Ghana and beyond. Located in Legon, Accra, UGMC epitomizes Ghanaian hospitality with a strong focus on customer service. Since its opening in 2018, UGMC has operated as a fully paperless facility, with all patient records generated, stored, and maintained digitally. This study aimed to explore digital transformation in healthcare using UGMC as a case study, particularly focusing on advancements made with SECTRA PACS amidst economic, legal, and ethical challenges. A multiple-case study design was used to explore how UGMC has been transformed digitally. The findings suggest that digital transformation is changing the face of the healthcare sector. This change should drive organizations to operate, grow, and innovate business models in healthcare and outline policies through ascertained digital advances while addressing legal, economic, and ethical considerations for successful healthcare digital transformations.

A qualitative exploration of knowledge attainment, safety practices and accessibility barriers to chest binding

ABSTRACT Objectives Chest binding is a common gender-affirming practice that transmasculine individuals can engage in for a range of reasons, including masculinising their physical appearance, which can facilitate gender euphoria, or alleviate gender dysphoria. In this study, we explored chest-binding experiences with a focus on knowledge attainment, understandings of safety and accessibility factors for those interested in binding. Method The study involved 15 semi-structured qualitative interviews with transmasculine people in Australia (aged 20–37 years) who have past or current chest binding experiences. These were analysed using thematic analysis. Results Data analysis resulted in the generation of four themes: 1) Online and social communities influence understandings of binding practices; (2) Learning about safety in binding is often self-directed; (3) Difficulties of navigating the application of safe binding within daily life, and (4) Common accessibility barriers to binding can be mitigated by trans communities. Conclusion The evidence in this study showed that chest-binding knowledge is acquired in diverse ways, and knowledge around safety and accessibility is not always readily available or easy to locate. However, participants unequivocally expressed that the practices are a crucial form of affirming care. Future research should continue to focus on creating strong, evidence-based affirming healthcare models for transmasculine Australians.