Areas Of Health Care Research Articles

Awareness and implementation of comprehensive genomic profiling and cancer support for adolescents and young adults among healthcare professionals in Osaka, Japan.

Comprehensive genomic profiling (CGP) and specialized support for adolescent and young adult (AYA) cancer patients are crucial yet underexplored areas of healthcare in Japan. This study investigated awareness of CGP testing and support for AYA cancer patients among healthcare professionals in Osaka. An anonymous online survey was conducted from 31 January to 31 March 2024. The survey targeted all staff, including doctors, nurses, technicians, pharmacists and others, from eight Toyono Medical Area Cancer Medical Network Council hospitals. The survey included questions on basic demographics, awareness of CGP testing and support provided to patients with AYA cancer. Among the 720 respondents, 41.9% were aware of CGP testing, while 20.3% were unaware. Regarding AYA cancer, 60.7% were aware and 14.3% were unaware. Only 7.5% had frequent contact with AYA patients and 96.8% recognized the need for education and information. Awareness of CGP was greater among doctors (72.5%) than among other professionals (34.4%); similarly, AYA cancer awareness was higher among doctors (73.9%) than among other professionals (57.7%). CGP awareness among doctors varied by years of experience and institutional type, being highest in core and cooperative hospitals (80 and 78.6%, respectively) and among doctors with more than 21years of experience (90%). This study reveals significant gaps in CGP and AYA cancer awareness among healthcare professionals in Osaka, Japan, with doctors demonstrating higher awareness levels than other professionals. There is a pressing need for targeted educational programs to enhance the understanding and implementation of CGP and support AYA cancer patients.

Unlocking the potential for microbiome-based therapeutics to address the sustainable development goal of good health and wellbeing.

Recent years have witnessed major advances and an ever-growing list of healthcare applications for microbiome-based therapeutics. However, these advances have disproportionately targeted diseases common in high-income countries (HICs). Within low- to middle-income countries (LMIC), opportunities for microbiome-based therapeutics include sexual health epidemics, maternal health, early life mortality, malnutrition, vaccine response and infectious diseases. In this review we detail the advances that have been achieved in microbiome-based therapeutics for these areas of healthcare and identify where further work is required. Current efforts to characterise microbiomes from LMICs will aid in targeting and optimisation of therapeutics and preventative strategies specifically suited to the unmet needs within these populations. Once achieved, opportunities from disease treatment and improved treatment efficacy through to disease prevention and vector control can be effectively addressed using probiotics and live biotherapeutics. Together these strategies have the potential to increase individual health, overcome logistical challenges and reduce overall medical, individual, societal and economic costs.

6.Y.2. AI and health care: what are the capabilities and limitations?

Abstract With the rapid advancement of artificial intelligence (AI) technologies and their implementation in health care, there is a critical need to explore the different applications and implications of AI. This workshop seeks to look at different aspects of AI, both potential applications for AI technology in health, public opinions of use of AI in health care, and the reality of implementing AI in different contexts. Understanding health care approaches to AI from different countries is a unique opportunity for shared learning of innovations across various sectors of health care and patient engagement in order to most effectively engage this emerging field. AI, in whichever form it may be incorporated into health care, has the opportunity to impart meaningful, innovative change, but understanding this new technology comes with important questions. This session will dive into research on AI in various areas of health care by 1) looking at different ways AI is being harnessed in health care; 2) discussing lessons which can be learned and adapted from other countries; 3) discussing promising solutions and approaches to implementing AI in health care; 4) discussing the limitations or concerns of integrating AI in health care. The panel will be composed of 1 moderator and 2 panelists. Panelists are experts in their fields, established researchers and practitioners, and alumni of the Harkness Fellowship from Germany and the United Kingdom. A moderator will briefly frame the discussion for the audience and introduce the speakers and their presentations before leading an interactive, engaging question and answer portion. The coherence of this panel lays in its theme of leveraging AI to enhance healthcare delivery and understanding ways we can work across countries to foster ethical, equitable AI technologies that revolutionize healthcare practices with the ultimate goal of improving patient outcomes and health system efficiencies. Dr. Saira Ghafur from the U.K. will begin by presenting her research on evidence-based reasons for implementing AI in health care and Dr. Benedikt Simon from Germany will close out by discussing his work in AI in Germany and the challenges that have prevented robust integration. Each panelist will speak for roughly 8-10 minutes, with about 5 minutes reserved for moderator and audience questions. Key messages • Sharing cross-country experiences and research enables us to better understand how AI can impact health care. • In weighing both the benefits and challenges or limitations of implementing AI, we can best understand effective approaches to utilizing AI in health care.

Experiences of treating people with persisting symptoms after COVID-19: a focus group study

Abstract Background A proportion of people who had COVID-19 infection continue to suffer with persistent symptoms. The long-term effects of COVID-19 are recognised as heterogeneous and complex, challenging health services. This study aims to explore the experiences of healthcare professionals dealing with patients suffering from persisting symptoms following COVID-19 infection and their views on the healthcare services response. Methods We held 4 focus groups (n = 19) with healthcare professionals by video-call. Healthcare professionals were recruited using a snowball strategy, taking level of care, healthcare area, and nature of function as diversification criteria. Participants were invited to tell their experiences regarding the following topics: experiences and challenges in providing care to patients with persisting symptoms following COVID-19 infection; usual care pathways; models of care. Data were recorded, transcribed, and anonymized. The qualitative data were submitted to thematic analysis following an inductive approach. A computer-assisted qualitative data analysis software (MaxQDA) was used. Results Based on thematic analysis, 4 core themes emerged: uncertainty; new condition, usual challenges; variable standards implementation; personalized and multilevel care. This new condition challenged health services and health professionals to keep adjusting and updating responses in a context of uncertainty, but at the same time revealed the usual challenges and needs for providing timely and integrated care. Health services burden challenges the implementation of care standards. This heterogeneous condition demands a multi-level response, including general information and advice, enabling self-management, and providing rehabilitation. Conclusions Healthcare professionals envision an heterogenous condition, bringing uncertainty to healthcare services. More research, training, and information to the population is required for an appropriate response. Key messages • Persisting symptoms following COVID-19 challenged an already overwhelmed health system, bringing barriers to healthcare standards implementation. • The heterogeneous nature of the condition and the healthcare services burden may leave some people to chance, demanding a diverse set of care.

Artificial intelligence to predict estimates of physical activity in small geographic areas

Abstract Background Artificial intelligence (AI) predictive models have been used to estimate the risk of a certain outcome occurring, using all available variables. Methods Using AI methods we have developed a small area estimation (SAE) technique to estimate the prevalence of leisure-time physical activity (LTPA), or who practices 150 minutes of LTPA per week, in small areas, in Belo Horizonte, Brazil, between 2009 and 2018, by the usage of k-means clustering. The VIGITEL, national telephone survey of Risk Factors for non-communicable diseases, was the main source. We applied available data to estimate prevalence of LTPA in 3300 census tracts, aggregated in 150 Primary Health Care (PHC) areas. The prevalence of PA was analyzed between two time periods, due to the low number of census tract interviews. With the available data, we estimate vulnerability clusters, derived from a Health Vulnerability Index (IVS), for the city of Belo Horizonte, according to socioeconomic, sanitation and health indicators, which measure the percentage of the population living in areas of vulnerability in the city. The index main purpose is to support public policy implementation. Results Nine clusters were identified according to the Silhouette coefficient analysis, i.e.: low (LO-0, LO-1), medium (ME-0, ME-1), high (HI-0, HI-1, HI-2) and very high) vulnerability (VH-0, VH-1. The prevalence of physical activity ranged from 23.7% (worst prevalence), in area of high vulnerability cluster (VH-1) to 45.5% in a low-risk cluster (LO-1) in period from 2009 to 2014. The prevalence of physical activity increased to 31.4% (high vulnerability cluster) to 52.81% (low-risk cluster) from 2014 to 2018. Conclusions The use of AI to estimate the prevalence of physical activity in small areas proved to be effective and highlighted important differences in the city. Thus, national surveys, with a small number of interviews per census sector, can be used to predict risks and health outcomes for small areas. Key messages • The study highlights the importance of using artificial intelligence to predict estimates of risk factors for chronic non-communicable diseases in small geographic areas. • The study showed less physical activity (PA) in areas of greater vulnerability. This can support health promotion policies and programs that encourage PA.

New evidence on household financial protection against out-of-pocket payments for health in Poland

Abstract Background Protecting households against financial hardship when using health care is an integral element of universal health coverage. Previous analysis showed that in Poland, catastrophic spending on health is more common than in many European countries. Over the last decade, several measures were undertaken to reduce the burden of out-of-pocket payments for households in Poland. Methods The study aimed to assess financial protection in Poland using the indicators of catastrophic and impoverishing health spending. It relies on the methodology developed by the WHO Region Office for Europe. Catastrophic expenditure is defined as out-of-pocket payments that are greater than 40% of household capacity to pay. The study uses data from the Polish household budget surveys in 2013-2021. Results The incidence of catastrophic health spending remained relatively constant over the years analyzed, with 9% of households affected. Only in the first year of the COVID-19 pandemic (2020) it reached nearly 10%, although overall household out-of-pocket expenditure declined that year. The share of households impoverished or further impoverished due to out-of-pocket payments decreased from 4% in 2013 to 3% in 2021. Payments on medicines are the main driver of catastrophic spending, particularly among poorer households, although their role has diminished over time. Household’s available resources, gender, age, education, disability status, residence place, number of children, and household’s main source of income are significantly associated with catastrophic health payments. Conclusions Despite the implemented policies, household financial protection against out-of-pocket payments in Poland did not improve significantly between 2013 and 2021. Available evidence should be used to design well-tailored measures to reduce the burden of out-of-pocket payments, targeting the most vulnerable population groups and specific healthcare areas. Key messages • Household financial protection against out-of-pocket payments in Poland did not improve significantly between 2013 and 2021. • Out-of-pocket payments for medicines are the main cause of financial hardship for Polish households.

From Code to Care: The Impact of Software Engineering and QA on Healthcare Delivery Systems

The rapid digitalization of healthcare has led to an unprecedented reliance on software systems to improve patient care, streamline operations, and ensure regulatory compliance. This article presents a comprehensive analysis of the critical role that software engineering and quality assurance (QA) play in three key areas of modern healthcare: Electronic Health Records (EHRs), telemedicine platforms, and medical device software. Through an examination of current practices, challenges, and case studies, we demonstrate how robust software engineering methodologies and rigorous QA processes contribute to the development of reliable, secure, and efficient healthcare applications. Our findings highlight the importance of data integrity, interoperability, user experience, and regulatory compliance in healthcare software development. Furthermore, we explore emerging trends such as artificial intelligence, blockchain, and the Internet of Medical Things (IoMT), discussing their implications for future software engineering and QA practices in healthcare. This article provides valuable insights for healthcare organizations, software developers, and policymakers, offering recommendations to enhance the quality and safety of software-driven healthcare solutions.

Expanding the primary care workforce by integrating genetic counselors in multidisciplinary care teams.

Collectively, rare diseases are common, affecting approximately 8% of the population in Canada and the USA. Therefore, the majority of primary care (PC) clinicians will care for patients who are affected or at risk for a genetic disease. Considering the increasing ways in which genetics is being implemented into all areas of healthcare, one way to address these needs and expand the capacity of the PC workforce is through the integration of genetic counselors (GCs) into PC multidisciplinary teams. GCs are Masters-educated allied health professionals with specialized training in molecular genetics, communication, and short-term psychotherapeutic counseling. The current models of GCs in PC mimic other multidisciplinary models. Complex tasks related to genetics, such as pre- and post-test counseling, genetic test selection, and results interpretation, are conducted by GCs, which, in turn, allows physicians, nurse practitioners, and other PC providers to work at the top of their scope of practice. Quality genetics services provided by GCs improve clinical outcomes for patients and their families; the simultaneous provision of genetic education and psychological support by a GC is associated with an increase in patient knowledge, perceived personal control, decrease in distress, and can lead to positive health behavior changes, all of which are aligned with the goals of primary healthcare. With their extensive training in clinical care, medical communication, and psychotherapeutic counseling, integrating GCs into PC care teams will improve the care patients receive and allow PC clinicians to ensure their patients are at the forefront of the personalized medicine revolution.

Developments in Advance Care Planning in Australia: Potential Opportunities and Roadblocks for an Increasingly Digital World.

Australia is committed to looking at ways to modernize its healthcare delivery further by integrating digital health. Advance Care Planning (ACP) is an area of healthcare that would likely benefit from further digitalization. However, while greater integration of technology in the delivery of ACP could help improve practices and lead to increased uptake, the extent to which this is achievable will be influenced, in part, by current approaches to ACP regulation. This article canvasses recent developments and trends in Australian law relevant to ACP and reflects on how these developments may impact the further digitalization of ACP.

Application of zero trust model in preventing medical errors

Medical errors can occur in many areas of healthcare, including hospitals, clinics, and surgery centers. They can result in negative consequences for patients and their loved ones. Over the years, different methods have been used to reduce medical errors. Zero Trust is an information security model that denies access to applications and data by default. Other industries have successfully used Zero Trust Model (ZTM), and it has been shown to improve outcomes. This editorial analyzes how the ZTM can be introduced to prevent medical errors in healthcare settings. ZTM application in healthcare could potentially revolutionize patient safety by tightly controlling and monitoring access to sensitive patient data and critical systems. By enhancing security measures, the ZTM could address the paramount concerns of patient data privacy and safety in healthcare. The zero-trust approach offers a potential solution by identifying consistent causes of errors and providing viable solutions to prevent their recurrence. In the era of worsening ransomware attacks on healthcare systems, the ZTM could also have enormous implications in other cybersecurity aspects. With this manuscript, the authors advocate for the broader application of ZTM across other facets of healthcare cybersecurity.

Knowledge, Attitude and Practices Regarding Third Wave of Coronavirus Pandemic among the Community People in Kathmandu Valley, Nepal

Background: Coronavirus pandemic (COVID-19) is a massive global health crisis. This paper aims to describe knowledge, attitude and practices (KAP) regarding Coronavirus pandemic among the community people residing in Kathmandu Valley. Methods: We have applied cross-sectional study design in which required data were collected from 312 sample households using accidental sampling procedure. We applied self-administered hand given questionnaire (Cronbach's alpha 0.97) consisting 105 items variables (35 each for KAP) on a six-point Likert scale, from 0(not applicable) to 5(strongly agree). Results: The study found that summative values of attitude (x̄ 3.71-3.97) and practices (x̄ 3.70-4.12) found comparatively weaker than knowledge (x̄ 3.09-4.24). About 124(39.7%) respondents have associated comorbidities allied with social distancing, masking/globing behavior, hand washing and sanitizing, physical exercise, PCR test/vaccination, health seeking behavior. KAP index is largely defined by variable family monthly expenditure on food/vegetable and their KAP index was significantly higher than others. However, presence of family members suffered from COVID-19 has negatively contributed to the KAP index. Conclusion: The denser views on KAP are the consistently with closer to agree and strongly agree points. KAP index found significant but skewed to left for Kirtipur and skewed to right for Lalitpur and Suryabinayak. Novelty: The municipal governments have been offering efficient and dedicated health services to the community people. However, knowledge, attitude and practices among the community people of residing in Kathmandu, Bhaktapur and Lalitpur found different. Therefore, the results of the study are valuable to policy makers and planners especially in the areas of healthcare and public health during pandemics.

Coexistence and food sources of adult mosquitoes (Diptera: Culicidae) in a rural health center in Piura, Peru 2024.

Motivation for the study. Rural health facilities could be potential foci of transmission and scenarios of zoonosis during epidemic outbreaks of dengue and other arbovirosis due to the coexistence of mosquito species that feed on different vertebrates. Main findings. Aedes aegypti feeds on Homo sapiens sapiens. Culex quinquefasciatus feeds on Homo sapiens sapiens and Canis familiaris. Both coexist in health care areas of the Querecotillo health center. Implications. Molecular techniques should be integrated into vector control to understand feeding patterns in natural conditions and information on probable reservoirs. This study aimed to determine the coexistence and food sources of adult mosquitoes (Diptera: Culicidae) in a rural health center in Piura, Peru by using a descriptive cross-sectional design. Entomological techniques were used to capture and identify mosquitoes, and molecular biotechnology techniques were used to identify food sources. A total of 793 specimens of the Culex and Aedes genera were found coexisting, 789 (99.5%) were Culex quinquefasciatus, 607 (76.9%) were males and 182 (23.1%) were females. Likewise, 4 (100%) corresponded to Aedes aegypti females. The food sources of Aedes aegypti were Homo sapiens sapiens, and Homo sapiens sapiens and Canis familiaris were the food sources of Culex quinquefasciatus. This study provides evidence that rural health centers could be acting as foci of arbovirosis, with the risk that people who come for different ailments could contract diseases transmitted by C. quinquefasciatus and A. aegypti.

ЛЕЧЕБНО-ВОССТАНОВИТЕЛЬНЫЕ И БИОТЕХНОЛОГИЧЕСКИЕ РЕСУРСЫ НАУЧНОЙ МУЗЫКОТЕРАПИИ В РЕШЕНИИ ПРОБЛЕМ БЕСПЛОДИЯ

Scientific music therapy is an advanced therapeutic and preventive direction, widely in demand in various areas of health care, psychological assistance, and social rehabilitation, but still underestimated in reproductive medicine. Complex scientific research conducted over thirty years has helped to better understand the nature of the main mechanisms of music's influence on the neuroendocrine system,vital organs, and cellular structures. On this basis, unique and effective methods of scientific music therapy and promising biotechnologies have been created, the possibilities of which in solving infertility problems are discussed in this article.

Novel insights into Antithrombin Deficiency enabled by Mass Spectrometry-based Precision Diagnostics

BackgroundAlthough P5 (preventive, personalized, predictive, participatory, psychocognitive) medicine and patient focused healthcare are gaining ground in various healthcare areas, the diagnosis of antithrombin deficiency (ATD) is still based on crude diagnostic tests clustering patients into clinically heterogeneous subgroups whereby relevant thrombophilia phenotypes may go unnoticed. Clinical pathways and the majority of evidence are based on these tests, therefore generic treatment is still the norm. ObjectivesTo unravel the heterogeneity of ATD, a mass spectrometry (LC-MRM-MS)-based test for antithrombin was developed allowing molecular characterization of the antithrombin proteoforms in patient plasma. This study provides the first insight into the tests’ clinical performance. MethodsPlasma from 91 unrelated ATD patients and 41 patients with a congenital disorder of glycosylation affecting antithrombin glycosylation were characterized functionally, genetically, and analyzed by LC-MRM-MS. An established data analysis strategy was applied for quantitation and molecular characterization of antithrombin proteoforms. ResultsThe test recognized patients with a quantitative defect, discriminated between type I and type II ATD, and identified variant proteoforms. Overall, the diagnostic sensitivity for ATD was 100% for LC-MRM-MS compared to 81.1% by the functional test. Type II ATD, a subtype prone to misdiagnosis, revealed an even larger difference of 100% identification by LC-MRM-MS versus 56.8% by functional test. ConclusionsThe qualitative and quantitative MS-based AT-test can serve as a platform for investigating the molecular basis of the clinical heterogeneity of ATD. This Precision Diagnostics approach for ATD can lower diagnostic uncertainty and modernize the ATD diagnostic and clinical pathways.

Editorial: Artificial Intelligence and Cybersecurity in Pervasive Computing

Pervasive computing, or ubiquitous computing, is rapidly increasing in capacity and capabilities. With the Internet of Things (IoT) becoming an integral part of daily life and the growing availability of edge computing resources, automation guided by data is advancing applications in healthcare, manufacturing, automotive, and other areas. It's natural that pervasive computing will intersect with artificial intelligence (AI) and cybersecurity. AI can improve detection, prediction, and anticipative responses to human needs, while cybersecurity addresses topics like misuse prevention, ethics, policies, and governance. This issue features seven articles on these intersections, including four AI articles exploring natural language processing and computer vision, and three cybersecurity articles covering cryptography, medical devices, and maritime security.

Editorial Preview

Effective from Volume 3, JIWE has transitioned to a triannual publication release effort. Specifically, releases occur each February, June, and October. This particular October 2024 release contains 12 papers within the regular section that covers a broad range of application concerning Machine Learning (ML), Artificial Intelligence (AI), Data Mining (DM), Software Engineering, Recommender Systems, Cybersecurity, Healthcare, and other key areas in web engineering. Additionally, this edition presents a captivating collection of 7 papers curated by our Thematic Editor, Dr. Ji-Jian Chin, under the theme "Pervasive Computing." In his editorial, Dr. Ji-Jian Chin highlights cutting-edge research on the integration of computing into everyday environments. Moreover, these papers are aligned to some of the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-being) through advancements in healthcare technologies, SDG 9 (Industry, Innovation, and Infrastructure) through software and systems innovation research, and SDG 16 (Peace, Justice, and Strong Institutions) through contributions to privacy and cybersecurity research.

Development of the Compassionate Technology Scale for Professionals (CTS-P): value driven evaluation of digital mental health interventions

BackgroundCompassion is an essential and beneficial value in mental healthcare. However, how digital mental health interventions influence compassion in treatment has not been systematically investigated, due to the lack of appropriate measurement instruments. To address this gap, we developed the Compassionate Technology Scale for Professionals (CTS-P), aimed at mental health professionals.MethodsWe used Q-methodology, a method that combines quantitative and qualitative analysis to explore shared viewpoints on a particular topic, to select and refine items. Participants were 15 professionals from different areas of mental healthcare. In individual sessions, while thinking aloud, they sorted 35 statements on relevance for evaluating technology use on compassion. The statements were based on a scientific conceptualization of compassion with five elements. The sorting task was followed by a short interview to explore participants’ associations with compassion and technology.ResultsWith by-person factor analysis, we found three different viewpoints among participants, all with eigenvalues > 1 and with a total explained variance of 63.02%. We selected prioritized items of each viewpoint and for each theoretical element of compassion, resulting in a full scale (15 items) and a short scale (3 items). Based on qualitative input from participants, the scale was adapted to clarify its focus and the wording of items. While thinking aloud, participants shared benefits and critical notes regarding technology and compassion.DiscussionTogether with key stakeholders, we developed the CTS-P. Most participants prioritized the potential of technology to obtain more information and be closer to their client in facilitating compassion. The main critical note participants had was that technology is not necessary to support compassion at the therapist’s experiential level. This emphasizes the need to further explore how mental health professionals and technology can complement each other in a system of compassionate care. Future research should explore the factor structure, validity, and reliability of the scale through psychometric validation.ConclusionsThe CTS-P can make the extent to which technology for mental healthcare influences elements of compassion measurable and comparable. The scale can prove useful for prioritizing the value of compassion in both the development and use of digital mental health interventions.

Job satisfaction of multidisciplinary staff working in intensive care units: a cross-sectional study in Qatar

Background/Aims Job satisfaction is an important contributor to the efficacy and success of organisations. An intensive care unit is a highly skilled area of healthcare that can be a physically and mentally challenging environment for staff, potentially impacting job satisfaction. This study aimed to assess job satisfaction levels among multidisciplinary staff members working in the intensive care units of a hospital in Qatar and evaluate how this is affected by sociodemographic and employment factors. Methods This was a cross-sectional, quantitative study that used a survey method. A total of 142 intensive care unit nurses, physicians and allied health professionals were recruited via random sampling from a tertiary hospital in Qatar. The Minnesota Satisfaction Questionnaire (short form) was used to collect data on respondents' intrinsic, extrinsic and overall job satisfaction levels, using statements scored with 5-point Likert scales. The survey also collected data on respondents' gender, age, job category and years of experience working in intensive care. Data were analysed using Shapiro-Wilk tests, Mann-Whitney U tests, Kruskal–Wallis tests and analysis of variance. Mean overall job satisfaction scores were classified as low (<3.00), moderate (3.00–3.99) or high (>4.00). A P value of <0.05 indicated statistical significance. Results The mean overall job satisfaction score was 3.82 out of 5.00, indicating moderate satisfaction. There were strong correlations between job satisfaction and both intrinsic (0.940) and extrinsic (0.894) satisfaction. There was a significant difference in job satisfaction levels depending on respondents' years of experience working in intensive care units (P=0.0477), with those who had less than 10 years of experience having the highest job satisfaction levels and those with 20–24 years' experience having the lowest job satisfaction levels. There were no significant differences between the job satisfaction levels of participants in different gender, age and job categories. Conclusions This study suggests that intensive care unit staff with more years of experience may have lower job satisfaction than those with fewer years of experience. Healthcare organisations should consider implementing targeted interventions to enhance job satisfaction, such as opportunities for professional development, recognition programmes, mentorship programmes, stress management workshops and efforts to improve work-life balance.

Barriers to Workforce-Driven Innovation in Healthcare.

Healthcare systems are continually developing new ways of delivering care in pursuit of quality improvement, increasing patient and provider satisfaction, and enhancing efficiency. This review measures the barriers to workforce-driven innovation in healthcare, a crucial yet underexamined area of study. Research into workforce-driven innovation in healthcare identifies several key barriers and solutions. Major impediments include a lack of knowledge and resources, as well as financial constraints, which hinder the implementation of innovations. Research findings from different regions enumerate organizational capability, leadership quality, and the adequacy of human resource management as influencing factors for innovation. Poor leadership, lack of inter- and cross-organizational learning, and structural barriers related to inadequate communication and formal forums also hinder progress. In addition, the resistance to change and the inability to engage employees effectively further obstruct innovation efforts. These issues can be addressed through the creation of a supportive innovation environment, enhancing training and development, and improving communication networks. Despite thorough database searches, the emerging nature of this topic has resulted in limited literature, restricting a comprehensive comparison of studies. Future research studies should be longitudinal in design, from diverse geographic contexts, and focus on the effects of emerging technologies to comprehensively understand these barriers and develop effective strategies for overcoming them.

Artificial Intelligence Applications for Imaging Metabolic Bone Diseases.

Artificial intelligence (AI) has significantly impacted the field of medical imaging, particularly in diagnosing and managing metabolic bone diseases (MBDs) such as osteoporosis and osteopenia, Paget's disease, osteomalacia, and rickets, as well as rare conditions such as osteitis fibrosa cystica and osteogenesis imperfecta. This article provides an in-depth analysis of AI techniques used in imaging these conditions, recent advancements, and their clinical applications. It also explores ethical considerations and future perspectives. Through comprehensive examination and case studies, we highlight the transformative potential of AI in enhancing diagnostic accuracy, improving patient outcomes, and contributing to personalized medicine. By integrating AI with existing imaging techniques, we can significantly enhance the capabilities of medical imaging in diagnosing, monitoring, and treating MBDs. We also provide a comprehensive overview of the current state, challenges, and future prospects of AI applications in this crucial area of health care.