Search Results (840)

Background/Objectives: Medication-related safety incidents rank among the most prevalent patient safety concerns globally. In addition to healthcare professionals, patients also play a vital role in ensuring safe medication practices. To effectively engage them, it is essential to gain a deeper understanding of their knowledge and perspectives. Methods: We conducted a netnography-based mixed-method content analysis study within the Hungarian online environment to identify key patient concerns. A total of 5174 relevant comments and discussions were analyzed (from 14 August 2020 to 14 August 2023), utilizing a medication safety framework based on Glies et al. The analysis was confined to publicly accessible online content related to oral medications and did not include demographic information about commenters. Results: The framework was applicable, though its representation was uneven. Patients predominantly focused on issues related to Access to services and Communication. Online discussions were primarily dominated by patients, with contributions from relatives and healthcare professionals being comparatively limited. The majority of concerns pertained to prescription medications, particularly in the fields of gynecology, internal medicine, and gastroenterology. ATC codes G and A were most frequently referenced, corresponding to the healthcare domains discussed. Conclusions: Initiatives aimed at enhancing medication safety should prioritize improving access and communication. Patients must be empowered as active agents in safety efforts; they can aid in preventing errors, reporting incidents, and offering feedback. Their engagement supports organizational learning and promotes safer healthcare delivery. Full article

The incorporation of artificial intelligence (AI) and digital technology in healthcare has revolutionized service delivery, improving diagnostic precision, patient outcomes, and operational efficacy. Nonetheless, despite considerable progress, numerous problems persist that impede the realization of full potential. Current reviews predominantly emphasize the advantages of AI in disease detection and health guidance, neglecting significant concerns such as social opposition, regulatory frameworks, and geographical discrepancies. This SLR, executed in accordance with PRISMA principles, examined 21 publications from 2020 to 2025 to assess the present condition of AI and digital technologies inside Saudi Arabia’s healthcare industry. Initially, 863 publications were obtained, from which 21 were chosen for comprehensive examination. Significant discoveries encompass the extensive utilization of telemedicine, data analytics, mobile health applications, Internet of Things, electronic health records, blockchain technology, online platforms, cloud computing, and encryption methods. These technologies augment diagnostic precision, boost patient outcomes, optimize administrative procedures, and foster preventative medicine, contributing to cost-effectiveness, environmental sustainability, and enduring service provision. Nonetheless, issues include data privacy concerns, elevated implementation expenses, opposition to change, interoperability challenge, and regulatory issues persist as substantial barriers. Subsequent investigations must concentrate on the development of culturally relevant AI algorithms, the enhancement of Arabic natural language processing, and the establishment of AI-driven mental health systems. By confronting these challenges and utilizing emerging technologies, Saudi Arabia has the potential to establish its status as a leading nation in medical services innovation, guaranteeing patient-centered, efficient, and accessible healthcare delivery. Recommendations must include augmenting data privacy and security, minimizing implementation expenses, surmounting resistance to change, enhancing interoperability, fortifying regulatory frameworks, addressing regional inequities, and investing in nascent technologies. Full article

Background/Objectives: Older adults with chronic kidney disease (CKD) are particularly vulnerable to polypharmacy-related adverse outcomes due to altered pharmacokinetics, multimorbidity, and increased susceptibility to medication-related harm. Polypharmacy in CKD is associated with falls, hospitalizations, and functional decline. Clinical pharmacist-led medication reviews may mitigate these risks; however, access barriers limit their implementation in routine care. To evaluate the clinical impact of a digitally mediated pharmacist consultation service on medication burden, fall risk, healthcare utilization, and resource use among older adults with CKD and polypharmacy. Methods: We conducted a retrospective cohort study using anonymized electronic medical records from a large integrated healthcare organization. Adults aged ≥ 65 years with CKD and polypharmacy (≥8 chronic medications) were included. Patients receiving a structured digital medication review by a clinical pharmacist, delivered via the primary care physician, were compared with a comparable control group of eligible patients who did not receive the intervention during the study period. Outcomes included changes in medication use, fall risk, renal function, and healthcare utilization. Results: Among 6124 eligible patients (1226 intervention; 4898 control), pharmacist consultation was associated with a modest but clinically meaningful reduction in medication burden and a higher likelihood of fall-risk reduction compared with controls. Decreases in outpatient healthcare utilization were also observed following the intervention. Renal function decline was similar between groups. Conclusions: A digitally mediated, physician-integrated pharmacist consultation may reduce polypharmacy-related risks and adverse outcomes in older adults with CKD. This model offers a scalable approach to improving medication safety in a high-risk CKD population while minimizing reliance on patient digital engagement. Full article

In recent decades, the burden of TB has been gradually declining; however, with the emergence of COVID-19 and ongoing political conflicts, including the war in Ukraine, the proper functioning of healthcare services and TB control programs has been jeopardized. Recently, research has emphasized the importance of hematological parameters associated with inflammation, which can be easily analyzed through routine blood tests. Combining these parameters may have predictive value for various diseases, including pulmonary tuberculosis and even help monitor the effectiveness of treatment. Since there is no single hematological or inflammatory biomarker that provides precise and dynamic information about the success or failure of treatment, identifying individual markers or sets of biomarkers with higher sensitivity and specificity is essential. This is particularly important since sputum culture conversion at two months remains insufficiently sensitive and microscopy conversion has limited sensitivity and specificity in detecting treatment failure. Also, the analysis of the impact of the standard directly observed treatment, short-course regimen on pathogenic mechanisms also focuses on how it influences the interaction between inflammation and oxidative tissue degradation, by measuring plasma levels of glutathione. Utilizing a combination of hematological, inflammatory, and antioxidant biomarkers offers significant insights into systemic inflammatory responses in pulmonary tuberculosis patients, both before commencing treatment and during the entire duration of antituberculosis therapy. Combining different inflammatory parameters into a multiple biomarker can significantly enhance the accuracy of predicting prognosis and response to antibiotic chemotherapy. Identifying an optimal combination of biomarkers with predictive value is crucial for assessing treatment response and evaluating the effectiveness of anti-TB medication. Rather than developing or testing a composite prediction model, this review summarizes reported performance metrics from individual studies and highlights priorities for future prospective validation of integrated biomarker panels. Full article

Introduction: Timely access to healthcare is essential for improving population health and reducing inequities. Immigrants often experience unique cultural, linguistic, and systemic barriers that delay care-seeking and service utilization. Despite the rapid growth of the Nepalese community in Canada, there is limited empirical evidence examining their healthcare access. This study aimed to assess the prevalence and determinants of delays in accessing healthcare among Nepalese immigrants. Methods: A community-based participatory research (CBPR) framework guided a cross-sectional survey conducted between January and June 2019. The research process was co-led by academic investigators, community scholars, and local Nepalese organizations to ensure cultural and contextual relevance. A snowball sampling strategy was used to recruit 401 Nepalese adults. Data were analyzed using descriptive statistics and multivariable logistic regression to examine sociodemographic and health-related factors associated with delayed healthcare access. Results: Of the 401 respondents, 66.3% (n = 266) reported experiencing a delay in accessing healthcare within the preceding 12 months. Delays were more common among participants aged 26–45 years, those who were married, employed, or had an undergraduate degree or lower. After adjusting for covariates, older age, lower education, having a family doctor, higher income (≥$26,000), and one or more chronic conditions were associated with increased odds of delay. Family size and the number of years living in Canada have had little effect on care delay. Conclusions: Delays in accessing healthcare are common among Nepalese immigrants in Calgary, reflecting the intersection of individual, cultural, and systemic determinants. These findings underscore the importance of community-engaged, culturally responsive strategies to address barriers and promote equitable healthcare access for immigrant populations. Strengthening partnerships between health systems and immigrant communities may enhance trust, navigation, and continuity of care. Full article

Background: Prostate cancer remains a significant public health burden globally, particularly in sub-Saharan Africa, where rising incidence rates are compounded by limited screening, late-stage diagnosis and disparities in healthcare access. In South Africa, the Eastern Cape Province reports high prostate cancer prevalence, with many patients presenting at advanced stages. Understanding the epidemiological profile of affected individuals is critical for developing targeted health strategies. Objectives: This sub-study aims to describe the epidemiological characteristics of patients diagnosed with prostate cancer, using secondary data from Nelson Mandela Academic Hospital (NMAH), focusing on patients seen between March 2020 and November 2021. Methods: A quantitative cross-sectional study design is employed. De-identified secondary data extracted from clinical records of male patients diagnosed with prostate cancer and managed at NMAH during the study period. Variables include demographic information, clinical characteristics, health service utilization indicators. Analysis: Data will be captured and coded in Microsoft excel 2013 (Microsoft corporation, Seattle, WA, USA). The data will then be exported to STATA 18 for analyses. Descriptive statistics will be used to summarize the data. Inferential analyses such as logistic regression and chi-square tests will be used to explore associations between variables and treatment outcomes. The study provides insights into the demographic and clinical profiles of prostate cancer patients in a high-burden setting. It is anticipated that findings will highlight the age distribution, stage at diagnosis, and treatment patterns among patients diagnosed with prostate cancer. This will inform future prevention and intervention strategies in the Eastern Cape Province. Conclusions: By mapping out the epidemiological patterns of prostate cancer in the Eastern Cape through this sub-study, the research contributes to evidence-based planning and resource allocation, ultimately supporting efforts to reduce prostate cancer morbidity and mortality in rural South Africa. Full article

Background: Language barriers remain a major obstacle to equitable healthcare access for immigrants and refugees across Europe. Greece, as both a transit and host country, faces persistent challenges in providing linguistically and culturally appropriate care. Methods: This study presents a narrative literature review synthesizing international, European, and Greek evidence on the effects of limited language proficiency, professional interpretation, and intercultural mediation on healthcare access, patient safety, satisfaction, and clinical outcomes. Peer-reviewed studies and selected grey literature were identified through searches of PubMed, Scopus, Web of Science, and CINAHL. Results: The evidence consistently demonstrates that the absence of professional interpretation is associated with substantially higher rates of clinically significant communication errors, longer hospital stays, increased readmissions, and higher healthcare costs. In contrast, the use of trained medical interpreters and intercultural mediators improves comprehension, shared decision-making, patient satisfaction, and clinical outcomes. Comparative European data from Italy, Spain, Germany, and Sweden show that institutionalized interpretation systems outperform Greece’s fragmented, NGO-dependent approach. Greek studies further reveal that limited proficiency in Greek is associated with reduced service utilization, longer waiting times, and lower patient satisfaction. Conclusions: This narrative review highlights the urgent need for Greece to adopt a coordinated, professionally staffed interpretation and intercultural mediation framework. Strengthening linguistic support within the healthcare system is essential for improving patient safety, equity, efficiency, and the integration of migrant and refugee populations. Full article

Translation of evidence-based resuscitation practices into clinical settings remains slow and inconsistent, a gap that significantly impacts survival and neurological outcomes. Implementation science offers a structured approach to accelerate adoption by identifying context-specific barriers—such as dispatcher workload, team choreography, and resource constraints—and tailoring strategies to overcome them. This paper applies the Knowledge-to-Action (KTA) framework to resuscitation, emphasizing stakeholder engagement, iterative monitoring, and sustainability. We provide detailed guidance across key resuscitation settings, including dispatch-assisted cardiopulmonary resuscitation (DA-CPR), in-hospital code teams, and emergency medical services (EMS). The manuscript introduces a comprehensive outcomes framework encompassing implementation, service/system, and patient-level metrics, and illustrates practical application through case examples such as DA-CPR and real-time feedback devices. To enhance scientific utility, we also present a decision-oriented table for pilot testing, offering healthcare institutions a roadmap for sustainable integration of evidence-based resuscitation protocols. Full article

In the context of the rapid growth of the Internet of Things and mobile health services, sensors and smart wearable devices are continuously collecting and uploading dynamic health data. Together with the long-term accumulated electronic medical records and multi-source heterogeneous clinical data from healthcare institutions, these data form the cornerstone of intelligent healthcare. In the context of medical data sharing, previous studies have mainly focused on privacy protection and secure data transmission, while relatively few have addressed the issue of incentive mechanisms. However, relying solely on technical means is insufficient to solve the problem of individuals’ willingness to share their data. To address this challenge, this paper proposes a three-party Stackelberg-game-based incentive mechanism for medical data sharing. The mechanism captures the hierarchical interactions among the intermediator, electronic device users, and data consumers. In this framework, the intermediator acts as the leader, setting the transaction fee; electronic device users serve as the first-level followers, determining the data price; and data consumers function as the second-level followers, deciding on the purchase volume. A social network externality is incorporated into the model to reflect the diffusion effect of data demand, and the optimal strategies and system equilibrium are derived through backward induction. Theoretical analysis and numerical experiments demonstrate that the proposed mechanism effectively enhances users’ willingness to share data and improves the overall system utility, achieving a balanced benefit among the cloud platform, electronic device users, and data consumers. This study not only enriches the game-theoretic modeling approaches to medical data sharing but also provides practical insights for designing incentive mechanisms in IoT-based healthcare systems. Full article

Fog computing has revolutionized the world by providing its services close to the user premises, which results in reducing the communication latency for many real-time applications. This communication latency has been a major constraint in cloud computing and ultimately causes user dissatisfaction due to slow response time. Many real-time applications like smart transportation, smart healthcare systems, smart cities, smart farming, video surveillance, and virtual and augmented reality are delay-sensitive real-time applications and require quick response times. The response delay in certain critical healthcare applications might cause serious loss to health patients. Therefore, by leveraging fog computing, a substantial portion of healthcare-related computational tasks can be offloaded to nearby fog nodes. This localized processing significantly reduces latency and enhances system availability, making it particularly advantageous for time-sensitive and mission-critical healthcare applications. Due to close proximity to end users, fog computing is considered to be the most suitable computing platform for real-time applications. However, fog devices are resource constrained and require proper resource management techniques for efficient resource utilization. This study presents an optimized resource allocation and scheduling framework for delay-sensitive healthcare applications using a Modified Particle Swarm Optimization (MPSO) algorithm. Using the iFogSim toolkit, the proposed technique was evaluated for many extensive simulations to obtain the desired results in terms of system response time, cost of execution and execution time. Experimental results demonstrate that the MPSO-based method reduces makespan by up to 8% and execution cost by up to 3% compared to existing metaheuristic algorithms, highlighting its effectiveness in enhancing overall fog computing performance for healthcare systems. Full article

Background: Carpal tunnel syndrome (CTS) is a common peripheral neuropathy with increasing prevalence and economic burden. This study aimed to analyze recent trends in CTS treatment patterns, healthcare utilization, and costs within the dualized healthcare system in Korea, using nationwide claim data. Methods: This cross-sectional study used data from the Korean Health Insurance Review and Assessment Service National Patient Sample (HIRA-NPS) between 2010 and 2017. Patients with a primary diagnosis of CTS (KCD-10: G56.0) were included. Descriptive analyses were performed to examine trends in patient characteristics, healthcare utilization, treatment patterns, and medical costs in Western and Korean medicine. Results: A total of 29,112 patients with CTS were analyzed. In Western medicine, diagnostic tests accounted for the highest expenditure, particularly X-ray, nerve conduction studies, and electromyography. Over time, X-ray utilization increased, while nerve conduction and electromyography tests decreased. The proportion of surgical treatment declined from 11.28% in 2010 to 8.55% in 2017, whereas Korean medicine use increased from 9.41% to 15.08%, mainly consisting of acupuncture and related procedures. Conclusions: Korea exhibited a lower CTS surgery rate than other countries, alongside a rising trend in Korean medicine utilization. These findings underscore the distinctive dual healthcare system in Korea and highlight the need for prospective studies to assess the long-term effectiveness of Korean medicine-based conservative treatments. Additionally, the results may inform national health policy decisions, including insurance coverage and resource allocation for CTS management. Full article

Background: Telemedicine can improve early symptom detection using medical devices and applications. It can also help identify barriers to patient adherence and enhance communication with healthcare professionals. This study aimed to evaluate the applicability, usability, and patient satisfaction with telemonitoring devices and apps for individuals with heart failure and type 2 diabetes. Methods: In a randomized study, patients in the Intervention Group received six months of nursing teleassistance and telemonitoring using a wearable electrocardiograph, a step tracker, and an App for recording clinical information and conducting video calls. Usability was measured using the System Usability Scale (SUS) and satisfaction with a six-item questionnaire. Results: A total of 43 patients (71 ± 8 years) were enrolled in the intervention group. A total of 41 (95%) of patients utilized the App daily, entering 13,048 information, 53 ± 59 per patient. The nurses performed 896 video-calls, 22 ± 21 per patient. The mean number of walking sessions recorded was 6.1 ± 0.9 per week (159 ± 24 per patient). Thirty-five patients (81%) used a 3-lead ECG and recorded 942 traces, 27 ± 14 per patient. At the end, 40 SUS were collected from patients: 15 (38%, 71 ± 7 years) considered the system excellent or good, 20 (50%, 71 ± 8 years) thought it fair, and 5 (13%, 74 ± 7 years) considered the system offered poor. The overall assessment of patient satisfaction with the service was 22 ± 3.3. Conclusions: This study provides evidence that, although technology can be complex for older adults, it is broadly accepted by most patients, especially when the benefits are understood. The support offered by nurses is essential for significantly enhancing the overall patient experience. Full article

Background/Objectives: Published prevalences of depression are mainly based on measurements of depressive symptoms, whereas data on clinical depressions are lacking. Our aim was to map the prevalence of ICD-10 diagnoses of depression made by physicians in routine healthcare, during the last year of life in non-cancer conditions and to study associations with clinical variables. Methods: A registry study on all persons in ordinary accommodation, dying in 2015–2023 in non-cancer conditions. Results: Of 62,228 persons dying from non-cancer conditions, 4391 (7.1%) were formally diagnosed with depression during the last year in life. Depression was significantly more common in women than in men, 8.0% vs. 6.3% (p < 0.001); adjusted odds ratio (aOR) 1.46 (95%CI 1.37–1.55). Prevalence of depression was highest in persons 18–44 years (18.3%) and lowest in persons >85 years old (5.7%) (p < 0.001); aOR 4.12 (95%CI 3.66–4.63). It was also more common in persons living in more affluent areas, aOR 1.19 (95%CI 1.10–1.29). The condition was most frequent in persons with Parkinson’s disease (9.4%) and COPD (8.2%). Depression was associated with more emergency room visits, 89.5% vs. 81.3% (p < 0.001), and visits in psychiatric services in the last year in life, 41.4% vs. 8.8% (p < 0.001). Depression was less prevalent in persons admitted to palliative care (p = 0.007). Conclusions: The highest frequencies were found in women, younger persons, and those living in affluent areas, but also in certain diagnoses such as Parkinson’s disease and COPD. Clinical depression in the last year of life is associated with more emergency room visits and utilization of psychiatric services. Full article

Objective: Pediatric overweight and obesity represent a growing public health concern with significant long-term implications. In children diagnosed with attention-deficit/hyperactivity disorder (ADHD), stimulant medications may alter appetite, potentially impacting body weight and growth patterns. However, real-world data on the effect of these treatments on body mass index (BMI) classification remains scarce. We aimed to evaluate the effect of ADHD stimulant therapy on transitions in the BMI categories among children. Study Design: We conducted a large-scale observational cohort study assessing longitudinal changes in BMI classification following the initiation of stimulant treatment, utilizing data from Clalit Health Services, Israel’s largest healthcare provider. BMI was categorized into four groups: normal weight, overweight, obesity, and severe obesity. Subgroup analysis was performed by sex and age groups: <7 years; >7 <13 years and >13 <18 years. Results: At baseline, 26,930 children met the study inclusion criteria. 12,448 (46%) were classified as overweight or obese. Most children with normal weight at baseline maintained their BMI classification (90%). 48% of children with overweight, 42% with obesity, and 29% with severe obesity transitioned to a lower BMI category. 39% of children with underweight transitioned to normal weight. Similar patterns in BMI category transitions were observed between sexes. Transition to a lower BMI category was more prevalent in the younger age group. Conclusions: Stimulant therapy for ADHD is associated with significant shifts in BMI classification among pediatric patients. While many children, especially younger with higher baseline BMI, experienced improvements in weight status, a notable minority exhibited weight gain. These findings underscore the importance of routine BMI monitoring and weight management strategies during ADHD treatment. Full article

The global expansion of healthcare services has made medical waste management an increasingly critical and complex issue. Medical wastes require specialized management due to their high infection risk, potential for environmental pollution, and adverse effects on public health. The correct collection, transportation, and final disposal are vital for protecting environmental health and ensuring the safety of hospital personnel and the community. Numerous disposal methods exist. Selecting the appropriate one, however, is a multi-dimensional decision-making problem, necessitating the simultaneous evaluation of various conflicting criteria. Adana, one of Turkey’s largest provinces, generates significant medical waste volumes due to its dense population and developed health infrastructure. Therefore, choosing the most suitable disposal method for hospitals in Adana is crucial for establishing an effective and sustainable waste management system. Making this decision using traditional methods is difficult. The multitude of criteria prevents any single method from being optimal across all aspects. This complexity mandates the use of Multi-Criteria Decision-Making (MCDM) methodologies. In this study, MCDM methods were applied, based on expert opinions, to select the disposal method at a university hospital in Adana. The research examined twelve criteria and four alternatives. The CRITIC (Criteria Importance Through Intercriteria Correlation) method was employed to objectively weigh the criteria. For the rigorous evaluation and ranking of the alternatives, three robust MCDM methods were utilized: PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluation), TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), and EDAS (Evaluation based on Distance from Average Solution). The final results conclusively identified incineration as the most appropriate disposal method for the hospital. Full article