Search Results (941)

Background: Digital transformation is reshaping healthcare operations, with loyalty programs increasingly used to strengthen patient engagement and streamline administrative workflows. However, fragmented information systems and manual verification routines continue to create bottlenecks, inconsistencies, and extended lead times. Methods: This study applies a mixed-methods approach within the Business Process Management (BPM) lifecycle to redesign the eligibility verification process for a loyalty program at Casa de Saúde São Mateus Hospital. Quantitative time measurements were collected during peak periods, while qualitative insights from staff observations and discussions supported process discovery and bottleneck identification. The proposed solution integrates a centralized SQL database, automated verification routines, and a dedicated administrative interface synchronized with the MedicineOne system. Results: The redesigned process reduced eligibility verification time by approximately 80% and improved Flow Efficiency by around 11.7%. Manual interventions, data fragmentation, and discount-application errors decreased substantially. The centralized database improved data reliability, while automated checks enhanced consistency and reduced staff workload. The system also enabled more accurate beneficiary management and improved coordination across administrative activities. Conclusions: Integrating Healthcare 4.0 principles with BPM enhances internal logistics, reduces lead times, and improves operational reliability. The proposed model offers a replicable framework for modernizing healthcare service delivery. Full article

Background/Objectives: Pre-hospital delivery is an unpredictable event posing significant challenges for Emergency Medical Services (EMS) teams. Despite advances in perinatal care, emergency deliveries outside the hospital environment remain associated with increased maternal and neonatal risks. This study aimed to identify predictors of out-of-hospital delivery in EMS-attended labor cases and determinants of neonatal condition immediately after delivery. Methods: We conducted a retrospective analysis of 5097 EMS records of laboring women in Poland from August 2021 to January 2022, of which 2927 were included in the final study sample. Multivariate logistic regression models with multiple imputation for missing data were used to identify predictors of pre-hospital delivery and adverse neonatal condition (Apgar ≤ 7) in EMS-managed childbirths. Results: Pre-hospital delivery was strongly associated with second-stage labor (OR ≈ 535; p < 0.0001), ruptured membranes (OR ≈ 8.7; p < 0.0001), and fewer previous pregnancies (OR = 0.86; p = 0.018), and showed a trend with higher maternal heart rate (OR = 1.015; p = 0.083). Neonatal status classified as Apgar ≤ 7 was significantly associated with preterm birth (p < 0.0001), absence of fetal movements (OR ≈ 26.4; p = 0.025), and complications during pregnancy (p = 0.036). Complications during labor and lack of prenatal care were not significantly associated with increased risk of pre-hospital delivery in the model. Conclusions: Rupture of membranes, second-stage labor, and fewer previous pregnancies are significant predictors of pre-hospital delivery in EMS-managed cases. Absence of fetal movements and preterm gestation predict worse neonatal outcomes (Apgar ≤ 7). Early identification of these factors may enhance prehospital perinatal care and improve maternal and neonatal prognosis. Full article

Background/Objectives: Children in paediatric palliative care often face school attendance barriers due to complex health needs. This study describes post-training perceptions of a training program by a pediatric hospice team to prepare school care assistants to safely include children with complex conditions, focusing on procedural skills, knowledge of the child, and family partnership. Methods: Care assistants who completed a structured course at the Paediatric Palliative Care Centre, University Hospital of Padua (2023–2024), were surveyed immediately after training. The program combined classroom instruction with hands-on simulation using high-fidelity mannequins and standard devices, including suction, pulse oximetry, ventilation, enteral feeding, and tracheostomy care. It also covered modules on urgent and emergency management, as well as family communication. An anonymous online questionnaire gathered socio-demographic data, prior training, clinical tasks performed, self-efficacy levels, and open-ended feedback. Quantitative results were analyzed descriptively, while qualitative comments were subjected to thematic analysis. Results: Of 130 invited assistants, 105 participated (81%). Participants reported strong perceived confidence: 85% selected the upper end of the 5-point scale (“very” or “extremely”) for routine-management ability, and 60% selected these same response options for emergency-management ability. In the most severe events recalled, 60.5% of incidents were resolved autonomously, 7.6% involved contacting emergency services, and 3.8% involved community or hospice nurses. Seventy-five percent judged the course comprehensive; thematic analysis of 102 comments identified satisfaction, requests for regular refreshers, stronger practical components, and requests for targeted topics. Conclusions: Immediately after the session, participants tended to select the upper end of the self-assurance item for both routine and emergency tasks. Combining core emergency procedures with personalized, child-specific modules and family-partnership training may support safety, trust, and inclusion. Regular refreshers and skills checks are advised. Full article

Objectives: This study aims to explore the facilitators and barriers in the process of using AI agents for disease management in older COPD patients. Methods: Based on the normalization process theory, a descriptive qualitative study was used to conduct semi-structured interviews with 28 older patients with COPD recruited from June to August 2025 in a Class A tertiary hospital in Wuxi, Jiangsu Province. Results: A total of 28 interviews were conducted. Four themes (Coherence, Cognitive Participation, Collective Action, Reflexive Monitoring), nine subthemes (recognition of intelligent technology;supported by policy discourse and the background of national-level projects; the creation of a family atmosphere; recommendations from HCPs; relief and social connection; new “doctor”–patient relationship and communication; eliminate the burden and return to life; benefit and value perception; right self-decision by AI) in facilitators and nine subthemes (privacy conflicts and trust deficiency; blurred boundaries of human–machine responsibility and authority; non-high-quality services are chosen reluctantly; technical anxiety; lack of motivation for continued engagement; extra burden; limitations of the physical environment; human–machine dialogue frustration; a sense of uncertainty about the future of AI) in barriers were extracted. Conclusions: This study identified key factors influencing the use of AI agents in chronic disease management in older patients with COPD. The results provide directions for improving the implementation and sustainable use of AI health technologies. Full article

Background/Objectives: Acute health events in institutionalized older adults often lead to avoidable hospital referrals, requiring rapid, accurate remote decision-making. Telemedicine has become a key tool to improve assessment and care continuity in nursing homes. This study aimed to evaluate outcomes associated with telemedicine-supported management of acute events in residential care facilities for older adults and to develop a deep learning model to classify episodes and predict hospital referrals. Methods: A quasi-experimental study analyzed 5202 acute events managed via a 24/7 telemedicine system in Vitalia nursing homes (January–October 2024). The dataset included demographics, comorbidities, vital signs, event characteristics, and outcomes. Data preprocessing involved imputation, normalization, encoding, and dimensionality reduction via Truncated SVD (200 components). Given the imbalance in referral outcomes (~10%), several resampling techniques (SMOTE, SMOTEENN, SMOTETomek) were applied. A deep feedforward neural network (256–128–64 units with Batch Normalization, LeakyReLU, Dropout, AdamW) was trained using stratified splits (70/10/20) and optimized via cross-validation. Results: Telemedicine enabled the resolution of approximately 90% of acute events within the residential setting, reducing reliance on emergency services. The deep learning model outperformed traditional algorithms, achieving its best performance with SMOTEENN preprocessing (AUC = 0.91, accuracy = 0.88). The proposed model achieved higher overall performance than baseline classifiers, providing a more balanced precision–specificity trade-off for hospital referral prediction, with an F1-score of 0.63. Conclusions: Telemedicine-enabled acute care, strengthened by a robust deep learning classifier, offers a reliable strategy to enhance triage accuracy, reduce unnecessary transfers, and optimize clinical decision-making in nursing homes. These findings support the integration of AI-assisted telemedicine systems into long-term care workflows. 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/Objectives: Healthcare workers at the frontline of managing pandemics are at increased risk for adverse physical and mental health outcomes, which has been shown to result in burnout. The relationship between personal resilience and burnout among clinical and non-clinical healthcare staff working in an acute care setting was assessed at the start of the COVID-19 pandemic. Methods: A prospective cross-sectional survey design with electronic questionnaires was used to measure resilience (Connor-Davidson Resilience Scale,) and burnout (Maslach Burnout Inventory—Human Services Survey). Linear regression analyses were conducted to examine the relationship between resilience and emotional exhaustion, depersonalization, and personal accomplishment. Results: A significant inverse relationship between resilience and both emotional exhaustion and depersonalization, and a positive relationship between resilience and personal accomplishment were identified. Higher resilience scores were significantly associated with lower emotional exhaustion and depersonalization and higher personal accomplishment under pandemic conditions. Conclusions: Strategies to boost resilience organization-wide amongst healthcare staff providing patient care are critical for providing skills to reduce the onset of burnout and support employee mental health. From a pandemic preparedness lens, organizational-level emergency management should consider the importance of resilience-building among staff to proactively prevent burnout and its subsequent effects on patient-care and general hospital functioning. Full article

Background: Patient-centered care (PCC) is a cornerstone of quality, yet its translation into managerial decision-making remains underexplored. Middle nurse managers (MNMs) play a pivotal role in enabling patient-centeredness, but their perspectives on PCC decisions are rarely investigated. Aim: This study explored MNMs’ perceptions of what constitutes a patient-centered decision in hospital settings and identified the essential dimensions underpinning such decisions. Methods: A qualitative descriptive design was adopted using semi-structured interviews. Thirty-eight MNMs from three hospitals in central Italy were included. Data were analyzed using Elo and Kyngäs’ content analysis approach. Results: Two overarching themes emerged as central to patient-centered managerial decision-making (PCMDM): “Meaning and definition of PCMDM,” and “Influencing dimensions of PCMDM”. MNMs described PCMDM as an evolving and adaptable process shaped by patient needs and organizational constraints and unfolding across distinct phases. Key influencing dimensions included the manager’s role, organizational environment, human resource management and knowledge of the patient. Conclusions: PCMDM is a continuous, ethical, and reflective process mediated by MNMs, who reconcile institutional priorities, team dynamics, and patient needs to create conditions for high-quality PCC. Implications for Practice: Strengthening PCMDM requires coordinated action aimed at equipping nurse managers with advanced leadership capabilities, building organizational structures that sustain patient-centered decisions, and empowering patients to actively co-shape the care process. Full article

Background and Objectives: Medically unexplained symptoms (MUS) represent a clinical syndrome encompassing conditions in which patients present with symptoms that cannot be adequately explained by identifiable organic pathology or do not meet established diagnostic criteria for organic disease. These symptoms pose a diagnostic and management challenge, particularly in acute care settings. The objective of this study was to determine the proportion of patients presenting with MUS to the Emergency Neurology Service of a tertiary care hospital. Materials and Methods: This retrospective study was conducted at the Emergency Neurology Service of Sveti Duh University Hospital. All patients who were triaged for neurological examination during the study period were included. Following clinical evaluation, attending neurologists assessed the extent to which each patient’s symptoms could be explained by organic disease (“organicity”). This assessment was recorded using a Likert scale ranging from “not at all explained” to “completely explained. Results: Out of 219 patients, 2.7% had symptoms that were rated as “not at all explained” by organic disease, 7.3% “somewhat explained”, 23.3% “largely explained” and 66.7% “completely explained” by organic disease. Conclusions: Approximately one-tenth of patients presenting to our Emergency Neurology Service have symptoms that are poorly explained by identifiable organic disease. Full article

Background/Objectives: Hyperglycemia in hospitalized patients is associated with an increased risk of complications, morbidity, mortality, and healthcare costs, regardless of a prior diagnosis of diabetes. The hospitalist system can improve various outcomes, including length of stay, medical costs, patient satisfaction, and mortality rates. However, the effects of hospitalist care on blood glucose control in hospitalized patients remain unclear. This study aimed to assess the specific effects of hospitalist services on blood glucose control in hospitalized patients, with a focus on hyperglycemia management and patient outcomes. Methods: This retrospective study reviewed the electronic medical records of patients diagnosed with diabetes at Yonsei Severance Hospital in Yongin, between March 2020 and February 2022. It included adults aged ≥20 years who were hospitalized and had undergone blood glucose measurements during hospitalization. Glycemic control was assessed using hemoglobin A1c, and the blood glucose levels were measured four times daily during hospitalization. Variability was quantified using the coefficient of variation and compared between hospitalist-led and traditional specialty care groups, over a 14-day hospitalization period. Results: Despite a higher baseline risk profile, patients receiving hospitalist-led care experienced significantly more stable glycemic variability over time (p = 0.002), suggesting better inpatient glucose management than those receiving traditional specialty care. Conclusions: Hospitalist-led care was associated with more stable glycemic variability over time in hospitalized patients with diabetes, despite a higher baseline burden of comorbidities and poorer glycemic control at admission. Full article

In recent years, payment schemes in healthcare have garnered attention for their potential impact on service delivery and cost management. This paper explores the impact of the bundled payment scheme (BP) on hospital outpatient services, focusing on the cost–speed tradeoff. Specifically, a higher service rate increases patient demand but also raises medical costs. We consider a queueing-game theoretical model to analyze servers’ service rate behaviors under different payment schemes (fee-for-service and BP) and the payer’s optimal payment scheme setting. Our study shows that achieving the first-best outcome under centralized decision making using the BP requires specific conditions. When the medical budget is sufficiently high, the payer can guide hospitals toward the first-best decision by setting an optimal price under the BP. However, when the budget is at an intermediate level, hospitals may set slower equilibrium service rates to control costs. To address this issue, the payer can implement service level regulation based on the BP scheme to achieve the first-best outcome. This scheme encourages hospitals to choose higher service rates by limiting expected waiting times. When the budget is too low, hospitals may be unwilling to provide service due to unprofitability. Moreover, as competition between hospitals intensifies, it becomes easier to maximize social welfare under the BP scheme. Full article

Background: Psychological services within hospitals are essential to delivering integrated, patient-centred care, yet in many health systems they remain fragmented, variably organised, or confined to specific medical specialties. The Clinical Psychology Unit of the Fondazione Policlinico Universitario Agostino Gemelli, Istituto di Ricerca e Cura a Carattere Scientifico (IRCCS), represents one of the few examples of a hospital-wide psychological governance model in Italy, but its organisational structure and longitudinal activity have not previously been systematically described. Objective: This study (I) describes the organisational design and operational components of the Gemelli Unit; (II) compares it with international organisational models using a typological framework; and (III) examines its resilience and adaptive capacity during the coronavirus disease 2019 (COVID-19) pandemic. Methods: A descriptive–narrative approach was adopted, integrating institutional documentation, routinely collected service data (2019–2024), anonymised case vignettes, and a structured comparison with national and international psychological care structures. The analysis was informed by theoretical models of integrated health-care delivery and by Donabedian’s structure–process–outcome framework. Results: Between 2019 and 2024, psychological interventions increased from 28,878 to 47,076 (+63%), with a post-pandemic average of 41,868 annual interventions. In 2024, the Unit supported 2150 patients and 340 healthcare professionals, with psycho-oncology accounting for approximately one-third of all activities. The model integrates clinical activity, staff support, conflict management, research, and training under a centralised governance structure, ensuring hospital-wide coverage and coordinated referral pathways. The comparative analysis identified four international organisational types—department-based, liaison/specialty-based, structured health-system, and academic–clinical hybrid—highlighting the hybrid and transversal nature of the Gemelli Unit and its capacity to maintain and adapt services during the COVID-19 emergency. Conclusions: The Gemelli Unit represents a distinctive hospital-wide organisational model that combines centralised governance, transversal deployment, personalised care, and structured support for healthcare professionals. These characteristics position it as a potentially transferable benchmark for health systems seeking to integrate psychological care into core organisational and clinical processes. Future work should prioritise the development of standardised outcome indicators and national frameworks to support the evaluation and harmonisation of hospital-based psychological services. Full article

This study investigates how next-generation digital infrastructures—terahertz (THz) communication and AI-driven network orchestration—shape perceived service quality, luxury perception, and loyalty within the context of luxury hospitality. An empirical survey was conducted among 693 guests at Torre Melina Gran Meliá (Barcelona) between June 2024 and June 2025. Using a refined 38-item Likert-scale instrument, a three-factor structure was validated: (F1) Network Performance (speed, stability, coverage, seamless roaming, and multi-device reliability), (F2) Luxury Perception (modernity, innovation, and brand image), and (F3) Service Loyalty (satisfaction, return intentions, recommendations, and willingness to pay a premium). The results reveal that superior network performance functions both practically and symbolically. Functionally, it enables uninterrupted video calls, smooth streaming, low-latency gaming, and reliable multi-device usage—now considered essential utilities for contemporary travelers. Symbolically, high-performing and intelligently managed connectivity conveys technological leadership and exclusivity, thereby enhancing the hotel’s luxury image. Collectively, these effects create a “virtuous cycle” in which technical excellence reinforces perceptions of luxury, which in turn amplifies satisfaction and loyalty behaviors. From a managerial perspective, advanced connectivity should be viewed as a strategic investment and brand differentiator rather than a cost center. THz-ready, AI-orchestrated networks support personalization, dynamic bandwidth allocation (i.e., real-time adjustment of network capacity in response to fluctuating user demand), and monetizable premium service tiers, directly strengthening guest retention and brand equity. Ultimately, next-generation connectivity emerges not as an ancillary amenity but as a defining pillar of luxury hospitality in the emerging 6G era. Full article

Background: In the era of Health 4.0, Emergency Departments (EDs) face increasing crowding and complexity, necessitating smart management solutions to balance efficiency with equitable care. Effective scheduling is critical for optimizing patient throughput and mitigating congestion. Methods: This paper constructs a decision support framework using Discrete Event Simulation (DES) to evaluate three patient scheduling strategies, including the Initial-First policy, Alternating 1:1 policy and a Slack-Based dynamic policy. The simulation framework has been conducted using a standardized operational dataset representing typical ED dynamics. The threshold of SBP was optimized by a grid search method to guarantee an objective comparison. Results: The simulation results show that when adopting the optimized SBP policy, the mean waiting time was shortened by around 23.8%, thus meeting all triage service level targets. Also, it could be seen that Slack-Based dynamic policy was robust under different arrival rates and physician staffing levels. Conclusions: This proposed model can provide a real-time and dynamic solution for ED resource allocation, meeting the demand of modern smart hospitals management. Full article

Background/Objectives: The increasing rate of complex patients with multiple chronic somatic and/or mental disorders in modern medicine is challenging, necessitating special management programs. The aim of the present study was to identify clinical variables and the use of health services associated with the primary-physician-driven inclusion of complex patients in the “Team Management for Complex Patients” (TMCP) special program. Methods: Using validated electronic medical records of a nationwide health maintenance organization, a case–control study was performed. The study compared parameters before enrollment of complex patients included in the TMCP program with those of complex patients during the same time period who were not included, and were matched using a propensity score for age, sex, socioeconomic status, place of residence, ethnicity, smoking status, physical activity, and the balance before the day of enrollment for the major body measurements and laboratory results. Results: The control group was well-balanced, except for the South region and no physical activity. Several respiratory, cardiac, gastrointestinal, neurological, inflammatory and autoimmune diseases were significantly more common among patients included in the TMCP program than among those not included. Complex patients included in the program presented significantly higher previous rates of attending outpatient urgent care centers, visiting hospital emergency departments, hospitalization, and medication use. Conclusions: Although limited by subjective inclusion criteria and potential confounding, the present comparative study identified clinical variables associated with the identification of complex patients for enrollment into a special managed program. These associations may inform future work to develop and validate criteria to support physician decision-making in selecting complex patients for managed programs and designing healthcare resources for patients who need them most. We currently meticulously follow the outcomes of the patients included in the special managed program. Full article