Search Results (138)

Hospital in the Home (HITH) programs are emerging as a key pillar of smart city healthcare infrastructure, leveraging technology to extend care beyond traditional hospital walls. The global healthcare sector has been conceptualizing the notion of a care without walls hospital, also called HITH, where virtual care takes precedence to address the multifaceted needs of an increasingly aging population grappling with a substantial burden of chronic disease. HITH programs have the potential to significantly reduce hospital bed occupancy, enabling hospitals to better manage the ever-increasing demand for inpatient care. Although many health providers and hospitals have established their own HITH programs, there is a lack of research that provides healthcare executives and HITH program managers with management models and frameworks for such initiatives. There is also a lack of research that provides strategies for improving HITH management in the health sector. To fill this gap, the current study ran a systematic literature review to explore state-of-the-art with regard to this topic. Out of 2631 articles in the pool of this systematic review, 20 articles were deemed to meet the eligibility criteria for the study. After analyzing these studies, nine management models were extracted, which were then categorized into three categories, namely, governance models, general models, and virtual models. Moreover, this study found 23 strategies and categorized them into five groups, namely, referral support, external support, care model support, technical support, and clinical team support. Finally, implications of findings for practitioners are carefully provided. These findings provide healthcare executives and HITH managers with practical frameworks for selecting appropriate management models and implementing evidence-based strategies to optimize program effectiveness, reduce costs, and improve patient outcomes while addressing the growing demand for home-based care. Full article

Background: Patients diagnosed with melanoma are at increased risk of developing multiple primary melanomas (MPMs). Identifying clinical and genetic factors associated with MPM is critical for implementing personalized surveillance strategies. This study aims to describe the clinical, histopathological, and genetic characteristics of patients with MPM managed in a tertiary hospital and to contextualize findings within the current literature. Methods: We conducted a retrospective review of patients diagnosed with two or more primary melanomas between 2010 and 2023 at a tertiary dermatology unit. Demographic data, personal and family cancer history, phototype, melanoma characteristics, genetic testing, staging, treatments, and outcomes were collected. These data were compared with findings from the recent literature. Results: Thirteen patients (ten males, three females; median age: 59 years) were found to have a total of 33 melanomas. Most patients had Fitzpatrick phototype II and no immunosuppression. The number of melanomas per patient ranged from two to five. Synchronous lesions were observed in two patients. Common locations included the trunk and extremities. Histologically, 57% were in situ melanomas, and subsequent melanomas were generally thinner than the index lesion. Two patients showed progression to advanced disease. One patient was positive for MC1R mutation; the rest were negative or inconclusive. Additional phenotypic and environmental risk factors were extracted from patient records and are summarized as follows: Ten patients (76.9%) had Fitzpatrick skin phototype II, and three (23.1%) had phototype III. Chronic occupational sun exposure was reported in four patients (30.8%), while five (38.5%) recalled having suffered multiple sunburns during childhood or adolescence. Eight patients (61.5%) presented with a total nevus count exceeding 50, and five (38.5%) exhibited clinically atypical nevi. None of the patients reported use of tanning beds. Conclusions: Our findings are consistent with the existing literature indicating that patients with MPM often present with thinner subsequent melanomas and require long-term dermatologic follow-up. The inclusion of genetic testing and phenotypic risk factors enables stratified surveillance and supports the application of personalized medicine in melanoma management. Full article

Background: Overcrowded emergency departments (EDs) create significant challenges for patient management and hospital efficiency. In response, Amiens Picardy University Hospital (APUH) developed the “Prediction of the Patient Pathway in the Emergency Department” (3P-U) model to enhance patient flow management. Objectives: To develop and clinically validate an explainable artificial intelligence (XAI) model for hospital admission predictions, using structured triage data, and demonstrate its real-world applicability in the ED setting. Methods: Our retrospective, single-center study involved 351,019 patients consulting in APUH’s EDs between 2015 and 2018. Various models (including a cross-validation artificial neural network (ANN), a k-nearest neighbors (KNN) model, a logistic regression (LR) model, and a random forest (RF) model) were trained and assessed for performance with regard to the area under the receiver operating characteristic curve (AUROC). The best model was validated internally with a test set, and the F1 score was used to determine the best threshold for recall, precision, and accuracy. XAI techniques, such as Shapley additive explanations (SHAP) and partial dependence plots (PDP) were employed, and the clinical explanations were evaluated by emergency physicians. Results: The ANN gave the best performance during the training stage, with an AUROC of 83.1% (SD: 0.2%) for the test set; it surpassed the RF (AUROC: 71.6%, SD: 0.1%), KNN (AUROC: 67.2%, SD: 0.2%), and LR (AUROC: 71.5%, SD: 0.2%) models. In an internal validation, the ANN’s AUROC was 83.2%. The best F1 score (0.67) determined that 0.35 was the optimal threshold; the corresponding recall, precision, and accuracy were 75.7%, 59.7%, and 75.3%, respectively. The SHAP and PDP XAI techniques (as assessed by emergency physicians) highlighted patient age, heart rate, and presentation with multiple injuries as the features that most specifically influenced the admission from the ED to a hospital ward. These insights are being used in bed allocation and patient prioritization, directly improving ED operations. Conclusions: The 3P-U model demonstrates practical utility by reducing ED crowding and enhancing decision-making processes at APUH. Its transparency and physician validation foster trust, facilitating its adoption in clinical practice and offering a replicable framework for other hospitals to optimize patient flow. Full article

Against the backdrop of frequent public health emergencies caused by infectious diseases, it is urgent to evaluate the importance of urban epidemic prevention by integrating population mobility networks. In this study, a comprehensive evaluation index system is constructed based on a population mobility network, and the improved entropy weight method and analytic hierarchy process are used to obtain the comprehensive weights. The weight imbalance problem of traditional methods is solved by introducing community structure weighting and subjective weight. We establish a Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)-based evaluation model named city importance evaluation based on the division of communities and TOPSIS (CICT) for the importance of urban epidemic prevention and simulate the model using data from 297 cities in China. It can rank indicators that affect the importance of cities in infectious disease prevention and control and identify key cities for infectious disease prevention and control. The influence of various indicators on the evaluation objectives vary during different investigation periods, but the entropy weights of confirmed cases, hospital beds, and practicing (assistant) physicians remain at a high level. Cities with a high number of confirmed cases consistently rank at the top in the comprehensive evaluation, but this model can also identify potential key cities with fewer confirmed cases. These cities require key management during the outbreak of infectious diseases. The evaluation model can scientifically assess the epidemic prevention significance of cities, improve the efficiency of public health emergency management, and provide quantitative support for formulating urban epidemic control strategies, promoting resource optimization allocation, and implementing targeted measures. Full article

Understanding how hospital length of stay (LoS) evolves with successive SARS-CoV-2 variants is central to the multiscale modeling and forecasting of COVID-19 and other respiratory virus dynamics. Using records from 1249 COVID-19 patients admitted to Chungbuk National University Hospital (2021–2023), we quantified LoS across three distinct variant phases (Pre-Delta, Delta, and Omicron) and three age groups (0–39, 40–64, and 65+ years). A gamma-distributed multi-state model—capturing transitions between semi-critical and critical wards—incorporated variant phase and age as log-linear covariates. Parameters were estimated via maximum likelihood with 95% confidence intervals derived from bootstrap resampling, and Monte Carlo iterations yielded detailed LoS distributions. Omicron-phase stays were 5–8 days, shorter than the 10–14 days observed in earlier phases, reflecting improved treatment protocols and reduced virulence. Younger adults typically stayed 3–5 days, whereas older cohorts required 8–12 days, with prolonged admissions (over 30 days) clustering in the oldest group. These time-dependent transition probabilities can be integrated with real-time bed-availability alert systems, highlighting the need for variant-specific ward/ICU resource planning and underscoring the importance of targeted management for elderly patients during current and future pandemics. Full article

Background/Objectives: Optimal management of acute bacterial prostatitis (ABP) remains uncertain, but the use of antibiotics with good prostatic tissue penetration is critical to prevent recurrence and chronic progression. This study aimed to describe clinical characteristics and outcomes of ABP due to Escherichia coli (ABP-E.coli), compare effectiveness of sequential high-dose cefuroxime (ABP-CXM) versus ciprofloxacin (ABP-CIP), and identify risk factors for clinical failure. Methods: We conducted a retrospective study including men >18 years diagnosed with ABP-E. coli between January 2010 and November 2023 at a 400-bed hospital. Patients received oral cefuroxime (500 mg/8 h) or oral ciprofloxacin (500 mg/12 h). Outcomes over 90 days included clinical cure, recurrence and reinfection. Definitions: Clinical cure—resolution of symptoms without recurrences; recurrence—new ABP episode with the same E. coli strain; reinfection—ABP involving different microorganism or E. coli strain; clinical failure—lack of cure, recurrence, or reinfection. Results: Among 326 episodes (158 ABP-CXM, 168 ABP-CIP), ABP-CXM patients were younger (median 63.5 vs. 67.5 years, p = 0.005) and had fewer comorbidities. Clinical cure was higher in ABP-CIP (96.9% vs. 85.7%, p < 0.001). Recurrence occurred only in ABP-CXM (6.96% vs. 0%, p < 0.001), while reinfection and mortality were similar. Multivariable analysis showed ciprofloxacin was protective against clinical failure (OR: 0.16, 95% CI: 0.06–0.42, p < 0.001), while prior urinary tract infection (UTI) increased failure risk (OR: 2.87, 95% CI: 1.3–6.3). Conclusions: Ciprofloxacin was more effective than cefuroxime in treating ABP-E. coli. Patients with recent UTIs may need closer monitoring or alternative therapies. Full article

Background/Objectives: European healthcare systems are increasingly adopting automation technologies to improve efficiency. This study evaluates the economic viability of hospital automation and medication management digitalization. Methods: An economic evaluation was based on a standardized hospital model comprising 561 beds, representative of an average acute care hospital across EU27 + UK. For each technology, several cost items were estimated using country-specific parameters such as labor costs, medication error rates, healthcare expenditure, and money discount rate. The financial metrics (Return On Investment—ROI, Net Present Value—NPV, Payback Time—PBT) were first calculated at the hospital level. These results were then extrapolated to the national level by scaling the per-hospital estimates according to the total number of hospital beds reported in each country. Finally, national results were aggregated to derive the overall European impact. Results: The analysis estimated a total European investment of EUR 3.55 billion, with an average PBT of 4.46 years and annual savings of 1,96 billion. ROI averaged 167%, and the total NPV was 8.21 billion. A major saving driver was the reduction in Medication Administration Errors that has an impact of 37.2% on the total savings. Payback times ranged from 3 years in high-GDP countries, to 7 years in lower-GDP nations. Conclusions: These findings demonstrate how providing structured data on hospital automation benefits could support decision-making processes, highlighting the organizational and economic feasibility of the investment across different European national contexts. Full article

Healthcare is a dynamic and ever-changing phenomenon and is subject to multiple challenges, particularly concerning sustainability and cost issues. The literature identifies bed space and problems related to the lack of hospital beds as being directly or indirectly related to both admission and discharge processes, with delays in in-patient discharges being identified as a variable of significance when it comes to a health system’s overall performance. In this respect, the aim of this research was to explore factors related to delayed discharges in an acute hospital setting in Malta, a small European member state, through the perspectives of health professionals. This study followed a qualitative approach. Semi-structured interviews (n = 8) and focus groups (n = 2) were conducted with a diverse group of experienced health professionals. Informed consent was obtained from all participants, and all data were treated with strict confidentiality throughout the study. The sample was limited to professionals working in adult, non-specialized healthcare settings. Manual thematic analysis was carried out. Codes were grouped to derive seven main themes, which were identified after carrying out the thematic analysis process on the transcripts of the interviews/focus groups. The derived themes are the following: (a) a faulty system, which is open to abuse and inefficiency, (b) procedural delays directly impacting delayed discharges, (c) long-term care/social cases as a major cause of delayed discharges, (d) the impact of external factors on delayed discharges, (e) stakeholder suggestions to management to counteract delayed discharges, (f) the impact of COVID-19 on delayed discharges, and (g) inter-professional relationships. Factors related to delayed discharges and the effects of delayed discharges on the hospital emerged from the main findings, together with specific potential interventions to minimise delays in discharge. Health professional interactions and the effects of inter-professional relationship setbacks on delayed discharges were explored, and the impact of the COVID-19 pandemic on hospital dynamics and additional delays were also addressed. This information is intended to provide hospital administrators with data-driven internal organisational evidence to guide them through changes and to inform future decisions regarding hospital performance and efficiency from a discharge delay perspective. Full article

Hospitals require continuous access to water to sustain essential health services, especially when resources are taxed when drought conditions are compounded with other public health emergencies. In mid-2020, we conducted a rapid assessment of 71 hospitals in northern Thailand to evaluate water use and resilience during the concurrent 2019–2020 drought and the early phase of the COVID-19 pandemic in Thailand. While most hospitals reported adequate water availability, many depended on short-term measures such as shallow wells and improvised storage. Water use per bed often exceeded international benchmarks, reflecting broader usage patterns that extend beyond potable consumption. Community hospitals, in particular, reported more limited backup supply and planning capacity. Drawing on both our findings and international guidance, we propose the Hazard Management Model, involving a set of recommendations to strengthen hospital water resilience, including hazard-specific planning, protected infrastructure, emergency storage, and improved efficiency. These insights contribute to the growing body of work on climate-adaptive healthcare, particularly in resource-constrained settings facing intensifying multi-hazard risks. Full article

Background and Objectives: Infectious disease outbreaks are a major challenge for public health systems worldwide, especially for healthcare workers (HCWs). Taif city, in Saudi Arabia, has a high population density and is a tourist destination, which puts it at a high risk of infectious disease outbreaks. Despite its geographical importance, no previous study has been conducted that focuses on assessing the preparedness of healthcare workers in Taif city for managing infectious disease outbreaks. Therefore, we aimed to assess the overall level of preparedness among HCWs in healthcare facilities across Taif city and identify the challenges they face when managing infectious disease outbreaks. Materials and Methods: We conducted a cross-sectional study from October to December 2024 among 294 healthcare workers, using a structured questionnaire. We assessed the sociodemographic characteristics, infection prevention and control (IPC) training received by HCWs, the level of preparedness for managing infectious disease outbreaks, and their level of knowledge (low, moderate, or high). The association between sociodemographic characteristics and knowledge from having received IPC training and the level of preparedness was assessed using binary logistic regression. A p-value of ≤ 0.05 was considered as significant. Results: Around 31.7% of the participants were aged 31–40 years, with 59.2% of them being female. Among the HCWs we assessed, 44.6% were nurses and 31.3% of the HCWs were from hospitals with a bed capacity of over 500. Only 16.3% of HCWs felt fully prepared on a personal level and only 20.7% believed their facility was fully prepared for managing an outbreak. A low level of knowledge was reported among 71.8% of the participants. The odds of having received IPC training were significantly higher among HCWs aged 41–50 years (AOR = 15.7; 95% CI = 4.26–58.1), for those working in the inpatient department (AOR = 6.3; 95% CI = 1.46–27.05), and for those with a moderate level of knowledge (AOR = 0.12; 95% CI = 0.03–0.5). The odds of being fully prepared for an infectious disease outbreak were significantly higher for males (AOR = 2.58; 95% CI = 1.18–5.63) and those working in the in-patient department (AOR = 6.87; 95% CI = 1.7–27.8) and significantly lower for those with a low level of knowledge (AOR = 0.19; 95% CI = 0.06–0.61). Conclusion: Even though many HCWs have undergone IPC training, our findings highlight gaps in both knowledge and overall preparedness among healthcare workers in Taif city. Regular refresher courses, improved resource allocation, and implementing scenario-based emergency drills may help in improving the overall knowledge and preparedness of HCWs. Full article

Background/Objectives: This study investigates the evolution of hospital capacity and utilization in California between 2003 and 2023, focusing on emergency departments (EDs) and trauma centers (TCs). We seek to document structural changes in the healthcare delivery system with respect to hospital-based emergency and trauma services. Methods: This analysis examines changes in population demographics, hospital resources, and patient utilization patterns across facility types. Given the significant increase in the proportion of the population aged 65+ and the documented higher use of emergency and trauma services by this population, we expected to observe an expansion in ED and trauma service capacity and utilization. Results: Utilizing a comprehensive dataset of California general acute care hospitals over this 20+ year period, our descriptive analysis reveals major shifts in the healthcare delivery system, notably the increased prominence of hospitals with EDs, particularly those designated as trauma centers. Findings indicate that, while the overall number of hospitals and licensed beds has slightly decreased, facilities with EDs, especially trauma centers, have increased their capacity and manage a greater proportion of inpatient admissions and ED visits. Conclusions: The increase in ED visits and inpatient admissions at trauma centers, contrasted with decreases in both capacity and utilization at non-trauma hospitals, indicates a significant restructuring of the health delivery system with significant implications for healthcare policy, financing, operations, and affordability. The high and increasing percentage of inpatient admissions originating from hospital EDs and from hospitals with trauma centers suggests a need for policies that foster integration between ED and inpatient care and the broader healthcare delivery system, while at the same time managing the increase in prices and costs associated with growing emergency services utilization. Further research is needed to explore the implications of these trends, particularly concerning their impact on the affordability of healthcare in the US. Full article

Background: Perioperative fluid management plays a critical role in optimizing recovery after radical cystectomy. Various strategies, such as restrictive fluid therapy, goal-directed fluid therapy (GDFT), and warmed fluids, have been studied for their impact on complications and outcomes. However, the optimal approach remains uncertain. Methods: We conducted a systematic review in accordance with PRISMA 2020 guidelines. A PubMed search was performed in January 2025. Eligible studies included randomized controlled trials (RCTs) and observational studies published in English that assessed perioperative fluid strategies in radical cystectomy. Two reviewers independently selected studies, with a third resolving discrepancies. Data were extracted on study characteristics, interventions, and outcomes. Risk of bias was assessed using the Cochrane Risk of Bias Tool. Due to heterogeneity, narrative synthesis was used. Results: Seventeen studies (eight RCTs, nine observational; total n = 3519) were included. Three publications based on a single RCT (n = 167) showed that restrictive fluid therapy with norepinephrine significantly reduced blood loss (p < 0.0001), transfusions (p = 0.0006), complications (p = 0.006), and hospital stay (p = 0.02), with a trend toward fewer 90-day complications (p = 0.12). Six studies (four RCTs, two observational) evaluated GDFT. Doppler- and SVV-based GDFT reduced ileus, nausea, wound infections, and blood loss, although findings on renal function and length of stay were mixed. One RCT showed that warmed fluids reduced transfusion needs (p = 0.028) and hospital stay (p = 0.05). VBFI (Vascular Bed Filling Index)- and aVBFI (adjusted Vascular Bed Filling Index)-guided strategies may lower complications in ileal conduit patients, but evidence remains limited. Conclusions: Restrictive fluid therapy with norepinephrine appears to improve outcomes after radical cystectomy. GDFT and warmed fluids show potential benefits, but findings are inconsistent. Further high-quality trials are needed to define the optimal strategy. Full article

Vibrio parahaemolyticus is a prevalent pathogen responsible for foodborne diseases in coastal regions. Understanding its dynamic relationship with various meteorological and marine factors is crucial for predicting outbreaks of bacterial foodborne illnesses. This study analyzes the occurrence of V. parahaemolyticus-induced foodborne illness in Zhejiang Province, China, from 2014 to 2018, using an 8-day time unit based on the temporal characteristics of marine products. The detection rate of V. parahaemolyticus exhibited a distinct cyclical pattern, peaking during the summer months. Meteorological and marine factors showed varying lag effects on the detection of V. parahaemolyticus, with specific lag periods as follows: sunshine duration (3 weeks), air temperature (3 weeks), total precipitation (8 weeks), relative humidity (7 weeks), sea surface temperature (1 week), and sea surface salinity (8 weeks). The SARIMAX model, which incorporates both marine and climatic factors, was developed to facilitate short-term forecasts of V. parahaemolyticus detection rates in coastal cities. The model’s performance was evaluated, and the actual values consistently fell within the 95% confidence interval of the predicted values, with a mean absolute error (MAE) of 0.047, indicating high accuracy. This framework provides both theoretical and practical insights for predicting and preventing future foodborne disease outbreaks. These findings can support food industry stakeholders—such as seafood suppliers, restaurants, regulatory agencies, and healthcare institutions—in anticipating high-risk periods and implementing targeted measures. These include enhancing cold chain management, conducting timely seafood inspections, strengthening cross-contamination controls during seafood processing, dynamically adjusting market surveillance intensity, and improving hygiene practices. In addition, hospitals and local health departments can use the model’s forecasts to allocate medical resources such as beds, medications, and staff in advance to better prepare for seasonal surges in foodborne illness. Full article

The study focused on the design of an ORMS in a medical center in central Taiwan, which also functions as a teaching hospital. Background/Objectives: The research objectives were to design an ORMS simulation system based on the status quo of the operating room planning and scheduling in the medical center, obtain the optimal parameter setting in the ORMS, and find improvement strategies according to the sensitivity analysis based on the optimal parameter setting for total performance. Methods: Taguchi’s dynamic method was adopted to design the ORMS under human and material resource constraints. The scope of the study was internal medicine patients of the ORMS. A neural network was used to construct a relationship between parameters and performances. A genetic algorithm was used to obtain the optimal parameter setting for optimal performance. Results: This study successfully established a robust operating room management system (ORMS) to help hospital manager to plan and schedule operating rooms and take the ORMS into account to meet patient needs. Decision-makers can use the insights from the sensitivity analysis to refine their strategies effectively. The sensitivity analysis showed that the impact power (the percentage change in d) of the “number of circulating nurses (−0.15 to −1.25; −0.25 to −1.85)” factor was less than (<) that of the “number of holding nurses (−0.85 to −2.04; −0.91 to −2.07)” factor < that of the “number of preoperative beds (−2.57 to −4.53; −2.23 to −4.10)” factor < that of the “number of anesthetists (−3.13 to −7.50)” factor. Conclusions: In the optimal parameter setting obtained, the number of holding nurses was 18, the number of circulating nurses was 20, the number of anesthetists was 15, and the number of preoperative beds was 12. The optimal performance was 0.91. Full article

Background/Objectives: COVID-19 has impacted Romania’s healthcare, economy, society, and public health. This study aims to evaluate the financial impact of the COVID-19 pandemic in Romania by analyzing both hospital costs and key elements of economic costs. The assessment was conducted from the perspective of the national payer. Hospital costs were analyzed covering two distinct timeframes: Q4 2020–Q3 2021 and Q1 2022–Q4 2022. The estimation of economic costs covered Q4 2020–Q3 2021. Methods: Hospital care costs were estimated using financial data from eight hospitals. The costs were extrapolated to inpatient data from 60 public hospitals for each of the two study periods. The disease burden was determined based on official data, including the number of confirmed cases, hospital bed occupancy, reported fatalities, and various cost components from an economic perspective. Results: The findings indicate that the average hospital cost per patient episode was EUR 2267 (95% CI: 2137–2396) during the first period and EUR 2003 (95% CI: 1799–2207) in the second. The total national hospitalization expenses amounted to EUR 1.35 billion and EUR 730 million, respectively. When accounting for productivity losses and testing costs, the overall expenditure reached EUR 5.39 billion for Q4 2020–Q3 2021. Conclusions: In conclusion, the total economic burden of the COVID-19 pandemic in Romania by the end of 2021 was estimated at EUR 5.39 billion, encompassing hospitalization, isolation, premature deaths, quarantine, testing, and parental allowances. Despite the emergence of costlier treatment options, overall treatment costs declined, possibly due to increased vaccination rates. The study highlights the significant financial strain on the healthcare system and underscores the importance of evidence-based resource allocation to better manage future public health crises. Full article