Hospital Topics最新文献

Objective: To evaluate the efficacy and cost-effectiveness of nurse-led telehealth interventions in patients with heart failure (HF).

Materials and methods: A structured literature review was conducted to analyze secondary data from Scopus, PubMed, and Google Scholar (2015-2024). Scopus queries and keywords, such as "telehealth" and "heart failure," were used for selection.

Results: Nurse-led telehealth reduced rehospitalization, enhanced self-management, and improved health-related quality of life (HRQoL). Remote monitoring, video conferencing, and personalized support optimize clinical outcomes and long-term cost efficiency. Despite the high initial costs, reduced hospitalizations and better resources demonstrate financial viability. This study highlights the efficacy and cost-effectiveness of nurse-led telemedicine in managing HFs.

Conclusion: Nurse-led telecare improves HRQoL, reduces rehospitalizations, and offers cost savings in managing chronic HF. These interventions are essential for addressing chronic disease challenges and improving healthcare efficiency. This study provides valuable data on the role of telemedicine in managing chronic conditions, particularly cardiovascular disease, in the digital age.

Purpose: Access to electronic databases is crucial for enabling evidence-based practice in nursing, enhancing patient care and clinical outcomes. In developing countries like India, there is limited data on the extent to which nurses use these databases in daily practice, affecting evidence-based practice adoption. This study aimed to assess (1) the usage of electronic databases by nurses for accessing research literature to support evidence-based practice, and (2) the relationship between socio-demographic factors and both the usage of and confidence in using these databases.

Methods: A cross-sectional survey was conducted among nursing professionals in North India, encompassing those in clinical practice, education, and research. A 15-item online questionnaire collected socio-demographic and professional data, information on database use (PubMed, CINAHL, Cochrane), confidence in usage, and perceived barriers. Chi-square analyses explored associations between variables.

Results: Among 506 respondents (mean age 36.09 ± 9.6 years), 68% reported using electronic databases, while 55.5% preferred general search engines like Google for clinical queries. About 30% lacked access to databases. No significant association was observed between electronic database usage and age, gender, or years of experience. However, significant associations were found with qualifications (p = 0.000), area of work (p = 0.000), and access to computers at work (p = 0.009) or home (p = 0.000). Usage was also significantly associated with the medical-surgical nursing specialty (p = 0.014).

Conclusion: Enhancing evidence-based practice among nurses requires addressing barriers to database access, improving resource availability, and promoting continuous professional development across diverse nursing settings.

Health systems are crucial for national well-being and developmental goals, such as achieving Sustainable Development Goals (SDGs). This scoping review compares the WHO Building Blocks and Control Knobs frameworks, using the ECLISPSE framework. Analyzing 23 research articles, Building Blocks Framework proves widely applicable in assessing health system performance, while the Control Knobs Framework excels in focused interventions, especially in family physician programs and primary care. Recognizing complementarity, combining both frameworks offers a holistic approach to health system assessment. Tailoring them to specific contexts enhances nuanced understanding and improves global health outcomes, though challenges in discerning differences for effective implementation persist.

Background: Insufficient nursing staff adversely impacts patient outcomes. This study was conducted to assess the factors influencing the intention to quit among nurses in a hospital in India.

Methods: This observational study was conducted at a tertiary care hospital and teaching institute in Chandigarh, India. A total of 229 nurses participated in the study. Data were collected using a validated questionnaire from a published thesis at Malardalen University, Sweden, with a Cronbach's alpha ranging from 0.82 to 0.85.

Results: The majority of the nurses were aged between 31 and 40 years (67.2%). Female nurses outnumbered male nurses [162 (70.7%) vs. 67 (29.3%)]. The mean work experience of the participants was 5.6 ± 2.746 years. Nearly 69% of the nurses expressed an intention to quit, albeit to varying extents. The intention to quit had a significant positive correlation with career growth, work schedule, and perceived health (p < 0.05). A weak correlation was observed with wages, organization, work environment, and managerial support, while no significant correlation was found with work climate.

Conclusion: In this hospital, 69.4% of nurses reported an intention to quit to some degree. The intention to quit was significantly associated with career growth, work schedule, and perceived health. Addressing these factors may help improve nurse retention.

The healthcare system of India has a major issue of inequality in the accessibility, quality among the public and private sector. These gaps have been addressed through Ayushman Bharat scheme initiated in 2018 to enhance access to healthcare in both sectors. This paper will explore the implication of Universal Health Schemes (UHS) or in this case Ayushman Bharat on the private hospital facilities. It examines impacts on revenues, operational expenses, long term budgetary sustainability and the new phenomenon of voluntary opt-outs provided a comparative approach to other economies. The systematic literature review adopted a PRISMA format to identify 54 relevant pieces of literature published between 2015 and 2024 based on PubMed, Scopus, Web of Science, and Google Scholar. Thematic coding was used to determine the following four themes that comprised of the findings: financial strain, operational burden, growth opportunities and cross-country insights. The findings indicate that Ayushman Bharat has caused growth in the number of patients but not an equivalent increment in revenues because of low reimbursement rates and delayed payment. Costs of operation have also increased. Nevertheless, there are prospects of growing services and nuturing public-private collaboration in case payment deficiencies and administrative obstacles are accommodated by policies. The increasing possibility of hospital opt-outs is a menace to the scheme sustainability. Accordingly, proper reimbursement, payment and low bureaucracies are necessary to sustain the input of the private sector and attain universal health coverage.

Introduction: Healthcare workers (HCWs) are exposed to needle stick injuries (NSIs), putting them at risk of contracting diseases such as Hepatitis B (HB) and AIDS. This study aims to identify and assess the risk of injuries caused by needles and sharps among healthcare personnel in a tertiary care hospital in Pune, by application of healthcare failure mode and effect analysis (HFMEA) tool.

Aim and objectives: The study aims to assessing NSI risks in healthcare environments using the HFMEA tool.

Objectives: To identify the determinants of NSI using HFMEA as tool.To suggest necessary recommendations based on risk severity of failure modes.

Methods: The study utilizes retrospective data from the incidence reports of the hospital. A total of 25 incidence reported were included in the study during the period January 2022-March 2023. The collected data from incidence reports were analyzed using the HFMEA tool was used to identify failure modes for NSIs and assess risk priority numbers (RPNs) and understand severity.

Findings and analysis: Total 11 failure modes scored high scored RPN. Failure mode with RPN more than 200 was selected for intervention to prevent NSIs. Reasons for NS injuries were found to be recapping, not discarding sharp immediately after procedure, transferring sharp from one person to another and casual attitudes.

Conclusion: HFMEA as a tool is effective and can be used to prevent NSI. Continuous education and training programs on the safe handling of needles would help prevent NSIs in the hospitals.

Childhood obesity is a growing public health concern in the United States, affecting children of all ethnic backgrounds, with disproportionate impacts on African American and Hispanic children. While many studies attribute these disparities to cultural factors, there is limited research examining how environmental conditions may also shape parental perceptions and childhood obesity rates. This study hypothesizes that parental perceptions of obesity may be influenced more by socio-economic environments than by cultural differences. Using data from the New Jersey Childhood Obesity Study (2009-2010), we compare childhood obesity rates and parental perceptions of weight status among Hispanic American and African American populations in three economically comparable cities: Camden, Trenton, and New Brunswick. By comparing children's actual weight status with their parents' perceptions, we explore whether differences in obesity rates and perceptions exist between these two cultural groups. Our findings show no significant differences between Hispanic and African American families across the three cities, supporting the hypothesis that obesity rates and parental misperceptions are more strongly influenced by shared environmental factors than by cultural or racial backgrounds.

Introduction: Due to the high costs of patient hospitalization, the increasing demand for readmission has led to a lack of suitable services provided by hospitals. The present study aimed to predict the risk of readmission among patients admitted to a large subspecialty hospital in Tehran using data mining techniques. Method: This retrospective cohort study employed data mining techniques following the CRISP-DM methodology to identify factors contributing to patient readmission. The study analyzed 47,892 electronic medical records from a large public hospital in Tehran, analyzing data from August 2018 to August 2019. The study utilized demographic and clinical data, extracting patterns to provide insights into readmission risks and support healthcare decision-making. Key algorithms included neural networks and the C5 decision tree. Model evaluation was measured by the accuracy rate in predicting readmission. Results: The findings from the neural network analysis revealed that the type of discharge, inpatient department, and length of stay significantly impacted readmission rates, with coefficients of 0.28, 0.21, and 0.16, respectively. The neural network model achieved an accuracy rate of 61.2% in predicting readmission. The analysis using the C5 decision tree algorithm showed that the length of stay, number of medications prescribed, and type of discharge had the most influence on readmission rates, with coefficients of 0.12, 0.11, and 0.10, respectively. Among the 37,832 patients analyzed, 11.95% experienced readmission, with 8.63% readmitted once, 2.32% twice, and 1% three or more times. Non-emergency admissions, non-surgical treatments, and specific discharge types were notable factors in readmission rates. Conclusion: Findings revealed that key factors, including the type of discharge, inpatient department, length of stay, and the number of medications prescribed, have substantial impacts on readmission likelihood. The data mining models achieved a suitable accuracy to predict readmissions as well as highlighted variables related to readmissions. Implementing strategies to use data mining models with better data management and quality can provide actionable insights for decision-making on patients' risk of readmission.

This study aimed to identify the status of hospital visions in Korea and understand the differences in vision based on hospital characteristics by conducting text mining. We collected 230 vision sentences from 85 Korean hospitals in 2024 through their websites. Major frequent words in visions were "Hospital," "Healthcare," "Lead," "Center," "Treatment," "Trust," "Patient," "Research," "Best," and "Customer" counted over 15 times. As a result of network analysis, six clusters were formed. We confirmed the recent trends in hospital visions and related important words by hospital characteristics, such as ownership, type of hospital, and location.

Background: Work-Related Musculoskeletal Disorder (WRMSD) is one of the noticeable problems among dental professionals, reporting musculoskeletal pain due to the prolonged working postures.

Purpose: This study aims to investigate the factors that influence dental doctor's health and quality of life related to their working conditions.

Methods: The study adopted 2 methodologies: Questionnaire based survey and Digital Human Modeling. Based on the questionnaire survey, it has been observed that 81.3% of doctors are suffering from WRMSDs in various parts of the body such as: neck, shoulder, upper back, and lower back. Chi-Square test was conducted to identify the factors that contribute to WRMSD. Digital Human modeling through JACK simulation package in the study was used to analyze the forces exerted on the lumbar area (L4-L5) of the lower back which helps to determine the risk for low back injuries. Written consent was obtained from the participants before participating in the study.

Results: The results show that WRMSD has a significant association with factors such as working hours and experience. It has been observed that the lower back compressive force on standing and sitting postures were below the NIOSH Compression limit value. But the prolonged working hours lead to discomfort to the dentist while performing their job.

Conclusion: Based on the study it has been concluded that WRMSD is more evident in standing position, especially while performing procedures with forward head postures and the postures followed for a prolonged period.