Journal of Multidisciplinary Healthcare最新文献

Objective: To explore the effect of the Integrated Management Model of Doctor-Nurse-Pharmacist Collaboration on the Safety of Intravenous Therapy in Critically Ill Patients.

Methods: 1587 patients who were hospitalized in the Intensive Care Department of the Fourth Hospital of Hebei Medical University in China from January 2021 to December 2022 were selected. 768 patients before the implementation of the integrated medical, nursing, and drug management model were selected as the control group, and 819 patients who implemented the integrated medical, nursing, and drug management model were selected as the observation group.

Results: Compared with the control group, the incidence of drug compatibility contraindications in the observation group decreased from 3.5% to 1.5% (χ²=6.957 P=0.008), the central venous catheter (CVC) blockage rate decreased from 2.5% to 1.0% (χ²=5.249 P=0.022), the daily incidence of catheter related bloodstream infections decreased from (1.84 ± 2.17) to (0.91 ± 1.19)(t=6.988 P=0.015), and the incidence of peripheral venous treatment related complications decreased from 10.3% to 2.9% (χ²=16.663 P=0.000). Among them, the incidence of phlebitis decreased from 5% to 1.6% (χ²=4.817 P=0.028). The incidence of drug exudation decreased from 3.4% to 0.8% (χ2=0.031 P=0.019). The incidence of extravasation has decreased from 2.5% to 0.4% (χ²=0.044 P=0.027). The differences were statistically significant (P<0.05).

Conclusion: The Integrated Management Model of Doctor-Nurse-Pharmacist Collaboration significantly reduced the incidence of catheter-related bloodstream infections (CRBSI), drug incompatibility, and other intravenous therapy-related complications, thereby enhancing the safety of intravenous therapy in critically ill patients.

Purpose: To identify the factors affecting Chinese oncology nurses' competency in coping with death, and their relationship with death attitudes and educational needs.

Methods: A national cross-sectional descriptive study was conducted using an online survey of Chinese oncology nurses. Data were collected using the Coping with Death, Death Attitude Profile-Revised, and Death Education Needs Scales. A Pearson's correlation analysis was used to examine the relationships among the research variables. A multiple linear regression analysis was used to analyze the factors influencing coping with death.

Results: The total score of coping with death was 133.57±26.78, showing a moderate coping level among Chinese oncology nurses. The Pearson's correlation analysis showed that death attitude was significantly and positively correlated with coping with death competence, and there was a statistically significant positive relationship between coping with death competence and death education needs. Years of oncology care experience, bereavement experience, death attitude, and death education needs were identified as statistically significant factors influencing competency in coping with death. These factors explained 30.6% of the differences in coping with death.

Conclusion: This study found that oncology nurses in China exhibited moderate levels of death coping competence, which needs to be improved to provide higher-quality end-of-life care. Further, death attitude and education needs were important factors affecting participants' coping with death competence. Tailored death education programs and continuing education on death should be provided for oncology nurses, to encourage them to actively participate in death competence-related training and promote an attitude of natural acceptance of death and positive care for terminally ill patients. In the future, virtual reality technology could complete course implementation designs with immersive, conceptual, and interactive characteristics, to enhance the death-coping education program. Nurses with less experience in oncology care and bereavement should improve their competency in coping with death.

Purpose: To assess abusive supervision and organizational silence among nurses and investigate the mediating influence of psychological capital and fear.

Background: Since the end of 2019, China's National Development and Reform Commission (NDRC) department has decided to start the construction of regional medical centers in Shanxi, reducing cross-provincial and cross-regional medical care. In order to improve the overall standard of care in a hospital in a short period of time, health care leadership decision makers may adopt various effective leadership management practices to achieve the set goals and have high work pressure at the same time. In this case, abusive management may occur.

Methods: A cross-sectional survey design was employed. In January -March 2024, a convenience sampling method was used to collect data from 470 nurses in a total of 5 hospitals in Shanxi province they were required to complete the questionnaires online anonymously. The chain mediation model was tested using the PROCESS macro program in the SPSS software and multiple linear regression model was used to verify the mediating effect.

Results: Psychological capital and fear mediate the relationship between abusive supervision and nurses' organizational silence, playing indirect mediating roles. Abusive supervision was positively associated with nurses' organizational silence. Additionally, psychological capital plays a negative mediating role, accounting for 48.48% of the indirect effect, and fear plays a positive mediating role, accounting for 45.83% of the indirect effect. They form a chain intermediary, accounting for 5.69% of the indirect effect.

Conclusion: Psychological capital and fear mediate the impact of abusive supervision on nurses' organizational silence. Positive leadership training should be conducted to help reducing the level of head nurses' abusive supervision behaviors, while also fostering actions that elevate nurses' psychological capital levels.

Objective: This study examined the link between physical activity levels, as measured by the Longshi Scale, and cardiac function and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels in stroke patients, aiming to find correlations with stroke risk factors.

Methods: The study involved 123 apoplexy patients divided into four groups based on the Longshi Scale: bedridden (31), domestic (32), community (30), and health (30). Clinical data was collected, and hemodynamic assessments were performed using impedance cardiography.

Results: Cardiac output time index (CTI) and estimated ejection fraction (EF est) were significantly reduced in both the domestic and community groups compared to the health group (P < 0.05), while diastolic arterial blood pressure (DABP) and systemic vascular resistance index (SVRi) were increased. In the bedridden group, stroke volume (SV), cardiac output (CO), CTI, left cardiac work index (LCWi), and EF est were all lower compared to the health group (P < 0.05), with SVRI and NT-proBNP levels being higher. Additionally, the bedridden group exhibited lower SV, CO, DABP, LCWi, CTI, and EF est when compared to the domestic and community groups (P < 0.05), but higher end-diastolic filling rate (EDFR) and NT-proBNP levels. The Longshi Scale grading positively correlated with SV (r = 0.536, P < 0.01), and NT-proBNP, EF, and cognitive dysfunction were found to be associated with activity levels in stroke patients.

Conclusion: The Longshi Scale correlates with cardiac function indicators like NT-proBNP and EF, and can help identify stroke patients at risk of cardiac dysfunction. Moreover, cognitive dysfunction was identified as a significant factor influencing the range of activity in patients with stroke.

Background: Artificial Intelligence (AI) is becoming integral to the health sector, particularly radiology, because it enhances diagnostic accuracy and optimizes patient care. This study aims to assess the awareness and acceptance of AI among radiology professionals in Saudi Arabia, identifying the educational and training needs to bridge knowledge gaps and enhance AI-related competencies.

Methods: This cross-sectional observational study surveyed radiology professionals across various hospitals in Saudi Arabia. Participants were recruited through multiple channels, including direct invitations, emails, social media, and professional societies. The survey comprised four sections: demographic details, perceptions of AI, knowledge about AI, and willingness to adopt AI in clinical practice.

Results: Out of 374 radiology professionals surveyed, 45.2% acknowledged AI's significant impact on their field. Approximately 44% showed enthusiasm for AI adoption. However, 58.6% reported limited AI knowledge and inadequate training, with 43.6% identifying skill development and the complexity of AI educational programs as major barriers to implementation.

Conclusion: While radiology professionals in Saudi Arabia are generally positive about integrating AI into clinical practice, significant gaps in knowledge and training need to be addressed. Tailored educational programs are essential to fully leverage AI's potential in improving medical imaging practices and patient care outcomes.

[This corrects the article DOI: 10.2147/JMDH.S464285.].

Background: Percutaneous coronary intervention (PCI) is the primary treatment for acute myocardial infarction (AMI). However, in-stent restenosis (ISR) remains a significant limitation to the efficacy of PCI. The cholesterol-to-lymphocyte ratio (CLR), a novel biomarker associated with inflammation and dyslipidemia, may have predictive value for ISR. Deep learning-based models, such as the multilayer perceptron (MLP), can aid in establishing predictive models for ISR using CLR.

Methods: A retrospective analysis was conducted on clinical and laboratory data from 1967 patients. The Boruta algorithm was employed to identify key features associated with ISR. An MLP model was developed and divided into training and validation sets. Model performance was evaluated using ROC curves and calibration plots.

Results: Patients in the ISR group exhibited significantly higher levels of CLR and low-density lipoprotein (LDL) compared to the non-ISR group. The Boruta algorithm identified 21 important features for subsequent modeling. The MLP model achieved an AUC of 0.95 on the validation set and 0.63 on the test set, indicating good predictive performance. Calibration plots demonstrated good agreement between predicted and observed outcomes. Feature importance analysis revealed that the number of initial stent implants, hemoglobin levels, Gensini score, CLR, and white blood cell count were significant predictors of ISR. Partial dependence plots (PDP) confirmed CLR as a key predictor for ISR.

Conclusion: The CLR, as a biomarker that integrates lipid metabolism and inflammation, shows significant potential in predicting coronary ISR. The MLP model, based on deep learning, demonstrated robust predictive capabilities, offering new insights and strategies for clinical decision-making.

Background: Hearing loss increases with age and due to increased life expectancy there is an increase in the number of individuals living with hearing loss. Older people with hearing loss residing in nursing homes are often dependent on healthcare professionals to help them with their hearing aids.

Objective: The aim of the study was to translate and test the psychometric properties of a Swedish version of a Norwegian questionnaire and to assess healthcare professionals' self-reported knowledge, experience, skills, competence, and information needs pertaining to residents' hearing loss and hearing aids in the Swedish context.

Materials and methods: A Norwegian questionnaire was translated and adapted, and thereafter distributed to healthcare professionals in nine nursing homes in mid Sweden between 2020 and 2021, and 313 questionnaires were returned.

Results: An exploratory factor analysis demonstrated adequate factorial structure in six factors, satisfying construct validity and internal consistency for the Swedish version. A confirmatory factor analysis showed a satisfactory model fit. Healthcare professionals reported having the skills required for handling hearing aids, but reported lower scores for having received information about hearing aids, taking initiatives to refer residents to hearing healthcare units, and checking for earwax. Registered nurses generally reported lower perceived knowledge and practical skills concerning hearing aids. Seventy-seven percent of the total group reported a need for information regarding hearing aid maintenance.

Conclusion: Healthcare professionals reported that the majority of nursing home residents need help with their hearing aids, but only a minority of these professionals had received education on hearing loss and training in hearing aid maintenance. Enrolled nurses and care assistants demonstrated higher levels of competence in handling hearing aids compared to registered nurses. In order to ensure safe and effective care, as well as facilitate communication among older adults with hearing loss, healthcare professionals need appropriate education and training.