Risk Management and Healthcare Policy最新文献

Background: Needle stick injuries (NSIs) are among the most frequent and preventable risks to healthcare workers. Behavioral models like the Health Belief Model (HBM) offer valuable insight into preventive behaviors, including those related to NSI. However, no validated tools currently exist to assess NSI-related beliefs using the HBM.

Objective: To develop and validate the NSI-Prevention Beliefs Scale (NSI-PBS), a tool grounded in the Health Belief Model (HBM), to examine nurses' perception about NSI risk and prevention.

Methods: The study followed a structured scale development process, including literature review, expert validation, and a cross-sectional survey of 545 nurses was directed in July 2025. Psychometric evaluation involved exploratory and confirmatory factor analysis (EFA/CFA), as well as internal consistency testing, and measurement error assessment.

Results: EFA identified a six-factor solution aligned with HBM domains: "Susceptibility, Severity, Benefits, Barriers, Cues to Action, and Self-Efficacy". CFA confirmed good model fit (CFI =0.926, TLI =0.914, RMSEA =0.063, SRMR =0.058). All subscales demonstrated strong reliability (α =0.81-0.93; ω =0.82-0.93). The final version of this scale produced 25 items and showed robust psychometric properties, theoretical coherence, clear factorial structure, and low measurement error.

Conclusion: This study contributes to literature by adding a new psychometrically sound and theory-based instrument for assessing NSI prevention beliefs among nurses. The NSI-PBS can be used to measure NSI-Prevention Beliefs in clinical settings and in designing training, risk profiling, and safety interventions for nursing staff and other healthcare workers.

Purpose: This study aims to identify the key factors influencing hospital selection among urological patients in China. Despite policy efforts to promote tiered care through the Hierarchical Diagnosis and Treatment (HDT) system, many patients continue to bypass primary care. Understanding the behavioral and psychological drivers of this pattern is essential for improving patient guidance and optimizing healthcare resource allocation.

Patients and methods: Data were collected from a stratified random sample of 676 patients between June 10 and October 10, 2024 from tertiary, secondary, and community healthcare institutions in Jiangsu Province. We collected detailed information on demographic characteristics, clinical profiles, psychological states, health behaviors, and economic factors. Multinomial logistic regression was employed to identify independent predictors of hospital choice, while Sankey diagrams and multiple correspondence analysis (MCA) were used to visualize patient-level decision pathways and structural patterns.

Results: A substantial proportion of patients sought care at tertiary hospitals for conditions that could be effectively managed at lower levels, reflecting a disconnect between actual patient behavior and the goals of the HDT system. Hospital choice was shaped by clinical needs, emotional responses, and perceived institutional trust. Patients choosing tertiary hospitals were more likely to have undergone surgery, experienced severe pain, and reported negative emotional reactions. Secondary hospital users commonly had benign prostatic hyperplasia, moderate symptom burden, rural residence, and engaged in regular physical activity. Community healthcare facilities users typically presented with mild symptoms, shorter illness duration, mild anxiety, lower financial burden, and closer geographic proximity. Across all tiers, anxiety levels and trust perceptions emerged as key behavioral drivers contributing to the bypassing of primary care.

Conclusion: Despite policy efforts to promote primary care, many patients with manageable conditions continue to bypass lower-tier facilities. Building trust and providing triage support in primary care are essential for achieving the goals of hierarchical healthcare.

Background: Patients with coronary artery disease (CAD) and type 2 diabetes mellitus (T2DM) are at markedly increased risk of developing heart failure (HF), yet early identification of high-risk individuals remains challenging. The remnant cholesterol inflammatory index (RCII) has been proposed as a predictor of adverse cardiovascular outcomes, but its role in patients with CAD and T2DM has not been fully elucidated.

Methods: We retrospectively analyzed clinical data from patients treated at our center. Demographic characteristics, comorbidities, medication use, and laboratory parameters were collected. Key features were selected using the Boruta algorithm, and five machine learning models-logistic regression (Logistic), decision tree (DT), elastic net regression (ENet), LASSO regression, and naïve Bayes (NB)-were constructed. Discrimination was assessed by receiver operating characteristic (ROC) curves and area under the curve (AUC), calibration by calibration plots and Brier scores, and interpretability by SHAP analysis.

Results: Among 1181 enrolled patients, 73 developed HF. Median RCII levels were significantly higher in the HF group. Boruta feature selection identified 13 key predictors for model development. Logistic regression demonstrated the best performance, achieving AUCs of 0.88 in the training set and 0.85 in the testing set, with overall accuracy of 0.87 and F1-score of 0.79 in the testing cohort. SHAP analysis revealed that elevated RCII, poor nutritional status, and smoking were major contributors to HF occurrence, with RCII showing a positive association with HF risk.

Conclusion: RCII is a valuable predictor of HF in patients with CAD and T2DM. Higher RCII levels are closely linked to an increased risk of HF.

Background: Heart failure is characterized by high rates of hospitalization, substantial medical expenses and increased mortality, posing a serious threat to human health. Malnutrition is a common complication among patients with heart failure and is associated with increased risks of infection, rehospitalization and mortality, resulting in a considerable disease burden and financial strain on both patients and their families. Identifying patient-related influencing factors is the primary prerequisite for recognizing the risk of malnutrition.

Objective: This scoping review aims to systematically summarize the factors influencing malnutrition in patients with heart failure, based on evidence from both domestic and international studies.

Methods: Studies on malnutrition in heart failure were retrieved from PubMed, Web of Science, Cochrane Library, CINAHL, CNKI and Wanfang, from database inception to 25 May 2025. Two researchers independently screened titles and abstracts and extracted data according to predefined criteria. Findings were categorized and reported descriptively.

Results: A total of 30 studies were included. The reported prevalence of malnutrition in heart failure varied by assessment tool. Based on the biopsychosocial model, nine categories of influencing factors were identified: demographic characteristics, disease characteristics, clinical physiological indicators, pharmacological treatment, emotional status, cognitive function, behavior, support system and living environment.

Conclusion: This scoping review provides the first comprehensive summary of malnutrition-related factors in patients with heart failure through the biopsychosocial model. The findings indicate that malnutrition in patients with heart failure is affected by both subjective and objective factors and is closely associated with disease progression. A comprehensive understanding of the influencing factors of malnutrition contributes to the development of more precise nutritional risk assessment tools and lays the foundation for a continuous management pathway of screening, assessment, intervention, and monitoring to facilitate early risk identification.

Background: Surgical safety is a global health priority, yet its consistent application in low- and middle-income countries remains a challenge due to systemic, cultural, and resource-related barriers. The World Health Organization's Surgical Safety Checklist (SSC) has been shown to reduce perioperative complications, but evidence from fragile health systems such as Somalia remains scarce.

Methods: This prospective closed-loop clinical audit was conducted at Dr. Sumait Hospital, a tertiary referral and teaching facility in Mogadishu, Somalia. A total of 160 surgical procedures were observed across two audit cycles. The first cycle established baseline compliance, while the second followed a structured intervention comprising targeted staff education sessions, strengthened leadership involvement, and placement of visual reminders and wall posters in operating theatres. Checklist adherence was assessed across the sign in, time out, and sign out phases using a standardized 25-item observation tool. Data were analyzed using the Wilcoxon signed-rank test, with significance set at p < 0.05.

Results: Overall checklist compliance increased significantly from 51.38% in the first cycle to 93.01% in the second (p < 0.001). Improvements were observed across all three SSC phases: sign in compliance rose from 54.62% to 88.19%, time out compliance from 50.60% to 96.94%, and sign out compliance from 47.29% to 95.01%. The most substantial gains were linked to improved team communication during the time out phase. However, checklist items requiring anticipatory planning, such as risk assessment for major blood loss, showed relatively lower improvements.

Conclusion: Context-sensitive, low-cost interventions-including focused education, leadership reinforcement, and visual prompts-can markedly improve adherence to the WHO Surgical Safety Checklist in resource-limited settings. These findings underscore the SSC's potential to strengthen surgical safety culture in Somalia and offer a practical model for similar fragile health systems aiming to reduce preventable perioperative harm.

Purpose: Globally, acute pediatric intoxication is a serious health concern with a significant burden. Differentiation between pharmaceutical and non-pharmaceutical poisoning is crucial for promoting early diagnosis and implementing effective preventive strategies.

Patients and methods: This three-year retrospective cohort study investigated 1328 exposed children, aiming to develop risk prediction nomograms to identify patients in need of pediatric intensive care unit (PICU) admission and those at risk of mortality.

Results: With a mean age of 8.21±6.64 years, a mortality rate of 1.7% and a PICU admission rate of 1.3%, more than 99% of infants and preschool children were exposed unintentionally, and intentional exposure was observed in about 88% of adolescents (p<0.001). Aluminum phosphide (AlP) was a leading cause of mortality and PICU admission. Non-pharmaceutical poisoning was associated with more severe clinical presentations and was exclusively linked to mortality. A predictive model for mortality with an overall accuracy of 99% underscores the role of receiving prehospital treatment in increasing the likelihood of mortality. Exposure to AlP contributed to PICU admission with a notably high odds ratio (50.596). Significant predictors of PICU need were rapid admission and leucocytosis. A model predicting PICU admissions, with a Nagelkerke pseudo-R² of 0.710, encompassed mutual factors contributing to mortality and PICU need, including age, sex, and blood pressure.

Conclusion: The obtained findings highlight critical differences in poisoning characteristics and outcomes across pediatric age groups and exposure types, emphasizing a need to implement preventive strategies through proper family education, increased social awareness, and the provision of psychological support for at-risk individuals.

Background: To develop a service quality standard and provide a reference for standardizing the quality of integrated healthcare institutions cooperating between tertiary hospitals and pension institutions in China. The establishment of the scientific and quantifiable service quality standard for collaborative integrated healthcare institutions can provide clear guidance on service direction, content and processes for care institutions, ensuring the effective implementation and coordinated growth of healthcare services.

Methods: A preliminary service quality standard was developed through literature review and semi-structured interviews. Two rounds of Delphi experts' consultation were conducted, and the relative weights of indicators at each level were calculated by the Analytic Hierarchy Process.

Results: The service quality standard consists of 3 first-level, 14 second-level, and 63 third-level indicators. The coordination of experts' opinions, expressed by Kendall's W of Delphi methods, ranged from 0.209 to 0.252. And the highest weights by the Analytic Hierarchy Process were observed for: "Service process" (0.493) among first-level indicators; " Operational management of integrated healthcare services" (0.181) among second-level indicators; and "Establish a professional service team for integrated healthcare in tertiary hospitals including doctors, nurses, therapists, pharmacists" (0.066) among third-level indicators.

Conclusion: The service quality standard developed in this study is systematic and scientific. It incorporates multi-dimensional service quality indicators through rigorous design and weight allocation, providing both a theoretical foundation and practical guidance for evaluating service quality under the "integrated healthcare contract" model. There are also geographic limitations to this study, and the samples need to be expanded in the future to verify generalizability.

Background: Medical personnel working in hospital disinfection and supply centers face high levels of occupational exposure to biological, chemical, and physical hazards. Assessing their awareness of these risks is essential for preventing workplace injuries and improving safety behavior. This study aimed to develop and validate the Occupational Exposure Risk Awareness Scale (OERAS) for healthcare workers in such settings.

Methods: A cross-sectional psychometric validation study was conducted among 959 medical staff from disinfection and supply centers in Jiangsu Province, China. The 20-item OERAS was developed through literature review, expert consultation, and pilot testing, and it comprised four dimensions: Occupational Exposure Knowledge, Protection Measures, Incident Response, Training and Education. Internal consistency, test-retest reliability, split-half reliability, content validity, construct validity, and criterion-related validity were analyzed using SPSS 26.0 and AMOS 24.0.

Results: The OERAS demonstrated high reliability, with Cronbach's α = 0.85 for the total scale, Spearman's ρ = 0.83 for test-retest reliability, and a split-half coefficient of 0.81. Content validity was excellent (mean CVI = 0.88). Exploratory factor analysis extracted four factors explaining 62.8% of total variance, while confirmatory factor analysis confirmed good model fit (CFI = 0.93, TLI = 0.91, RMSEA = 0.05). Criterion validity showed a significant but low/moderate correlation (ρ = 0.42, p < 0.001) with an external safety knowledge test.

Conclusion: The corrected OERAS exhibits strong internal reliability and construct validity, making it a robust and practical tool for measuring occupational exposure risk awareness among medical personnel. Although criterion validity was low/moderate, this reflects that awareness and knowledge are related yet distinct constructs. The OERAS can support targeted training and policy interventions to enhance occupational safety in healthcare environments.

Background/objectives: Dispensing errors have the potential to cause significant and preventable patient harm, including adverse drug events, hospitalization, or even death. This study aims to analyze the characteristics of drug product dispensing errors in the outpatient pharmacy, identify risk factors, and develop a risk warning model for error prediction.

Methods: A retrospective study analyzed 930 prescriptions with product dispensing errors and 1860 control prescriptions without errors in an outpatient pharmacy of a tertiary hospital from April 2021 to March 2023. Univariate and multivariable logistic regression were used to identify risk factors. A risk warning model with a cutoff value was constructed and its reliability evaluated using Receiver Operating Characteristics(ROC) curve analysis. The cutoff value was then used to assess the model's test effectiveness with validation dataset.

Results: Logistic regression analysis identified six independent risk factors for product dispensing errors in outpatient pharmacies: work experience, professional title, education level, similar drug names, similar drug appearances, and multiple specifications. A risk warning model (p=e^x/(1+e^x), x=3.721-2.133×X1-0.424×X2-0.382×X3+0.736×X4+0.890×X5+0.701×X6) was established. ROC curve analysis showed an AUC of 0.921 (95% CI: 0.908, 0.933), cutoff value of 0.508, sensitivity of 86.0%, specificity of 91.7%, and Youden index of 0.777 for the training dataset. For the validation dataset, results revealed an AUC of 0.928 (95% CI: 0.901, 0.956), sensitivity of 85.90%, specificity of 83.10%, and Youden index of 0.69.

Conclusion: The risk warning model demonstrated high accuracy in predicting product dispensing errors in outpatient pharmacies. Validated externally, it provides a practical reference for preventing such errors.

Purpose: This study aimed to evaluate occupational health and safety risks among patient transport personnel at Vajira Hospital, Thailand, using the ISO 45001:2018 Occupational Health and Safety Management System (OHSMS). The goal was to identify hazards, quantify risk levels, and propose targeted corrective measures to enhance workplace safety.

Patients and methods: Data were collected from 60 patient transport personnel and their supervisors using in-person, semi-structured interviews. Task-related hazards were identified through standardized checklists aligned with ISO 45001:2018. Descriptive statistics (frequencies, percentages, mean values) were applied to summarize participant characteristics and risk levels.

Results: Among 21 assessed work activities: 2 activities were categorized as very high risk (ergonomic hazards). 12 activities as high risk. 6 activities as medium risk. 1 activity as low risk. Key hazards included repetitive lifting, awkward postures, and potential exposure to infectious agents. ISO 45001:2018 clauses 6.1.2 (Hazard Identification and Risk Assessment) and 8.1 (Operational Planning and Control) were most relevant for these high-risk activities.

Conclusion: The study identifies urgent needs for ergonomic interventions, staff training, and procedural adjustments to reduce high-risk activities. Implementing ISO 45001:2018 systematically can improve hazard control and promote a safer working environment for patient transport personnel in hospital settings.