Objective To comprehensively compare the methods and tools for medical risk management and assessment in the United Kingdom, the United States, Canada, Australia and Taiwan region (hereafter shortened as “four countries and one region”), so as to provide evidence and recommendations for medical risk management policy in China. Methods The official websites of the healthcare risk management agencies in these four countries and one region were searched to collect materials concerning healthcare risk management and monitoring, such as laws, regulatory documents, research reports, reviews and evaluation forms, then the descriptive comparative analysis was performed on the methods and tools for risk management. Results a) A total of 146 documents were included in this study, including 2 laws, 17 regulatory documents, 41 guidelines, 37 reviews and 49 documents about general information; b) The United Kingdom applied the integrated risk management; Australia and Taiwan adopted the classical risk management process, including risk identification, risk analysis, risk evaluation and risk control, while the United States and Canada mainly chose the prospective failure mode and effects analysis (FMEA) for clinical risk management; c) The severity of clinical risk was divided into five grades in the United Kingdom and Australia, and six in Taiwan, respectively. The frequency of medical risk was divided into five grades with four grade responses in above two countries and one region; and d) There were almost the same processes and tools about Root Cause Analysis (RCA), but a little difference in the objects of analysis in these four countries and one region. Conclusion?There are three models of risk management with the same assessment tools in these four countries and one region: the prospective risk assessment, the retrospective assessment based on occurred incidents and the integrated risk management. Although the grading of risk is similar, the definition of grading is different in the United Kingdom, Australia and Taiwan. The methods and processes of analyses on the adverse events are almost the same in these four countries and one region.
ObjectiveTo establish the model of nosocomial infection risk assessment, and evaluate its accuracy of prediction. MethodsThe model of nosocomial infection risk assessment was established by expert grading, and cross-section survey of nosocomial infection was used to evaluate the predictive effect from December 2013 to February 2014. ResultsThe infection risk score of the model had statistically significant influence on nosocomial infection [OR=1.35, 95%CI (1.26, 1.44), P<0.001]. The area under curve of the receiver operating characteristic curve was 0.754. The diagnostic test's sensitivity, specificity, positive predictive value, negative predictive value and accuracy were 56.30%, 84.50%, 17.80%, 97.00% and 82.95% respectively, and the cutoff was 4. ConclusionThe model of nosocomial infection risk assessment has certain significance in the prediction of nosocomial infection, and can be regarded as a reference for establishing precaution system of nosocomial infection.
With significantly increasing proportion of high-risk patients undergoing cardiovascular surgery, a quantitative risk stratification system of perioperative patients is needed for cardiovascular surgeons. European system for cardiac operative risk evaluation (EuroSCORE) is a widely-used risk prediction model for adult patients undergoing cardiovascular surgery in the world. Research data from Chinese Cardiac Surgery Registry show that the performance of EuroSCORE in the prediction of postoperative risk of Chinese cardiovascular surgical patients is not satisfactory. Thus, the first Chinese coronary operative risk evaluation model (Sino system for coronary operative risk evaluation,SinoSCORE) is established with latest cardiovascular surgery data by Collaboration Association of Cardiovascular Surgeon in China, and has been widely used in clinical practice. This review focuses on the application and prospect of EuroSCORE and SinoSCORE for the prediction of mortality after cardiovascular surgery in adults.
Objective To investigate the application of risk assessment in the control of nosocomial infections in surgical departments of infectious disease hospitals so as to provide references for the regulation of prevention and control measures. Methods Nosocomial infection risks in surgical departments of infectious disease hospitals were identified by the method of brainstorming. Based on risk assessment and planning of American children's national medical center in Washington for epidemic and infectious diseases control, the matrix method was used for risk assessment. The three highest risks were controlled, and then we compared the incidence of nosocomial infections before and after the risk assessment. Results The major risk factors in surgical departments existed in the process of diagnosis and treatment. By matrix scoring, excluding high readiness items, we found that the top three risks were airborne diseases, prevention and nursing of hematogenous infections and air disinfection. Nosocomial infection rate in the surgical departments dropped to 2.03% after carrying out risk assessment and taking correspondent measures (χ2=5.480,P=0.019). Conclusion Evaluation of nosocomial infection risk in surgical departments of infectious disease hospitals can discover major potential risks and reduce the incidence of nosocomial infections, which can provide references for management and control of nosocomial infections.
Objective To systematically review the predictive model of stroke-related pneumonia risk. Methods The CNKI, WanFang Data, CBM, PubMed, Web of Science, Embase, MEDLINE and Cochrane Library databases were electronically searched to collect studies on risk prediction models for stroke-associated pneumonia from inception to February 15, 2023. Two researchers independently screened the literature and extracted data. The risk of bias and applicability of the models were assessed using PROBAST. Results A total of 18 studies and 27 SAP risk prediction models were included. The AUC values for inclusion in the model ranged from 0.67 to 0.96, and the number of candidate predictors ranged from 4 to 25, with the most common predictors being age, NIHSS score, dysphagia, mRS score, and impaired consciousness (GCS score). Conclusion The overall predictive performance of SAP risk prediction models is good, but their predictive performance cannot be directly compared because of the differences in study type, study population, and SAP diagnostic criteria. Moreover, 72.3% of the models are not externally validated, and most of the studies have a high risk of bias.
Objective To explore the application of risk assessment of nosocomial infection control in outpatient departments, so as to find out the high-risk departments and high-risk links of nosocomial infection, and to provide basis for the formulation of nosocomial infection prevention and control measures in outpatient departments. Methods The improved risk assessment tool was used to evaluate the nosocomial infection management risk in the outpatient departments of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology. We evaluated risk indicators and risk levels from three dimensions: likelihood of risk occurrence, severity of consequences, and integrity of the current system. Results Among the evaluated outpatient departments, the departments with extremely high risk levels included pediatric fever outpatient department (147.8 points), pediatric outpatient department (141.2 points), emergency internal medicine department (139.4 points), and pediatric emergency department (138.8 points). The departments with high risk levels included internal medicine outpatient department (138.4 points), dermatology outpatient department (136.0 points), otolaryngology-head and neck surgery outpatient department (135.6 points), and ophthalmology outpatient department (134.0 points). The risk assessment scores of 31 outpatient departments showed a normal distribution. The evaluation results of various risk indicators showed that among the 26 risk indicators, there were 2 extremely low risk, 4 low risk, 6 medium low risk, 7 medium high risk, 4 high risk, and 3 extremely high risk. The 3 extremely high risk indicators were lack of nosocomial infection prevention and control knowledge, patients with difficult to identify diseases (air/droplet transmission) seeking medical treatment, and crowded waiting areas for patients. Conclusions The comprehensive risk assessment of outpatient departments can screen out high risk outpatient departments and find out the main risk links. We can concentrate resources on key departments, prevent key risks, and improve the efficiency of nosocomial infection control.
Objective To systematically review venous thromboembolism (VTE) risk assessment tools. Methods The Embase, PubMed, CNKI, CBM, WanFang Data, VIP databases and 22 relevant institutions and associations were searched to identify all VTE assessment tools from inception to December 31, 2022. Two researchers independently screened the literature, extracted data, and cross-checked the data. A qualitative analysis was used to describe the country's essential characteristics, publishing organization, year, applicable disease type, applicable population, tool formation method, etc. Key elements and techniques were compared in terms of evaluation dimension, methods, and procedures to form the tool, risk stratification ability, and whether to verify. Results A total of 42 VTE risk assessment tools were included, of which 16 were in the United States, and only 4 were in China. They were released between 1996 and 2021, and the applicable disease types and populations differ. Nineteen tools were constructed based on case-control or retrospective cohort studies, 16 were conducted using prospective cohort studies, and 5 were based on cross-sectional and RCT studies; Additionally, 20 tools were built based on logistic regression models; The evaluation dimensions of each tool differed, and the most common frequency of occurrences were VTE history, age, BMI value, and confirmed tumor, accounting for 64.29%, 54.76%, 54.76%, and 47.62%, respectively. Thirty-three tools were stratified for risk, and 30 tools were presented in the form of risk scores; Some tools lacked clinical validation data, and only 12 tools were analyzed for specificity, sensitivity, NPV, PPV, and AUC. Conclusion The evaluation dimensions and evidence sources of existing VTE risk assessment tools are not completely consistent, the implementation methods and results presentation forms of the tools are not completely the same, and the scope of application is different; Some tool construction methods and processes are not clear enough, and there is a lack of validation research on external validity, which has certain limitations in promoting clinical practice in China.