Healthcare-associated infection management has advanced rapidly in recent years. With the development of more standards and guidelines, infection control measures become more standardized and evidence-based. Evidence-based measures are increasingly applied in infection control, which promote more studies on the prevention and control of healthcare-associated infections. Furthermore, more new ideas of infection control have emerged, with old ones being challenged. The hand hygiene reform, multidrug-resistant organisms, and surgical site infections become the hot topics in recent years. In addition, whole-genome sequencing also provides more bases for understanding pathogen transmission in hospitals. Based on the high-quality studies published in recent years, this opinion review discusses these hot topics in the prevention and control of healthcare-associated infections.
ObjectiveTo describe the status of epilepsy inpatients healthcare service in tertiary public hospitals in China by the data collected from the Hospital Quality Monitoring System.MethodsA population-based study was conducted with data of hospitalized patients collected from the Hospital Quality Monitoring System between 2015 and 2017. Diagnoses were identified by International Statistical Classification of Diseases and Related Health Problems 10th Revision codes for epilepsy (G40). The information of demographic characteristics, costs, payment methods, and discharge status were extracted and analyzed annually to make cross-sectional studies.ResultsA total of 329 241 hospitalized epilepsy patients from 585 tertiary public hospitals were identified. The average age of the patients was 31.74 and male patients accounted for 60.00% of the total. The proportion of patients covered by the national basic medical insurance in the three years was 50.15%, and that in the year 2015, 2016, and 2017 was 49.03%, 49.79%, and 51.80%, respectively; the proportion of patients with full self-payment was 30.40%. The average length of hospital stay was 6.65 d, the average cost for each stay was 7 985.53 yuan, the average self-payed cost for each stay was 3 979.62 yuan. In terms of the discharge way of the patients, 88.02% discharged following doctors’ advice, 0.40% were transferred to another hospital with doctors’ advice, and 6.59% discharged against doctors’ advice. The in-hospital mortality in the three years was 0.16%, and that in the year 2015, 2016, and 2017 was 0.19%, 0.16%, and 0.12%, respectively.ConclusionThe study shows that the in-hospital mortality rate of epilepsy inpatients in the tertiary public hospitals in China decreased gradually from 2015 to 2017, the coverage rate of national basic medical insurance increased year by year, and there is still room for further improvement.
Electronic skin has shown great application potential in many fields such as healthcare monitoring and human-machine interaction due to their excellent sensing performance, mechanical properties and biocompatibility. This paper starts from the materials selection and structures design of electronic skin, and summarizes their different applications in the field of healthcare equipment, especially current development status of wearable sensors with different functions, as well as the application of electronic skin in virtual reality. The challenges of electronic skin in the field of wearable devices and healthcare, as well as our corresponding strategies, are discussed to provide a reference for further advancing the research of electronic skin.
Objective To set up healthcare device-technology deployment assessment model and procedures through establishing the assessment parameter system between the functions of the clinical technical requirements and devices. Methods The bidirectional assessment parameter system developed by the literature review and Delphi, then combination weighting calculated by the combination weighting method, and the proposals for function deployment performed on the cluster analysis. Results The positive coefficients of twice Delphi were 75.56% and 87.50%, respectively. The effective recovery rates of the questionnaire were higher. The structure of the bidirectional assessment parameter system acquired according to the data mining and review, Delphi and integrated analysis. We calculated the weighting for the required functions and the deployed functions of the ventilator in the ICU, ER and RR. We listed the absolute importance and rank. The proposals for the function deployment of the ventilator which met different needs in fields of the critical care medicine were produced by the cluster analysis, ranking absolute importance and the calibration of weighting based on the investigation for actual function utilized rate. Conclusion It studies healthcare device-technology deployment assessment model by sequential integrated methods and sets up bidirectional assessment parameter system based on clinical technical function requirement, and the result is effective.
Objective To investigate the situation and related factors of influenza vaccination among healthcare workers in Sichuan, and provide a basis for the formulation of the strategy of influenza vaccination. Methods From August 1st to August 6th, 2022, healthcare workers from 21 prefectures and cities in Sichuan province were selected by the hospital infection quality control centers to conduct an online questionnaire survey for status and related factors of influenza vaccination. Single factor analysis of vaccination rate was carried out by χ2 test, and the related factors of influenza vaccination were analyzed by binary multiple logistic regression model. Results A total of 3264 copies of questionnaires were distributed, and 3244 valid copies were recovered, with an effective recovery rate of 99.4%. The vaccination rate of influenza vaccine in the surveyed healthcare workers was 56.9% (1846/3244). The gender, age, professional title, position, department, hospital type, hospital nature, hospital level, influenza awareness, and influenza vaccination willingness were the factors resulting in statistically significant differences in influenza vaccination rate among healthcare workers (P<0.05). Binary multiple logistic regression indicated that age≥35 years old [odds ratio (OR)=0.799, 95% confidence interval (CI) (0.681, 0.937), P=0.006], the educational background being bachelor degree or above [OR=1.221, 95%CI (1.036, 1.439), P=0.017], position [nurses vs. doctors: OR=1.339, 95%CI (1.112, 1.612), P=0.002; technicians vs. doctors: OR=1.849, 95%CI (1.278, 2.676), P=0.001], the hospital type being specialized hospital [OR=1.804, 95%CI (1.446, 2.251), P<0.001], hospital level [secondary vs. primary hospitals: OR=0.344, 95%CI (0.271, 0.437), P<0.001; tertiary vs. primary hospitals: OR=0.526, 95%CI (0.413, 0.671), P<0.001], influenza awareness [fair vs. poor: OR=1.262, 95%CI (1.057, 1.508), P=0.010; good vs. poor: OR=1.489, 95%CI (1.142, 1.940), P=0.003], vaccination willingness [OR=4.725, 95%CI (4.009, 5.569), P<0.001] were related factors of influenza vaccination in healthcare workers. The influenza awareness was good in 416 healthcare workers (12.8%), fair in 1989 (61.3%), and poor in 839 (25.9%). The correct rate of influenza vaccination frequency was the highest (82.7%), while the correct rate of influenza contraindication was the lowest (3.2%). Among the healthcare workers, 2206 (68.0%) were willing to be vaccinated, of whom 1548 (70.2%) believed that they could protect people with weak immune function around them after vaccination; 1038 were unwilling to be vaccinated with influenza vaccine in the near future, of whom 335 (32.3%) believed that they had strong immunity and did not need to be vaccinated. Conclusions The influenza vaccination rate of medical staff is related to a variety of factors. Strengthening the publicity and education, and encouraging hospitals to provide free influenza vaccination, especially the correct understanding of contraindications, may be helpful to improve the vaccination rate.
Objective To explore the impact of community healthcare workers’ (CHWs) knowledge, attitude and practice (KAP) on the influenza vaccination among elderly people. Methods By means of simple random sampling, 1 residential quarter of each communities, 2 communities of each districts, 5 districts of Chengdu city were randomly selected, and the elderly equal to or more than 60-year-old were on-site investigated. Meanwhile, the questionnaire survey was conducted among healthcare workers in the selected communities. Results There were 4 KAP factors played a positive role in influenza vaccination among elderly people: CHWs’ affirmation of the effectiveness of influenza vaccine, explicitly knowing the focus groups for influenza vaccination, recommendation of vaccination in flu season when the elderly visits, and participation in flu-related education activities. When the accuracy rate of each factor got improved by 1%, the influenza vaccination rate would improve by 2.747%, 1.299%, 0.864%, 0.602%, respectively. Conclusion The knowledge, attitude and practice of HCWs have impacts on the influenza vaccination rates of elderly people. They are significant to improve the influenza vaccination rates of the elderly.
Objective To understand the current situation of healthcare-associated infection (HAI) in comprehensive hospitals with a number of beds≥900, and provide a reference for the next step in formulating HAI prevention and control measures. Methods The data on the prevalence rate of HAI in comprehensive hospitals with a number of beds≥900 of Yunnan Province between 2020 and 2022 were retrospective collected. The HAI situation and trend in each year were analyzed. Results A total of 119 comprehensive hospitals were included, with 166 745 patients surveyed and 3 237 cases of HAI. Lower respiratory tract infection and urinary tract infection were the most common sites. The department with the highest incidence of hospital infections was the intensive care unit, followed by neurosurgery and hematology. The prevalence rates of HAI showed a downward trend from 2020 to 2022 (2.08% vs. 1.99% vs. 1.79%, χ2=14.301, P<0.001). A total of 1 315 strains of hospital-acquired pathogens were detected, all of which were mainly Gram-negative bacteria, with Escherichia coli and Klebsiella pneumoniae being more common. The rate of antibiotics use and the rate of pathogen testing showed an upward trend from 2020 to 2022 (χ2=79.233, 23.866, P<0.001), the infection rate of incision site and the prophylactic use rate of antimicrobial drugs in patients with class Ⅰ surgery both showed a decreasing trend (χ2=15.551, 6.311, P<0.05). Conclusions The prevalence of infection in comprehensive hospitals of Yunnan Province is decreasing. But the supervision of key departments, the implementation of pathogen prevention and control measures, and the rational use of antibiotics in inpatients are still the focus of future work.
Objective To use bibliometrics to identify research hotspots and emerging trends in the use of artificial intelligence (AI) in healthcare-associated infections (HAI), as well as to offer a resource for more relevant research. Methods The literature on AI and HAI from the Science Citation Index Expanded database of the Web of Science Core Collection was retrieved through computer searches, covering the period from January 1, 1994, to January 22, 2024. VOSviewer (v1.6.19) and CiteSpace (v6.1. R6) software were utilized for bibliometric analysis, creating knowledge maps that include research cooperation networks and keyword analysis. Results A total of 305 documents were included, and both the number of early publications and the frequency of citations were at a very low level for a long time before showing an annual increase trend after 2018. The United States had the most published documents among the 50 countries/regions from where they were sourced. Harvard University was the scientific research institution with the most publications, while Professor Evans HL of the Medical University of South Carolina was the scholar with the most publications. Research on AI in the field of HAI primarily focused on three aspects: AI algorithms and technologies, monitoring and prediction of HAI, and the accuracy of HAI diagnosis and prediction. These findings were based on keyword co-occurrence and clustering analysis. Conclusions A new phase of AI research in the subject of HAI has begun. More in-depth research can be done in the future for the hot direction, as there is still a gap between China’s academic accomplishments in this subject and the advanced level of the world.
Objective To construct a quality evaluation index system for healthcare-associated infection (HAI) management, and conduct an empirical evaluation on the quality of HAI management in clinical departments. Methods The literature research method and panel discussion method were adopted to initially form the framework of HAI management quality evaluation index system, and the Delphi method and the analytic hierarchy process were used to establish the index system and determine the weights from January to December 2018. Eight comprehensive evaluation methods, such as osculating value method and technique for order preference by similarity to an ideal solution method, were used to evaluate the quality of HAI management in clinical departments of West China Hospital, Sichuan University in 2018. Kendall’s coefficient of concordance (W) was used to assess the consistency of the results. The clinical departments were ranked by the standardized total scores, which were the means of the normalized scores of the eight methods. Results A quality evaluation index system for HAI management with 3 first-level indicators and 15 second-level indicators was established finally. The results of the eight comprehensive evaluation methods for the quality evaluation of HAI management in 39 clinical departments of West China Hospital, Sichuan University were consistent (W=0.952, χ2=259.800, P<0.001). The standardized total score of Department 18 was 100, which ranked the first place. Conclusion The HAI management quality evaluation index system constructed in this study could be used in clinical departments to evaluate the quality of HAI management in combination with comprehensive evaluation methods.
This paper expounds the classification and characteristics of healthcare-associated infections (HAI) surveillance systems from the perspective of the informatization needs of HAI monitoring, explains the determination requirements of numerator and denominator in the surveillance statistical data, and introduces the regular verification for auditing the quality of HAI surveillance. The basic knowledge of machine learning and its achievements are introduced in processing surveillance data as well. Machine learning may become the mainstream algorithm of HAI automatic monitoring system in the future. Infection control professionals should learn relevant knowledge, cooperate with computer engineers and data analysts to establish more effective, reasonable and accurate monitoring systems, and improve the outcomes of HAI prevention and control in medical institutions.