To compare the differences in antibiotic use between COPD and non-COPD residents, and to explore the effect of COPD on antibiotic use.
Participants aged 40 years old or over from the Songjiang Adult Cohort were included. Information on prescription and baseline survey was collected based on the health information system. A logit-negative binomial Hurdle model was used to explore correlations between COPD and percentage of antibiotic use and average rate of antibiotic prescribing of different types of antibiotic. Multinomial logistic regression was used to assess the association between COPD and antimicrobial combination therapy and routes of administration.
A total of 34576 individuals were included and 1594 (4.6%) were COPD patients. During the 6 years\' follow-up, the percentage of antibiotic use for COPD patients was 98.4%, which was 7.88 (95%CI: 5.24-11.85) times of that for non-COPD patients after adjusting for potential confounders. The prescribing rate was 3220 prescriptions (95%CI: 3063.6-3385.2) per 1000 person-years for COPD patients, which was 1.96 (95%CI: 1.87-2.06) times of that for non-COPD patients. Other beta-lactam antibacterials, Macrolides, lincosamides and streptogramins, and quinolone antibacterials were the most commonly used types of antibiotic. Except for aminoglycoside antibacterials, both percentage of antibiotic use and rate of antibiotic prescription were increased in COPD patients. COPD patients were more likely to be prescribed a maximum of two antibiotics (OR=1.34, 95%CI: 1.20-1.50); and were more likely to use antibiotics intravenously (OR=2.77, 95%CI: 2.47-3.11).
COPD patients were more likely to have increased antibiotic use in a large-scale population-based adult cohort, suggesting COPD patients are a high-priority group for the management of antibiotic use in communities.

Emerging studies have suggested that environmental factors are associated with fracture. However, little is known about the association of neighborhood walkability and residential greenness with fracture.
To investigate the association of long-term exposure to walkability and greenness with incident fracture and explore the potential interaction effect.
This cohort study recruited participants aged 40 years or older in Ningbo, China from June 2015 to January 2018. Participants were observed for outcomes through February 2023, with data analysis conducted in March 2023.
Neighborhood walkability was measured by a modified walkability calculation method according to a walk score tool. Residential greenness was assessed by satellite-derived normalized difference vegetation index (NDVI) within a 1000-m buffer.
Incident fracture was ascertained according to International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes via the Yinzhou Health Information System. Cox proportional hazards models were fit, with age as time scale to estimate the associations of walkability and greenness with fracture. Potential effect modification was explored by covariates, as well as the interactive effect of walkability and greenness.
A total of 23 940 participants were included in this study with 13 735 being female (57.4%). The mean (SD) age at baseline was 63.4 (9.4) years. During a follow-up period of 134 638 person-years, 3322 incident fractures were documented. In the full adjusted model, every IQR increment in neighborhood walkability and residential greenness was associated with a hazard ratio (HR) of 0.88 (95% CI, 0.83-0.92) and 0.84 (95% CI, 0.80-0.89), respectively, for fracture. Furthermore, the association of greenness and fracture was greater with an increase in walkability. The HR (Q4 vs Q1) for greenness was 0.62 (95% CI, 0.46-0.82) in neighborhoods with the highest quartile of walkability.
This population cohort study suggested that long-term exposure to neighborhood walkability and residential greenness were both associated with lower risk of incident fracture. The benefits of greenness increased in more walkable areas.

Health information systems (HISs) are continuously targeted by hackers, who aim to bring down critical health infrastructure. This study was motivated by recent attacks on health care organizations that have resulted in the compromise of sensitive data held in HISs. Existing research on cybersecurity in the health care domain places an imbalanced focus on protecting medical devices and data. There is a lack of a systematic way to investigate how attackers may breach an HIS and access health care records.
This study aimed to provide new insights into HIS cybersecurity protection. We propose a systematic, novel, and optimized (artificial intelligence-based) ethical hacking method tailored specifically for HISs, and we compared it with the traditional unoptimized ethical hacking method. This allows researchers and practitioners to identify the points and attack pathways of possible penetration attacks on the HIS more efficiently.
In this study, we propose a novel methodological approach to ethical hacking in HISs. We implemented ethical hacking using both optimized and unoptimized methods in an experimental setting. Specifically, we set up an HIS simulation environment by implementing the open-source electronic medical record (OpenEMR) system and followed the National Institute of Standards and Technology\'s ethical hacking framework to launch the attacks. In the experiment, we launched 50 rounds of attacks using both unoptimized and optimized ethical hacking methods.
Ethical hacking was successfully conducted using both optimized and unoptimized methods. The results show that the optimized ethical hacking method outperforms the unoptimized method in terms of average time used, the average success rate of exploit, the number of exploits launched, and the number of successful exploits. We were able to identify the successful attack paths and exploits that are related to remote code execution, cross-site request forgery, improper authentication, vulnerability in the Oracle Business Intelligence Publisher, an elevation of privilege vulnerability (in MediaTek), and remote access backdoor (in the web graphical user interface for the Linux Virtual Server).
This research demonstrates systematic ethical hacking against an HIS using optimized and unoptimized methods, together with a set of penetration testing tools to identify exploits and combining them to perform ethical hacking. The findings contribute to the HIS literature, ethical hacking methodology, and mainstream artificial intelligence-based ethical hacking methods because they address some key weaknesses of these research fields. These findings also have great significance for the health care sector, as OpenEMR is widely adopted by health care organizations. Our findings offer novel insights for the protection of HISs and allow researchers to conduct further research in the HIS cybersecurity domain.

Overuse and misuse of antibiotics are major factors in the development of antibiotic resistance in primary care institutions of rural China. In this study, the effectiveness of a Health Information System-based, automatic, and confidential antibiotic feedback intervention was evaluated.
A randomized, cross-over, cluster-controlled trial was conducted in primary care institutions. All institutions were randomly divided into two groups and given either a three-month intervention followed by a three-month period without any intervention or vice versa. The intervention consisted of three feedback measures: a real-time pop-up warning message of inappropriate antibiotic prescriptions on the prescribing physician\'s computer screen, a 10-day antibiotic prescription summary, and distribution of educational manuals. The primary outcome was the 10-day inappropriate antibiotic prescription rate.
There were no significant differences in inappropriate antibiotic prescription rates (69.1% vs. 72.0%) between two groups at baseline (P = 0.072). After three months (cross-over point), inappropriate antibiotic prescription rates decreased significantly faster in group A (12.3%, P < 0.001) compared to group B (4.4%, P < 0.001). At the end point, the inappropriate antibiotic prescription rates decreased in group B (15.1%, P < 0.001) while the rates increased in group A (7.2%, P < 0.001). The characteristics of physicians did not significantly affect the rate of antibiotic or inappropriate antibiotic prescription rates.
A Health Information System-based, real-time pop-up warnings, a 10-day prescription summary, and the distribution of educational manuals, can effectively reduce the rates of antibiotic and inappropriate antibiotic prescriptions.

There are various problems in diagnosing and treating tumor diseases in significant hospitals. The content includes misjudgement and over-surgery issues. For example, the judgment of pulmonary nodules mainly relies on artificial experience, and most of the artificial experience is too radical. This paper is mainly based on the extensive medical data of significant hospitals, extracts the diagnosis and treatment data and digital images of similar cases from the extensive database, classifies them through the deep learning of the computer, and then proposes the control mechanism and the solution of the doctor\'s misjudgement and excessive medical treatment. This method mainly relies on the CT and MRI digital images of various types of tumor diseases accumulated in the history of major hospitals. Based on the preliminary judgment of each diagnosis and treatment and the results of surgical and pathological examinations, the accumulation of various types of digital images from the history is used. The features are analysed and extracted, the model is built, and finally, a predictive analysis system for this type of tumor is obtained, which can predict the benign and malignant cases of currently occurring cases and avoid the limitations and instability of artificial experience greatest extent. It is proved by experiments and combined with Spearman to remove redundancy. The redundancy removal method SVM_RFE is used for dimensionality reduction. The method can timely correct the misjudgement of the doctor\'s experience and effectively reduce the instability of the manual, which provides a solution for solving the contradiction between doctors and patients and improving the scientific of diagnosis and treatment.

BACKGROUND: The overuse and abuse of antibiotics is a major risk factor for antibiotic resistance in primary care settings of China. In this study, the effectiveness of an automatically-presented, privacy-protecting, computer information technology (IT)-based antibiotic feedback intervention will be evaluated to determine whether it can reduce antibiotic prescribing rates and unreasonable prescribing behaviours.
METHODS: We will pilot and develop a cluster-randomised, open controlled, crossover, superiority trial. A total of 320 outpatient physicians in 6 counties of Guizhou province who met the standard will be randomly divided into intervention group and control group with a primary care hospital being the unit of cluster allocation. In the intervention group, the three components of the feedback intervention included: 1. Artificial intelligence (AI)-based real-time warnings of improper antibiotic use; 2. Pop-up windows of antibiotic prescription rate ranking; 3. Distribution of educational manuals. In the control group, no form of intervention will be provided. The trial will last for 6 months and will be divided into two phases of three months each. The two groups will crossover after 3 months. The primary outcome is the 10-day antibiotic prescription rate of physicians. The secondary outcome is the rational use of antibiotic prescriptions. The acceptability and feasibility of this feedback intervention study will be evaluated using both qualitative and quantitative assessment methods.
CONCLUSIONS: This study will overcome limitations of our previous study, which only focused on reducing antibiotic prescription rates. AI techniques and an educational intervention will be used in this study to effectively reduce antibiotic prescription rates and antibiotic irregularities. This study will also provide new ideas and approaches for further research in this area.
BACKGROUND: ISRCTN, ID: ISRCTN13817256. Registered on 11 January 2020.

Objective: Using data of health information system (HIS) of medical institutions to study epidemiological characteristics of herpes zoster in Xicheng district of Beijing. Methods: To collect data of outpatient herpes zoster cases of all 42 medical institutions in 2019 based on HIS. After distinguishing the reduplicated cases, we organized these data for descriptive epidemiological analysis. Results: A total of 3 982 primary outpatient cases were investigated, the estimated incidence was 3.38‰ (3 982/1 178 999). The incidence was 2.90‰ (1 655/570 320) for males and 3.82‰ (2 327/608 679) for females and with increasing trends with age. Herpes zoster occurred from January to December. These cases mainly visited tertiary hospitals, with central departments as dermatology and traditional Chinese medicine involved. For the first identified cases, the average age was (60.48±15.43) years old. The ages of disseminated herpes zoster patients was (74.00±8.98) years old, while the age of herpes zoster in the outer ear was (54.32±15.73) years old. The top three diseases were herpes zoster, post-herpetic neuralgia, and Herpes zoster with other neurological complications, with proportions as 82.65% (3 291/3 982), 10.37% (413/3 982), and 4.37% (174/3 982), respectively. Conclusions: Most herpes zoster cases were more than 50 years old in Xicheng district of Beijing, with females have seen more than males. Complications commonly occurred among individuals more than 50 years old and with the most widely seen complication as post-herpetic neuralgia.
目的： 基于医疗机构就诊电子信息系统数据分析北京市西城区带状疱疹流行特征。 方法： 利用医疗机构病例就诊电子信息系统，收集2019年北京市西城区全部42家医疗机构带状疱疹病例进行回顾性调查。收集2019年北京市西城区全部医疗机构带状疱疹病例个人基本信息和诊疗信息。经查重后筛选出现住址为西城区的门诊病例，进行描述性分析。 结果： 首次就诊的门诊病例3 982例，年发病率为3.38‰（3 982/1 178 999）。男性和女性发病率分别为2.90‰（1 655/570 320）和3.82‰（2 327/608 679），发病率随年龄增长呈增高的趋势。1-12月均有发病。病例主要就诊于三级医院，就诊科室主要为皮肤科、中医科。首诊就诊病例的年龄（60.48±15.43）岁，在带状疱疹并发症的临床类型中，播散性带状疱疹病例的年龄（74.00±8.98）岁，外耳带状疱疹病例的年龄（54.32±15.73）岁。并发症位居前3位的分别为带状疱疹（82.65%，3 291/3 982）、带状疱疹后神经痛（10.37%，413/3 982）和伴其他神经系统并发症（4.37%，174/3 982）。 结论： 2019年北京市西城区带状疱疹门诊病例以≥50岁人群为主，女性的发病率高于男性。带状疱疹并发症中，以≥50岁、带状疱疹后神经痛为主。.

Identification of the essential components of the quality of the data collection process is the starting point for designing effective data quality management strategies for public health information systems. An inductive analysis of the global literature on the quality of the public health data collection process has led to the formation of a preliminary 4D component framework, that is, data collection management, data collection personnel, data collection system, and data collection environment. It is necessary to empirically validate the framework for its use in future research and practice.
This study aims to obtain empirical evidence to confirm the components of the framework and, if needed, to further develop this framework.
Expert elicitation was used to evaluate the preliminary framework in the context of the Chinese National HIV/AIDS Comprehensive Response Information Management System. The research processes included the development of an interview guide and data collection form, data collection, and analysis. A total of 3 public health administrators, 15 public health workers, and 10 health care practitioners participated in the elicitation session. A framework qualitative data analysis approach and a quantitative comparative analysis were followed to elicit themes from the interview transcripts and to map them to the elements of the preliminary 4D framework.
A total of 302 codes were extracted from interview transcripts. After iterative and recursive comparison, classification, and mapping, 46 new indicators emerged; 24.8% (37/149) of the original indicators were deleted because of a lack of evidence support and another 28.2% (42/149) were merged. The validated 4D component framework consists of 116 indicators (82 facilitators and 34 barriers). The first component, data collection management, includes data collection protocols and quality assurance. It was measured by 41 indicators, decreased from the original 49% (73/149) to 35.3% (41/116). The second component, data collection environment, was measured by 37 indicators, increased from the original 13.4% (20/149) to 31.9% (37/116). It comprised leadership, training, funding, organizational policy, high-level management support, and collaboration among parallel organizations. The third component, data collection personnel, includes the perception of data collection, skills and competence, communication, and staffing patterns. There was no change in the proportion for data collection personnel (19.5% vs 19.0%), although the number of its indicators was reduced from 29 to 22. The fourth component, the data collection system, was measured using 16 indicators, with a slight decrease in percentage points from 18.1% (27/149) to 13.8% (16/116). It comprised functions, system integration, technical support, and data collection devices.
This expert elicitation study validated and improved the 4D framework. The framework can be useful in developing a questionnaire survey instrument for measuring the quality of the public health data collection process after validation of psychometric properties and item reduction.

BACKGROUND: China is still faced with the public health challenge of tuberculosis (TB), and a robust surveillance system is critical for developing evidence-based TB control policies. The Tuberculosis Information Management System (TBIMS), an independent system launched in 2005, has encountered several challenges in meeting the current needs of TB control. The Chinese government also planned to establish the National Health Information System (NHIS) aggregating data in different areas. The China National Health Commission-Gates TB Project Phase III launched a new TB surveillance system to address these challenges and also as a pilot for the countrywide implementation of the NHIS. This commentary highlights the improvements and challenges in implementing the new TB system and also discusses the implications for the roll-out of the NHIS.
METHODS: The new TB surveillance system piloted in each prefecture of the project provinces was designed based on the local information system under the unified principle of organizing patient information under a unique ID and realizing the function of data exchange. Upon mid-2019, the data exchange successful rate reached almost 100%, and the system showed good performance in data completeness. Major improvements of the new system included achieving automatic data extraction instead of manual entry, assisting clinical service provision, and the augmented statistical functions. The major challenges in the implementation and scale-up of the new system were the licensing issue and the diversities of infrastructures that hinder the promotion of the new system at a low cost. This pilot also accumulated experiences for the roll-out of the NHIS regarding the technical solutions of reforming current information systems as well as effective training approaches for the developers and users of the new system.
CONCLUSIONS: The successful implementation of the new TB surveillance system in the three TB designated medical institutions demonstrated how the diverse infrastructures of the information system could be reformed to achieve the functions of automatic data extraction and data exchange and better cater to the needs of healthcare workers. This pilot also accumulated rich experiences and lessons learnt for developing technical solutions and personnel training for the scale-up of the NHIS.

BACKGROUND: Health information systems (HIS) are fundamental tools for the surveillance of health services, estimation of disease burden and prioritization of health resources. Several gaps in the availability of HIS for kidney disease were highlighted by the first iteration of the Global Kidney Health Atlas.
METHODS: As part of its second iteration, the International Society of Nephrology conducted a cross-sectional global survey between July and October 2018 to explore the coverage and scope of HIS for kidney disease, with a focus on kidney replacement therapy (KRT).
RESULTS: Out of a total of 182 invited countries, 154 countries responded to questions on HIS (85% response rate). KRT registries were available in almost all high-income countries, but few low-income countries, while registries for non-dialysis chronic kidney disease (CKD) or acute kidney injury (AKI) were rare. Registries in high-income countries tended to be national, in contrast to registries in low-income countries, which often operated at local or regional levels. Although cause of end-stage kidney disease, modality of KRT and source of kidney transplant donors were frequently reported, few countries collected data on patient-reported outcome measures and only half of low-income countries recorded process-based measures. Almost no countries had programs to detect AKI and practices to identify CKD-targeted individuals with diabetes, hypertension and cardiovascular disease, rather than members of high-risk ethnic groups.
CONCLUSIONS: These findings confirm significant heterogeneity in the global availability of HIS for kidney disease and highlight important gaps in their coverage and scope, especially in low-income countries and across the domains of AKI, non-dialysis CKD, patient-reported outcomes, process-based measures and quality indicators for KRT service delivery.