Chinese experts' consensus on the application of intensive care big data.

The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts' Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.

Clinical characteristics and risk factors associated with ICU-acquired infections in sepsis: A retrospective cohort study.

Intensive care unit (ICU)-acquired infection is a common cause of poor prognosis of sepsis in the ICU. However, sepsis-associated ICU-acquired infections have not been fully characterized. The study aims to assess the risk factors and develop a model that predicts the risk of ICU-acquired infections in patients with sepsis. Methods: We retrieved data from the Medical Information Mart for Intensive Care (MIMIC) IV database. Patients were randomly divided into training and validation cohorts at a 7:3 ratio. A multivariable logistic regression model was used to identify independent risk factors that could predict ICU-acquired infection. We also assessed its discrimination and calibration abilities and compared them with classical score systems. Results: Of 16,808 included septic patients, 2,871 (17.1%) developed ICU-acquired infection. These patients with ICU-acquired infection had a 17.7% ICU mortality and 31.8% in-hospital mortality and showed a continued rise in mortality from 28 to 100 days after ICU admission. The classical Systemic Inflammatory Response Syndrome Score (SIRS), Sequential Organ Failure Assessment (SOFA), Oxford Acute Severity of Illness Score (OASIS), Simplified Acute Physiology Score II (SAPS II), Logistic Organ Dysfunction Score (LODS), Charlson Comorbidity Index (CCI), and Acute Physiology Score III (APS III) scores were associated with ICU-acquired infection, and cerebrovascular insufficiency, Gram-negative bacteria, surgical ICU, tracheostomy, central venous catheter, urinary catheter, mechanical ventilation, red blood cell (RBC) transfusion, LODS score and anticoagulant therapy were independent predictors of developing ICU-acquired infection in septic patients. The nomogram on the basis of these independent predictors showed good calibration and discrimination in both the derivation (AUROC = 0.737; 95% CI, 0.725-0.749) and validation (AUROC = 0.751; 95% CI, 0.734-0.769) populations and was superior to that of SIRS, SOFA, OASIS, SAPS II, LODS, CCI, and APS III models. Conclusions: ICU-acquired infections increase the likelihood of septic mortality. The individualized prognostic model on the basis of the nomogram could accurately predict ICU-acquired infection and optimize management or tailored therapy.

A Novel Interval-Valued q-Rung Dual Hesitant Linguistic Multi-Attribute Decision-Making Method Based on Linguistic Scale Functions and Power Hamy Mean.

The interval-valued q-rung dual hesitant linguistic (IVq-RDHL) sets are widely used to express the evaluation information of decision makers (DMs) in the process of multi-attribute decision-making (MADM). However, the existing MADM method based on IVq-RDHL sets has obvious shortcomings, i.e., the operational rules of IVq-RDHL values have some weaknesses and the existing IVq-RDHL aggregation operators are incapable of dealing with some special decision-making situations. In this paper, by analyzing these drawbacks, we then propose the operations for IVq-RDHL values based on a linguistic scale function. After it, we present novel aggregation operators for IVq-RDHL values based on the power Hamy mean and introduce the IVq-RDHL power Hamy mean operator and IVq-RDHL power weighted Hamy mean operator. Properties of these new aggregation operators are also studied. Based on these foundations, we further put forward a MADM method, which is more reasonable and rational than the existing one. Our proposed method not only provides a series of more reasonable operational laws but also offers a more powerful manner to fuse attribute values. Finally, we apply the new MADM method to solve the practical problem of patient admission evaluation. The performance and advantages of our method are illustrated in the comparative analysis with other methods.

A meta-analysis of ABCG2 gene polymorphism and non-small cell lung cancer outcomes.

We aimed to analyze the correlation between ABCG2 gene polymorphisms of 34 GG/(GA + AA) loci, 421 CC/(AC + AA) loci, and non-small cell lung cancer (NSCLC) therapeutic effects via meta-analysis. With key words, the databases PubMed and EMBASE were searched for clinical studies on ABCG2 polymorphism and NSCLC. RR and 95% CIs were used to compute combined effects, followed by heterogeneity testing. Publication bias was examined using the funnel plot method. Review Manager 5.3 software was used for the meta-analysis. Ten studies were included. No evidence of heterogeneity exists in these studies. The results indicate that two polymorphic loci of ABCG2 gene (34 G>A, and 421 C>A) had no relationship with the curative effect of chemotherapy for NSCLC, except ABCG2 34G>A, which had a significant relationship with the skin toxicity complication. There was no significant relationship between these polymorphisms and complications (skin toxicity, diarrhea, interstitial pneumonia, liver dysfunction, and neutropenia). Begg's test and Egger's test indicated that there was no obvious publication bias. The meta-analysis indicated that there was no significant correlation between ABCG2 gene polymorphism and NSCLC outcomes.

Analysis for warning factors of type 2 diabetes mellitus complications with Markov blanket based on a Bayesian network model.

BACKGROUND AND OBJECTIVE: Type 2 diabetes mellitus (T2DM) complications seriously affect the quality of life and could not be cured completely. Actions should be taken for prevention and self-management. Analysis of warning factors is beneficial for patients, on which some previous studies focused. They generally used the professional medical test factors or complete factors to predict and prevent, but it was inconvenient and impractical for patients to self-manage. With this in mind, this study built a Bayesian network (BN) model, from the perspective of diabetic patients' self-management and prevention, to predict six complications of T2DM using the selected warning factors which patients could have access from medical examination. Furthermore, the model was analyzed to explore the relationships between physiological variables and T2DM complications, as well as the complications themselves. The model aims to help patients with T2DM self-manage and prevent themselves from complications. METHODS: The dataset was collected from a well-known data center called the National Health Clinical Center between 1st January 2009 and 31st December 2009. After preprocess and impute the data, a BN model merging expert knowledge was built with Bootstrap and Tabu search algorithm. Markov Blanket (MB) was used to select the warning factors and predict T2DM complications. Moreover, a Bayesian network without prior information (BN-wopi) model learned using 10-fold cross-validation both in structure and in parameters was added to compare with other classifiers learned using 10-fold cross-validation fairly. The warning factors were selected according the structure learned in each fold and were used to predict. Finally, the performance of two BN models using warning features were compared with Naïve Bayes model, Random Forest model, and C5.0 Decision Tree model, which used all features to predict. Besides, the validation parameters of the proposed model were also compared with those in existing studies using some other variables in clinical data or biomedical data to predict T2DM complications. RESULTS: Experimental results indicated that the BN models using warning factors performed statistically better than their counterparts using all other variables in predicting T2DM complications. In addition, the proposed BN model were effective and significant in predicting diabetic nephropathy (DN) (AUC: 0.831), diabetic foot (DF) (AUC: 0.905), diabetic macrovascular complications (DMV) (AUC: 0.753) and diabetic ketoacidosis (DK) (AUC: 0.877) with the selected warning factors compared with other experiments. CONCLUSIONS: The warning factors of DN, DF, DMV, and DK selected by MB in this research might be able to help predict certain T2DM complications effectively, and the proposed BN model might be used as a general tool for prevention, monitoring, and self-management.

Is the Internet Different from Traditional Mass Media in Promoting Patient Compliance with Mature Treatments?

Background: Through mass media, some patients tend to seek mature treatment-related health information whereas some prefer information related to emerging treatments, which may influence patient compliance, specifically, following the medical diagnoses and treatment regimens. Given that traditional mass media (TMM) and the internet (INT) may promote the publication of different treatment-related information, this study aims to identify the difference between TMM and the INT in influencing patient compliance with mature treatments (PCMTs). Materials and Methods: Our subjects were Chinese who had received therapies within a month and had experience of seeking health information through mass media. An online survey involving 384 valid responses was conducted to collect data. The confirmatory factor analysis and structural equation modeling were adopted to test hypotheses. Results: Both TMM and the INT significantly affect PCMTs, through the mediation of mature treatment-related health information. Conclusions: A provision of mature treatment-related information via TMM can effectively help patients gain awareness and knowledge about treatments. In addition, physicians can update patients' knowledge by making cutting-edge treatments continuously available to patients through the mass media and analyzing patient's access patterns for different treatment-related information.

CYFRA21-1 tests in the diagnosis of non-small cell lung cancer: A meta-analysis.

OBJECTIVE: The aim of the study was to evaluate the diagnostic value of soluble fragment of cytokeratin 19 (CYFRA21-1) tests in detecting non-small cell lung cancer (NSCLC), including squamous cell carcinoma, lung adenocarcinoma, and large cell carcinoma. METHODS: The relevant studies were identified from PubMed, Embase and the Cochrane Library before November 2018. Summary estimates for sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CYFRA21-1 tests for the diagnosis of NSCLC were calculated using the random effects model. A summary receiver operating characteristic (SROC) curve was used to assess the overall effectiveness of the test. Meta-DiSc 1.4 and Stata11.0 were applied to the statistical analysis. Publication bias was detected using Egger's test. RESULTS: A total of 22 studies consisting of 7910 NSCLC patients (squamous cell carcinoma/lung adenocarcinoma/large cell carcinoma) and 2630 benign lesions patients that met the inclusion criteria were included. The meta-analysis showed that CYFRA21-1 tests had a relatively high accuracy for squamous cell carcinoma detection and a lower accuracy for lung adenocarcinoma detection. The overall sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio of CYFRA21-1 tests for squamous cell carcinoma detection were 0.72 (95% confidence interval (CI) 0.70, 0.74), 0.94 (95% CI 0.92, 0.95), 9.73 (95% CI 7.06, 13.40), 0.37 (95% CI 0.29, 0.47), and 27.30 (95% CI 17.68, 42.16), respectively. The area under the SROC curve was 0.9171 (Q* = 0.8500). No publication bias was tested in the squamous cell carcinoma (P = 0.567) and lung adenocarcinoma (P = 0.378) groups. CONCLUSIONS: CYFRA21-1 tests might be appropriate for detecting squamous cell carcinoma.

Why do patients follow physicians' advice? The influence of patients' regulatory focus on adherence: an empirical study in China.

BACKGROUND: In general, medical regimens and treatments are more likely to be effective if patients follow their physicians' advice. However, limited studies have focused on the relationship between regulatory focus and patient adherence. This study explores the antecedents of patient adherence employing regulatory focus theory. METHODS: This study established a research model consisting of two independent variables, two mediators, one dependent variable, two moderators, three control variables, and six hypotheses. An online survey involving 336 valid responses was conducted to collect data in China. We used structural equation modelling and confirmatory factor analysis to test the hypotheses and to develop the research model. RESULTS: The reliability and validity of the measures were accepted. In terms of control variables, age had a positive effect on conservative treatment-related health information seeking behaviour, and patients with different resident statuses held different attitudes towards seeking conservative treatment-related health information. However, educational level did not have any effect on the variables of the research model. The hypothesis testing results corroborate that promotion focus had a positive impact on patients' emerging treatment-related health information seeking behaviour; prevention focus had a positive impact on patients' conservative treatment-related health information seeking behaviour, which had a positive impact on patient adherence. In addition, media campaigns had a positive impact on the relationship between promotion focus and emerging treatment-related health information seeking behaviour, and website reputation had a positive impact on the relationship between prevention focus and conservative treatment-related health information seeking behaviour. CONCLUSIONS: Individuals can be encouraged to seek health information and share health-related knowledge through mass media, such as the Internet, when the quality of information, especially information from online sources, is guaranteed. In addition, physicians need to improve their professionalism and expand their knowledge of conservative healthcare. As a further application of our work, an Internet information recommendation system can be designed to recommend different types of health information for users according to their regulatory focus.

Understanding inter-organizational trust among integrated care service provider networks: A perspective on organizational asymmetries.

OBJECTIVE: To explore the factors that influence trust among the integrated healthcare service provider network in the context of seeking combined health and care services in the UK. DATA SOURCES/STUDY SETTING: Primary data were collected from three regional integrated care service provider networks from March 2016 to October 2017. STUDY DESIGN: Explorative qualitative study and inductive methods from emerging findings. DATA COLLECTION/EXTRACTION METHODS: We conducted qualitative semi-structured interviews in three care networks and collected organizational documents from local integration boards from 2016 to 2017. Thematic analysis was performed in three large care networks with hospital staff, local councils, integration boards, and community and voluntary organizations under the NHS England Better Care Fund. PRINCIPAL FINDINGS: Our findings reveal that trust among integrated care service provider networks is influenced by the following factors on various asymmetries: 1) recognition and knowledge asymmetries among care service partners of each other's skills, expertise and capabilities; 2) capacity and financial imbalances within the network; and 3) organizational differences in management, culture and attitudes toward change. CONCLUSION: There is a need to improve competence recognition and capacity imbalances and to foster open minds toward change within networks to build trust to overcome divisions and facilitate integrated services among health and care organizations.

Medical service unity: an effective approach for medical care in rural areas in China.

CONTEXT: Medical care in rural China has long suffered because of a concentration of medical resources in major hospitals in cities. The patients in rural areas thus do not have affordable access to quality medical services. To tackle such issues, a tiered medical scheme (TMS) was promoted by the Chinese State Council in 2015. It divides hospitals into three tiers and encourages collaborations among different tiers within a region in order to provide better accessibility to medical care for patients in rural areas. ISSUES: The implementation of the TMS policy has not been successful, because the previous funding model, which allocated funding to each hospital according to the number of patients treated, did not facilitate close collaborations between different hospitals. In this report, the medical service unity (MSU) approach, which has been piloted in Funan county, is reported. The MSU organises the tiered hospitals as a unity in terms of medical capabilities and financial abilities. With the radical reform of financial decentralisation, three flows are thereby enabled: the funding flow binds together the hospitals into a unity, the patient flow shares the load across the providers and eases barriers to access, and the resource flow ensures accessibility and affordability for patients. LESSONS LEARNED: The MSU approach has been shown by the pilot project in Funan to be effective for the realisation of the TMS policy, benefiting hospitals, doctors and patients. The successful experience of the Funan MSU could be introduced to other regions across China and other countries. In particular, future finance reform policies for the health system would largely benefit the health reforms and especially the decentralisation of medical resources to rural areas.

Relationship Between Internet Health Information and Patient Compliance Based on Trust: Empirical Study.

BACKGROUND: The internet has become a major mean for acquiring health information; however, Web-based health information is of mixed quality and may markedly affect patients' health-related behavior and decisions. According to the social information processing theory, patients' trust in their physicians may potentially change due to patients' health-information-seeking behavior. Therefore, it is important to identify the relationship between internet health information and patient compliance from the perspective of trust. OBJECTIVE: The objective of our study was to investigate the effects of the quality and source of internet health information on patient compliance using an empirical study based on the social information processing theory and social exchange theory. METHODS: A Web-based survey involving 336 valid participants was conducted in China. The study included independent variables (internet health information quality and source of information), 2 mediators (cognition-based trust [CBT] and affect-based trust [ABT]), 1 dependent variable (patient compliance), and 3 control variables (gender, age, and job). All variables were measured using multiple-item scales from previously validated instruments, and confirmative factor analysis as well as structural equation modeling was used to test hypotheses. RESULTS: The questionnaire response rate was 77.16% (375/486), validity rate was 89.6% (336/375), and reliability and validity were acceptable. We found that the quality and source of internet health information affect patient compliance through the mediation of CBT and ABT. In addition, internet health information quality has a stronger influence on patient compliance than the source of information. However, CBT does not have any direct effect on patient compliance, but it directly affects ABT and then indirectly impacts patient compliance. Therefore, the effect of ABT seems stronger than that of CBT. We found an unexpected, nonsignificant relationship between the source of internet health information and ABT. CONCLUSIONS: From patients' perspective, internet health information quality plays a stronger role than its source in impacting their trust in physicians and the consequent compliance with physicians. Therefore, patient compliance can be improved by strengthening the management of internet health information quality. The study findings also suggest that physicians should focus on obtaining health information from health websites, thereby expanding their understanding of patients' Web-based health-information-seeking preferences, and enriching their knowledge structure to show their specialization and reliability in the communication with patients. In addition, the mutual demonstration of care and respect in the communication between physicians and patients is important in promoting patients' ABT in their physicians.

A Novel Multiattribute Decision-Making Method Based on Point⁻Choquet Aggregation Operators and Its Application in Supporting the Hierarchical Medical Treatment System in China.

The hierarchical medical treatment system is an efficient way to solve the problem of insufficient and unbalanced medical resources in China. Essentially, classifying the different degrees of diseases according to the doctor's diagnosis is a key step in pushing forward the hierarchical medical treatment system. This paper proposes a framework to solve the problem where diagnosis values are given as picture fuzzy numbers (PFNs). Point operators can reduce the uncertainty of doctor's diagnosis and get intensive information in the process of decision making, and the Choquet integral operator can consider correlations among symptoms. In order to take full advantage of these two kinds of operators, in this paper, we firstly define some point operators under the picture fuzzy environment, and further propose a new class of picture fuzzy point⁻Choquet integral aggregation operators. Moreover, some desirable properties of these operators are also investigated in detail. Then, a novel approach based on these operators for multiattribute decision-making problems in the picture fuzzy context is introduced. Finally, we give an example to illustrate the applicability of the new approach in assisting hierarchical medical treatment system. This is of great significance for integrating the medical resources of the whole society and improving the service efficiency of the medical service system.

Mature or Emerging? The Impact of Treatment-Related Internet Health Information Seeking on Patients' Trust in Physicians.

Years of clinical trials have proven the maturity and safety of certain treatments, however, some of these mature treatments may not be highly effective. Several treatments have emerged through technological innovations, but their long-term safety, efficacy, and adverse effects remain unknown. At present, many patients seek information related to their treatments on the Internet, which may impact their attitudes towards different treatments and their trust in physicians. In this study, a research model was developed to examine how patients' trust in their physicians is influenced by related online information on mature or emerging treatments. The hypotheses were tested using confirmatory factor analysis (CFA) and structural equation modelling (SEM). A total of 336 valid responses were collected through an online survey. Mature treatments related health information was found to significantly improve patients' trust. Thus, physicians should pay more attention to mature treatments, and encourage their patients to seek related information online. Moreover, the quality of online information should be developed further to increase patients' satisfaction. Physicians should also consider their patients' psychological safety in communication with patients to strengthen their trust.

A Text Structuring Method for Chinese Medical Text Based on Temporal Information.

Chinese Electronic Medical Records (EMRs) contains a large number of complex medical free text which includes a variety of information, such as temporal information, patients' symptoms and laboratory data. However, as an important knowledge base, these unstructured text data in EMR are hard to process directly by computer to support further medical research. This paper proposes a novel text structuring method to extract knowledge from EMR texts and reorganize them in chronological order according to the temporal information in the text. By implementing some entropy-based algorithms as contrast, experiments evaluate the performance of the proposed method, which indicates the new method can significantly reduce the complexity of EMR text. This work is significant in structuring the EMR free text into temporal-structured data for further medical analysis.

A Knowledge-Constrained Access Control Model for Protecting Patient Privacy in Hospital Information Systems.

Current access control mechanisms of the hospital information system can hardly identify the real access intention of system users. A relaxed access control increases the risk of compromise of patient privacy. To reduce unnecessary access of patient information by hospital staff, this paper proposes a knowledge-constrained role-based access control (KC-RBAC) model in which a variety of medical domain knowledge is considered in access control. Based on the proposed Purpose Tree and knowledge-involved algorithms, the model can dynamically define the boundary of access to the patient information according to the context, which helps to protect patient privacy by controlling access. Compared with the role-based access control model, KC-RBAC can effectively protect patient information according to the results of the experiments.