Mining electronic health records using artificial intelligence: Bibliometric and content analyses for current research status and product conversion.

BACKGROUND: The use of Electronic Health Records is the most important milestone in the digitization and intelligence of the entire medical industry. AI can effectively mine the immense medical information contained in EHRs, potentially assist doctors in reducing many medical errors. OBJECTIVE: This article aims to summarize the research status and trends in using AI to mine medical information from EHRs for the past thirteen years and investigate its information application. METHODS: A systematic search was carried out in 5 databases, including Web of Science Core Collection and PubMed, to identify research using AI to mine medical information from EHRs for the past thirteen years. Furthermore, bibliometric and content analysis were used to explore the research hotspots and trends, and systematically analyze the conversion rate of research resources in this field. RESULTS: A total of 631 articles were included and analyzed. The number of published articles has increased rapidly after 2017, with an average annual growth rate of 55.73%. The US (41.68%) and China (19.65%) publish the most articles, but there is a lack of international cooperation. The extraction of disease lesions is a hot topic at present, and the research topic is gradually shifting from disease risk grading to disease risk prediction. Classification (66%), and regress (15%) are the main implemented AI tasks. For AI algorithms, deep learning (31.70%), decision tree algorithms family (26.47%), and regression algorithms family (17.43%) are used most frequently. The funding rate for publications is 69.26%, and the input-output conversion rate is 21.05%. CONCLUSIONS: Over the past decade, the use of AI to mine medical information from EHRs has been developing rapidly. However, it is necessary to strengthen international cooperation, improve EHRs data availability, focus on interpretable AI algorithms, and improve the resource conversion rate in future research.

The Plant-Beneficial Rhizobacterium Bacillus velezensis FZB42 Controls the Soybean Pathogen Phytophthora sojae Due to Bacilysin Production.

Soybean root rot caused by the oomycete Phytophthora sojae is a serious soilborne disease threatening soybean production in China. Bacillus velezensis FZB42 is a model strain for Gram-positive plant growth-promoting rhizobacteria and is able to produce multiple antibiotics. In this study, we demonstrated that B. velezensis FZB42 can efficiently antagonize P. sojae. The underlying mechanism for the inhibition was then investigated. The FZB42 mutants deficient in the synthesis of lipopeptides (bacillomycin D and fengycin), known to have antifungal activities, and polyketides (bacillaene, difficidin, and macrolactin), known to have antibacterial activities, were not impaired in their antagonism toward P. sojae; in contrast, mutants deficient in bacilysin biosynthesis completely lost their antagonistic activities toward P. sojae, indicating that bacilysin was responsible for the activity. Isolated pure bacilysin confirmed this inference. Bacilysin was previously shown to be antagonistic mainly toward prokaryotic bacteria rather than eukaryotes. Here, we found that bacilysin could severely damage the hyphal structures of P. sojae and lead to the loss of its intracellular contents. A device was invented allowing interactions between P. sojae and B. velezensis FZB42 on nutrient agar. In this manner, the effect of FZB42 on P. sojae was studied by transcriptomics. FZB42 significantly inhibited the expression of P. sojae genes related to growth, macromolecule biosynthesis, pathogenicity, and ribosomes. Among them, the genes for pectate lyase were the most significantly downregulated. Additionally, we showed that bacilysin effectively prevents soybean sprouts from being infected by P. sojae and could antagonize diverse Phytophthora species, such as Phytophthora palmivora, P. melonis, P. capsici, P. litchi, and, most importantly, P. infestans. IMPORTANCEPhytophthora spp. are widespread eukaryotic phytopathogens and often extremely harmful. Phytophthora can infect many types of plants important to agriculture and forestry and thus cause large economic losses. Perhaps due to inappropriate recognition of Phytophthora as a common pathogen in history, research on the biological control of Phytophthora is limited. This study shows that B. velezensis FZB42 can antagonize various Phytophthora species and prevent the infection of soybean seedlings by P. sojae. The antibiotic produced by FZB42, bacilysin, which was already known to have antibacterial effectiveness, is responsible for the inhibitory action against Phytophthora. We further showed that some Phytophthora genes and pathways may be targeted in future biocontrol studies. Therefore, our data provide a basis for the development of new tools for the prevention and control of root and stem rot in soybean and other plant diseases caused by Phytophthora.

Adoption of Electronic Health Records (EHRs) in China During the Past 10 Years: Consecutive Survey Data Analysis and Comparison of Sino-American Challenges and Experiences.

BACKGROUND: The adoption rate of electronic health records (EHRs) in hospitals has become a main index to measure digitalization in medicine in each country. OBJECTIVE: This study summarizes and shares the experiences with EHR adoption in China and in the United States. METHODS: Using the 2007-2018 annual hospital survey data from the Chinese Health Information Management Association (CHIMA) and the 2008-2017 United States American Hospital Association Information Technology Supplement survey data, we compared the trends in EHR adoption rates in China and the United States. We then used the Bass model to fit these data and to analyze the modes of diffusion of EHRs in these 2 countries. Finally, using the 2007, 2010, and 2014 CHIMA and Healthcare Information and Management Systems Services survey data, we analyzed the major challenges faced by hospitals in China and the United States in developing health information technology. RESULTS: From 2007 to 2018, the average adoption rates of the sampled hospitals in China increased from 18.6% to 85.3%, compared to the increase from 9.4% to 96% in US hospitals from 2008 to 2017. The annual average adoption rates in Chinese and US hospitals were 6.1% and 9.6%, respectively. However, the annual average number of hospitals adopting EHRs was 1500 in China and 534 in the US, indicating that the former might require more effort. Both countries faced similar major challenges for hospital digitalization. CONCLUSIONS: The adoption rates of hospital EHRs in China and the United States have both increased significantly in the past 10 years. The number of hospitals that adopted EHRs in China exceeded 16,000, which was 3.3 times that of the 4814 nonfederal US hospitals. This faster adoption outcome may have been a benefit of top-level design and government-led policies, particularly the inclusion of EHR adoption as an important indicator for performance evaluation and the appointment of public hospitals.

MiR-330-3p contributes to INS-1 cell dysfunction by targeting glucokinase in gestational diabetes mellitus.

AIMS: High-expressed miR-330-3p in gestational diabetes mellitus (GDM) patients was reported. However, the role and mechanism of miR-330-3p in GDM are rarely reported. In this research, we aim to investigate the effects of miR-330-3p on GDM. METHODS: MiR-330-3p expression in the GDM patients' blood was determined by q-PCR. Blood glucose of blood samples was detected using blood glucose detection kits. Glucokinase (GCK) was confirmed to be a target gene of miR-330-3p by bioinformatics and luciferase analysis. Correlations between miR-330-3p with GCK and blood glucose were analyzed by Pearson correlation analysis. After INS-1 cells were treated with glucose and transfected with mimic, inhibitor or siGCK, GCK expression was detected by western blot, and q-PCR, enzyme-linked immunosorbent assays, cell counting kit-8 and Annexin-V/propidium iodide were conducted to examine the expression of insulin, cell viability and apoptosis. RESULTS: MiR-330-3p was high-expressed in GDM patients' blood, while GCK was low-expressed. The miR-330-3p expression level positively correlated with blood glucoseand and it was highly expressed in glucose-treated INS-1 cells (11 and 22 mmol/L), while miR-330-3p expression negatively correlated with GCK expression. GCK expression was inhibited by miR-330-3p mimic and enhanced by the miR-330-3p inhibitor. MiR-330-3p mimic inhibited INS-1 cells' insulin expression, cell viability and induced apoptosis. Yet miR-330-3p inhibitor and siGCK exhibited opposite effects which miR-330-3p mimic and GCK played on INS-1 cells. In addition, siGCK reversed the effect of miR-330-3p inhibitor on INS-1 cells. CONCLUSION: Our findings proved that miR-330-3p targeting GCK lead to the dysfunction of INS-1 cells in GDM, and could become a therapeutic target for GDM treatment.

A Preliminary Study on the Abnormal Deaths and Work Burden of Chinese Physicians: A Mixed Method Analysis and Implications for Smart Hospital Management.

Background: The population of Chinese physicians is frequently threatened by abnormal death, including death by overwork or homicide. This is not only a health problem, but also a social problem that has attracted the attention of both hospitals and the government. Objective: This study aims to analyze the characteristics of abnormal death in physicians in Chinese hospitals from 2007 to 2020 and to investigate the relationship between abnormal death and physician workload, in order to provide information for policy makers and request improvement technologies. Methods: A mixed research method was used. In order to ensure accuracy and completeness, a relatively comprehensive search was conducted using multiple heterogeneous data sources on the abnormal death of physicians in Chinese hospitals from 2007 to 2020. The collected cases were then descriptively analyzed using the work-related overwork death risk concept framework and the deductive grounded theory approach. In addition, the workload of physicians was calculated between 2007 and 2019 based on three important workload indicators. Results: Between 2007 and 2020, 207 abnormal death events of physicians on the Chinese mainland were publicly reported. Among the 207 victims, the majority (~79%) died from overwork or sudden death. The number of victims who were men was 5.5 times higher than that of women, and victims were between the ages of 31-50 years. These physicians mainly belonged to the departments of surgery, anesthesiology, internal medicine, and orthopedics. Further analysis of the direct causes of death in cases of overwork death showed that 51 physicians (31.1%) died from cardiogenic diseases. Additionally, the per capita workload of physicians in China increased drastically by about 42% from 2007 to 2019, far exceeding physician workloads in Europe, Asia, and Australia (number of inpatients per physician in 2017: 72 vs. 55, 50, 45). The analysis revealed that there was a strong correlation between the number of abnormal deaths of physicians in China and the number of inpatients per physician (r = 0.683, P = 0.01). Conclusion: High-intensity working conditions may be positively correlated with the number of abnormal deaths among physicians. Smart hospital technologies have the potential to alleviate this situation.

A Comparison of the Development of Medical Informatics in China and That in Western Countries from 2008 to 2018: A Bibliometric Analysis of Official Journal Publications.

Objective: We focused on medical informatics journal publications rather than on conference proceedings by comparing and analyzing the data from journals and conferences from a broader perspective. The aim is to summarize the unique contributions of China to medical digitization and foster more multilevel international cooperation. Method: In February 2019, publications from 2008 to 2018 in three major English-language medical informatics journals were retrieved through Scopus, including the journals, namely, International Journal of Medical Informatics (IJMI, international community), JAMIA (United States), and Methods of Information in Medicine (MIM, Europe). Three major Chinese-language journals, namely, China Digital Medicine (CDM), Chinese Journal of Health Informatics and Management (CJHIM), and Chinese Journal of Medical Library and Information Science (CJMLIS), were searched within the major three Chinese literature databases. The datasets were preprocessed using the NLP package on Python, and a smart local moving algorithm was used as a clustering method for identifying the aforementioned journals. Result: Between 2008 and 2018, the total number of published papers and H-index of the three English-language journals was 1371 and 67 (IJMI), 1752 and 86 (JAMIA), and 637 and 35 (MIM), respectively. In the same period, the total number of published papers and H-index in the three Chinese-language journals was 6668 and 23 (CDM), 1668 and 22 (CJHIM), and 2557 and 25 (CJMLIS), respectively. IJMI, JAMIA, and MIM received submissions from 82, 59, and 62 countries/regions, respectively. By contrast, the three Chinese journals only received submissions from seven foreign countries. The proportions of authors from institutional affiliations were similar between the three English-language journals (IJMI, JAMIA, and MIM) and CJMLIS because the majority of the authors were from universities (81%, 74%, 73%, and 65.2%), followed by medical institutions (12%, 10%, 9%, and 23.4%) or research institutes (2%, 4%, 10%, and 4.3%). Furthermore, the proportions of the authors from enterprises were low (2%, 6%, 4%, and 0.3%) for all journals. However, the authors in CDM and CJHIM were mainly from medical institutions (50% and 40%), followed by universities (33% and 32%) and research institutes (3% and 4%). In addition, the proportions of enterprises were only 3% and 2%, respectively. Among the top five authors in three English-language journals (ranked in terms of the number of published papers), 100% had doctoral or master's degrees, compared with only 60% in the Chinese journals. Additionally, 28204 different keywords were extracted from the aforementioned papers, covering 275 specific high-frequency key terms. Based on these key terms, four clusters were found in the English literature-"Health and Clinical Information Systems," "Internet and Telemedicine," "Medical Data Statistical Analysis," and "EHRs and Information Management"-and three clusters were found in the Chinese literature: "Hospital Information Systems and EMR," "Library Science and Bibliometrics Analysis," and "Medical Reform Policy and Health Digitization." Only two clusters are similar, and Chinese-language journals focus more on health information in technology and industrial applications than in medical informatics basic research. Conclusion: This study provides important insights into the development of medical informatics (MI) in China and Western countries showing that the medical informatics journals of China, the United States, and Europe have distinct characteristics. Specifically, first, compared with the Western journals, the number of papers published in the journals of professional associations in the field of MI in China is large and the application value is high, but the academic influence and academic value are relatively low; second, most of the authors of the Chinese papers are from hospitals, and most of the counterparts in the Western countries are from universities. The proportion of master's or doctoral degrees in the former is also lower than that of the latter; furthermore, regarding paper themes, on the one hand, China MI has no theoretical and basic research on medical data statistics and consumer health based on the Internet and telemedicine; on the other hand, after nearly 10 years of hospital digital development, China has fully used the latecomer and application advantages in hospitals and, through extensive international cooperation, has made significant advancements in and contributions to the development of medical information.

Evaluating the Applications of Health Information Technologies in China During the Past 11 Years: Consecutive Survey Data Analysis.

BACKGROUND: To achieve universal access to medical resources, China introduced its second health care reform in 2010, with health information technologies (HIT) as an important technical support point. OBJECTIVE: This study is the first attempt to explore the unique contributions and characteristics of HIT development in Chinese hospitals from the three major aspects of hospital HIT-human resources, funding, and materials-in an all-around, multi-angled, and time-longitudinal manner, so as to serve as a reference for decision makers in China and the rest of the world when formulating HIT development strategies. METHODS: A longitudinal research method is used to analyze the results of the CHIMA Annual Survey of Hospital Information System in China carried out by a Chinese national industrial association, CHIMA, from 2007 to 2018. The development characteristics of human resources, funding, and materials of HIT in China for the past 12 years are summarized. The Bass model is used to fit and predict the popularization trend of EMR in Chinese hospitals from 2007 to 2020. RESULTS: From 2007 to 2018, the CHIMA Annual Survey interviewed 10,954 hospital CIOs across 32 administrative regions in Mainland China. Compared with 2007, as of 2018, in terms of human resources, the average full time equivalent (FTE) count in each hospital's IT center is still lower than the average level of US counterparts in 2014 (9.66 FTEs vs. 34 FTEs). The proportion of CIOs with a master's degree or above was 25.61%, showing an increase of 18.51%, among which those with computer-related backgrounds accounted for 64.75%, however, those with a medical informatics background only accounted for 3.67%. In terms of funding, the sampled hospitals' annual HIT investment increased from ¥957,700 (US $136,874) to ¥6.376 million (US $911,261), and the average investment per bed increased from ¥4,600 (US $658) to ¥8,100 (US $1158). In terms of information system construction, as of 2018, the average EMR implementation rate of the sampled hospitals exceeded the average level of their US counterparts in 2015 and their German counterparts in 2017 (85.26% vs. 83.8% vs. 68.4%, respectively). The results of the Bass prediction model show that Chinese hospitals will likely reach an adoption rate of 91.4% by 2020 (R2=0.95). CONCLUSIONS: In more than 10 years, based on this top-down approach, China's medical care industry has accepted government instructions and implemented the unified model planned by administrative intervention. With only about one-fifth of the required funding, and about one-fourth of the required human resources per hospital as compared to the US HITECH project, China's EMR coverage in 2018 exceeded the average level of its US counterparts in 2015 and German counterparts in 2017. This experience deserves further study and analysis by other countries.