Recent trends in biomedical informatics: a study based on JAMIA articles

Health informatics publication trends in Saudi Arabia: a bibliometric analysis over the last twenty-four years

OBJECTIVE

Understanding health informatics (HI) publication trends in Saudi Arabia may serve as a framework for future research efforts and contribute toward meeting national "e-Health" goals. The authors' intention was to understand the state of the HI field in Saudi Arabia by exploring publication trends and their alignment with national goals.

METHODS

A scoping review was performed to identify HI publications from Saudi Arabia in PubMed, Embase, and Web of Science. We analyzed publication trends based on topics, keywords, and how they align with the Ministry of Health's (MOH's) "digital health journey" framework.

RESULTS

The total number of publications included was 242. We found 1 (0.4%) publication in 1995-1999, 11 (4.5%) publications in 2000-2009, and 230 (95.0%) publications in 2010-2019. We categorized publications into 3 main HI fields and 4 subfields: 73.1% (n=177) of publications were in clinical informatics (85.1%, n=151 medical informatics; 5.6%, n=10 pharmacy informatics; 6.8%, n=12 nursing informatics; 2.3%, n=4 dental informatics); 22.3% (n=54) were in consumer health informatics; and 4.5% (n=11) were in public health informatics. The most common keyword was "medical informatics" (21.5%, n=52). MOH framework-based analysis showed that most publications were categorized as "digitally enabled care" and "digital health foundations."

CONCLUSIONS

The years of 2000-2009 may be seen as an infancy stage of the HI field in Saudi Arabia. Exploring how the Saudi Arabian MOH's e-Health initiatives may influence research is valuable for advancing the field. Data exchange and interoperability, artificial intelligence, and intelligent health enterprises might be future research directions in Saudi Arabia.

Evaluating the outcomes of medical informatics development as a discipline in China: A publication perspective

BACKGROUND

As the world's second largest economy, China makes unique contributions to the world in many fields, including sociology, the economy, technology and defense. Medical informatics (MI) is an important cross-disciplinary field that, along with its applications, has received massive funding from the Chinese government. However, the question of how to evaluate China's input and output in MI remains important and complex issue of great significance for China and the rest of the world.

OBJECTIVE

This paper analyzed, for the first time, the quality and quantity of research by Chinese academics in MI based on their articles published in international specialty journals in recent years and examined MI research hotspots in China. Our purpose is to summarize the experiences and lessons learned by China and the rest of the world as they develop MI.

METHOD

We targeted 18 MI journals listed in the JCR 2016 report and searched for papers published by Chinese academics in these 18 journals in the WOS and PUBMED databases and on journal sites. We also performed data cleansing and categorized the obtained information. We used Excel, SPSS, Ucinet and NetDraw to conduct quantitative analyses on the research papers.

RESULTS

A total of 1340 articles satisfied the inclusion criteria of this study. We observed a significant upward trend in the number of articles published over time, particularly after 2011. Lei Jianbo, Huang Zhengxing and Li Jin-song are active Chinese authors in the MI discipline who have written many high-quality publications. Meanwhile, universities remain the primary breeding grounds for scientific research: 93.36% of the articles came from universities. Zhejiang University published the most first-author articles, whereas Zhejiang University, Shanghai Jiao Tong University and Tsinghua University produced 17.76% of the total articles. According to the lists of authors, 24% of the papers were co-authored with foreign researchers. This rate of cooperation is increasing each year, from 5.88% to the current rate of 39.04%. An analysis of keywords showed that "EMR", "SVM", "Authentication", "Telecare medical information system", "EEG", "ECG" and "RFID" were the most frequently searched terms in popular technological fields, including artificial intelligence and image processing. In recent years, there has been a significant increase in the number of high-frequency keywords and a broadening range of research fields, which has led to the emergence of several research hotspots, including MI systems, mobile health care, telecare, data mining and machine learning.

CONCLUSIONS

Through the quantitative analysis of publications, we discovered the emergence of three stages - infancy, slow growth and rapid growth - in China's MI research in recent years as academics make achievements in their research works. The global influence of Chinese academics is growing, and they are making increasingly conscious efforts to enter into research collaborations with foreign researchers. The findings of Chinese academics' publications are gaining international recognition.

Big-Data Based Decision-Support Systems to Improve Clinicians' Cognition

Complex clinical decision-making could be facilitated by using population health data to inform clinicians. In two previous studies, we interviewed 16 infectious disease experts to understand complex clinical reasoning. For this study, we focused on answers from the experts on how clinical reasoning can be supported by population-based Big-Data. We found cognitive strategies such as trajectory tracking, perspective taking, and metacognition has the potential to improve clinicians' cognition to deal with complex problems. These cognitive strategies could be supported by population health data, and all have important implications for the design of Big-Data based decision-support tools that could be embedded in electronic health records. Our findings provide directions for task allocation and design of decision-support applications for health care industry development of Big data based decision-support systems.

Medical informatics research trend analysis: A text mining approach

The objective of this research is to identify major subject areas of medical informatics and explore the time-variant changes therein. As such it can inform the field about where medical informatics research has been and where it is heading. Furthermore, by identifying subject areas, this study identifies the development trends and the boundaries of medical informatics as an academic field. To conduct the study, first we identified 26,307 articles in PubMed archives which were published in the top medical informatics journals within the timeframe of 2002 to 2013. And then, employing a text mining -based semi-automated analytic approach, we clustered major research topics by analyzing the most frequently appearing subject terms extracted from the abstracts of these articles. The results indicated that some subject areas, such as biomedical, are declining, while other research areas such as health information technology (HIT), Internet-enabled research, and electronic medical/health records (EMR/EHR), are growing. The changes within the research subject areas can largely be attributed to the increasing capabilities and use of HIT. The Internet, for example, has changed the way medical research is conducted in the health care field. While discovering new medical knowledge through clinical and biological experiments is important, the utilization of EMR/EHR enabled the researchers to discover novel medical insight buried deep inside massive data sets, and hence, data analytics research has become a common complement in the medical field, rapidly growing in popularity.

Trends in biomedical informatics: automated topic analysis of JAMIA articles

Biomedical Informatics is a growing interdisciplinary field in which research topics and citation trends have been evolving rapidly in recent years. To analyze these data in a fast, reproducible manner, automation of certain processes is needed. JAMIA is a "generalist" journal for biomedical informatics. Its articles reflect the wide range of topics in informatics. In this study, we retrieved Medical Subject Headings (MeSH) terms and citations of JAMIA articles published between 2009 and 2014. We use tensors (i.e., multidimensional arrays) to represent the interaction among topics, time and citations, and applied tensor decomposition to automate the analysis. The trends represented by tensors were then carefully interpreted and the results were compared with previous findings based on manual topic analysis. A list of most cited JAMIA articles, their topics, and publication trends over recent years is presented. The analyses confirmed previous studies and showed that, from 2012 to 2014, the number of articles related to MeSH terms Methods, Organization & Administration, and Algorithms increased significantly both in number of publications and citations. Citation trends varied widely by topic, with Natural Language Processing having a large number of citations in particular years, and Medical Record Systems, Computerized remaining a very popular topic in all years.

Publication on health policy worldwide from 1898 to 2013: identifying position of iran

BACKGROUND

As the field of health policy continues to evolve and grow, it is important to examine the trend of scientific output generated in this domain. Scientific outputs can also be used to evaluate academic progress of the field in each country or over a given period of time.

OBJECTIVE

Aim of this study is to depict trend of publication on topics of health policy world-wide and to highlight contribution of Iran in this field.

METHODS

The web of science database was used to identify all relevant published papers worldwide The search was conducted on documents published from January 1898 to December 2013. The criteria for retrieval were set to be "health policy" in topics. Then the retrieved papers were filtered in terms of distinct years, countries, source titles, and languages.

RESULTS

Findings revealed an increasing trend of publication on health policy over past decades. English was the first most dominant language of publication. USA had the highest number of publication with 5347 papers; however Switzerland ranked first after considering publication number in terms of countries' population. BMJ was the source title with highest number of publication on topics of health policy. Number of publication by Iranian authors was 87 from January 1898 to December 2013.

CONCLUSION

It seems discipline of health policy has started its evolution worldwide long time ago while Iran is in its initial phases.

Trends in publication of nursing informatics research

We analyzed 741 journal articles on nursing informatics published in 7 biomedical/nursing informatics journals and 6 nursing journals from 2005 to 2013 to begin to understand publication trends in nursing informatics research and identify gaps. We assigned a research theme to each article using AMIA 2014 theme categories and normalized the citation counts using time from publication. Overall, nursing informatics research covered a broad spectrum of research topics in biomedical informatics and publication topics seem to be well aligned with the high priority research agenda identified by the nursing informatics community. The research themes with highest volume of publication were Clinical Workflow and Human Factors, Consumer Informatics and Personal Health Records, and Clinical Informatics, for which an increasing trend in publication was noted. Articles on Informatics Education and Workforce Development; Data Mining, NLP, Information Extraction; and Clinical Informatics showed steady and high volume of citations.

Clinical research informatics and electronic health record data

OBJECTIVES

The goal of this survey is to discuss the impact of the growing availability of electronic health record (EHR) data on the evolving field of Clinical Research Informatics (CRI), which is the union of biomedical research and informatics.

RESULTS

Major challenges for the use of EHR-derived data for research include the lack of standard methods for ensuring that data quality, completeness, and provenance are sufficient to assess the appropriateness of its use for research. Areas that need continued emphasis include methods for integrating data from heterogeneous sources, guidelines (including explicit phenotype definitions) for using these data in both pragmatic clinical trials and observational investigations, strong data governance to better understand and control quality of enterprise data, and promotion of national standards for representing and using clinical data.

CONCLUSIONS

The use of EHR data has become a priority in CRI. Awareness of underlying clinical data collection processes will be essential in order to leverage these data for clinical research and patient care, and will require multi-disciplinary teams representing clinical research, informatics, and healthcare operations. Considerations for the use of EHR data provide a starting point for practical applications and a CRI research agenda, which will be facilitated by CRI's key role in the infrastructure of a learning healthcare system.